roadmap.ipynb

{
 "cells": [
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "---\n",
    "description: package for working with itslive ice velocity data\n",
    "output-file: index.html\n",
    "title: ITS_LIVE_TOOL\n",
    "skip_showdoc: true\n",
    "skip_exec: true\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "# ROADMAP\n",
    "\n",
    "## About\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "\n",
    "`ITS_LIVE_TOOL` is a package designed to aid users working with the [Inter-mission Time Series of Land Ice Velocity and Elevation](link) (ITS_LIVE) dataset. The package provides functions for accessing data as well as various methods to process ITS_LIVE observations. This notebook will demonstrate various elements of the package and walk through the steps of a typical workflow using ITS_LIVE_TOOL. \n",
    "\n",
    "## Overview \n",
    "\n",
    "- Data Access\n",
    "- Organization\n",
    "- Data Processing\n",
    "- Velocity Inversion\n",
    "\n",
    "### Data Access + Organization\n",
    "\n",
    "#### 1. Interactive map widget\n",
    "\n",
    "This is an interactive widget design to streamline access ITS_LIVE image pair ice velocity time series. \n",
    "\n",
    "#### 2. Organization: `Glacier`, `Glacier_Centerline`, `Glacier_Point` objects\n",
    "\n",
    "These are provided to store and keep track of different types of data related to individual units of analysis such as points, centerlines or full glacier surface areas. \n",
    "\n",
    "This roadmap document will first demonstrate data access and organization tools before demonstrating the processing tools. \n",
    "\n",
    "### Data Processing\n",
    "\n",
    "We demonstrate and make available two processing routines. Be sure to check out the accompanying [book]() and consider if either of these are appropriate for your data and use case. Note that these methods are in active development and thus should be considered in *beta* phase. Please perform your own data inspection and due diligence if implementing these methods. \n",
    "\n",
    "#### Inversion\n",
    "\n",
    "The Velocity Inversion solves ITS_LIVE's velocity timestamp issue. It inputs the length in time of all satellite pairs and recalculates a velocity that weighs each ITS_LIVE velocities falling withing the same time-window. It is a way of correcting and interpolating the dataset.\n",
    "\n",
    "### Processing\n",
    "\n",
    "We demonstrate and make available two processing routines. Be sure to check out the accompanying [book]() and consider if either of these are appropriate for your data and use case. Note that these methods are in active development and thus should be considered in *beta* phase. Please perform your own data inspection and due diligence if implementing these methods. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from ITS_LIVE_TOOL import datacube_tools, interactive, programmatic_access, obj_setup, preprocess, invert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pyproj\n",
    "import matplotlib.path as path\n",
    "import s3fs\n",
    "import zarr\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy\n",
    "from datetime import timedelta\n",
    "from tqdm import tqdm\n",
    "import xarray as xr\n",
    "import re\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.path as mplp\n",
    "import ipyleaflet as ipyl\n",
    "from ipyleaflet import WMSLayer\n",
    "import ipywidgets as ipyw\n",
    "import json\n",
    "import pandas as pd\n",
    "from ipyleaflet import Map, WMSLayer, basemaps, GeoData\n",
    "from ipywidgets import HTML\n",
    "from owslib.wms import WebMapService"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Install\n",
    "\n",
    "Install this package using the below command \n",
    "\n",
    "```{note}\n",
    "someday we hope to have a pip or conda install, for now use pip install git+ github repo url\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "# Section 1: Data Access + Organization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Data access: Interactive, Programmatic options\n",
    "### How to use\n",
    "\n",
    "There are two ways to access data using ITS_LIVE_TOOL. The first way is through the interactive widget. This is great for exploratory analysis. The second way is by specifying an RGI ID and point coordinates manually. This is useful if you already know which glacier(s) you want to examine and simply want to pass a list of RGI IDs and coordinates. We'll first demonstrate using the interactive widget.\n",
    "\n",
    "## Interactive data selection widget\n",
    "\n",
    "First, use the interactive map to select data. Do this by right- and left-clicking on the map location where you'd like to access data. \n",
    "This will return an object containing the coordinates of the point you clicked, a `geopandas.GeoDataFrame` of the [RGI7](http://www.glims.org/rgi_user_guide/welcome.html) data for that glacier and the URL of the ITS_LIVE granule covering the clicked point. \n",
    "\n",
    "```{note}\n",
    "If the glacier you want to study lies in multiple ITS_LIVE granules, or you'd like to look at multiple glaciers, click in multiple points and the output objects will be appended with each click. \n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#| eval: false\n",
    "#| output: false\n",
    "\n",
    "data_map = interactive.Widget()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fb9c32ec09cc4c438112682ada0c36e2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "GridBox(children=(VBox(children=(Map(center=[0, 0], controls=(ZoomControl(options=['position', 'zoom_in_text',…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| eval: false\n",
    "#| output: false\n",
    "data_map.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### If you want to directly invert the dataset, jump to section 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[36.47706744492884, 74.10346028493463]]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_map.added_coords"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Create data objects\n",
    "\n",
    "Once you have made your selection(s) on the map, use the following methods to create objects that will store your data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### If you've only selected one glacier, create individual objects as follows: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['http://its-live-data.s3.amazonaws.com/datacubes/v2/N30E070/ITS_LIVE_vel_EPSG32643_G0120_X450000_Y4050000.zarr']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_map.urls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "glacier = interactive.create_glacier_from_click(data_map, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'RGI60-14.03035'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier.rgi_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "original xy [74.10346028493463, 36.47706744492884] 4326 maps to datacube (419685.50940682524, 4037237.8990700087) EPSG:32643\n",
      "subset and load at   4.59 seconds\n"
     ]
    }
   ],
   "source": [
    "glacier_point = interactive.create_glacier_point_from_click(data_map, 0, 'phony label')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "glacier_centerline = interactive.create_glacier_centerline_from_click(data_map, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "As you can see, these objects all store data related to the same glacier that was selected, but at different spatial scales. The `glacier` object contains an RGIID, name and the RGI outline and attributes for that glacier. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "glacier.outline_prj.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `glacier_point` object also has the RGI ID and name inherited from the map widget but additionally contains ITS_LIVE image pair velocity time series data for the selected point as well as a 3x3 pixel cube surrounding the point. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
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       "\n",
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       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
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       "  width: auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (time_numeric: 198, x: 3, y: 3)\n",
       "Coordinates:\n",
       "    mid_date               (time_numeric) datetime64[ns] 2005-05-21T13:56:05....\n",
       "  * x                      (x) float64 4.544e+05 4.545e+05 4.546e+05\n",
       "  * y                      (y) float64 3.884e+06 3.884e+06 3.884e+06\n",
       "    img_separation         (time_numeric) float64 193.0 81.0 40.0 ... 81.0 48.0\n",
       "  * time_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    obs_id                 (time_numeric) int64 10 15 16 18 ... 501 502 503 507\n",
       "    mapping                int64 0\n",
       "Data variables:\n",
       "    v                      (time_numeric, y, x) float32 99.0 100.0 ... nan nan\n",
       "    vy                     (time_numeric, y, x) float32 -96.0 -96.0 ... nan nan\n",
       "    vx                     (time_numeric, y, x) float32 -23.0 -28.0 ... nan nan\n",
       "    v_error                (time_numeric, y, x) float32 34.0 34.0 ... nan nan\n",
       "    satellite_img1         (time_numeric) &lt;U2 &#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2A&#x27; &#x27;8&#x27; &#x27;8&#x27;\n",
       "    satellite_img2         (time_numeric) &lt;U2 &#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2B&#x27; &#x27;8&#x27; &#x27;8&#x27;\n",
       "    acquisition_date_img1  (time_numeric) datetime64[ns] 2005-02-14T13:55:19....\n",
       "    acquisition_date_img2  (time_numeric) datetime64[ns] 2005-08-25T13:56:51....\n",
       "    img1_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    img2_numeric           (time_numeric) float64 2.006e+03 ... 2.023e+03\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.8\n",
       "    GDAL_AREA_OR_POINT:         Area\n",
       "    author:                     ITS_LIVE, a NASA MEaSUREs project (its-live.j...\n",
       "    autoRIFT_parameter_file:    http://its-live-data.s3.amazonaws.com/autorif...\n",
       "    datacube_software_version:  1.0\n",
       "    date_created:               25-Sep-2023 21:37:37\n",
       "    ...                         ...\n",
       "    s3:                         s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    skipped_granules:           s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    time_standard_img1:         UTC\n",
       "    time_standard_img2:         UTC\n",
       "    title:                      ITS_LIVE datacube of image pair velocities\n",
       "    url:                        https://its-live-data.s3.amazonaws.com/datacu...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-36ce0d4c-4cdf-4ff3-8eb7-3d05cf2f0d91' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-36ce0d4c-4cdf-4ff3-8eb7-3d05cf2f0d91' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time_numeric</span>: 198</li><li><span class='xr-has-index'>x</span>: 3</li><li><span class='xr-has-index'>y</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-18579c55-3004-4e09-9371-144c39b3e93a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18579c55-3004-4e09-9371-144c39b3e93a' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mid_date</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-05-21T13:56:05.476257920 .....</div><input id='attrs-f21be731-2821-4140-93b8-daac60664658' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f21be731-2821-4140-93b8-daac60664658' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7cd2c90-1274-4695-805e-27e2c51d9571' class='xr-var-data-in' type='checkbox'><label for='data-d7cd2c90-1274-4695-805e-27e2c51d9571' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>midpoint of image 1 and image 2 acquisition date and time with granule&#x27;s centroid longitude and latitude as microseconds</dd><dt><span>standard_name :</span></dt><dd>image_pair_center_date_with_time_separation</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-05-21T13:56:05.476257920&#x27;, &#x27;2005-10-05T13:51:57.072903936&#x27;,\n",
       "       &#x27;2005-10-25T01:53:53.027030016&#x27;, &#x27;2005-12-08T13:51:50.355538944&#x27;,\n",
       "       &#x27;2006-12-27T13:52:45.628609024&#x27;, &#x27;2007-02-01T02:00:32.390277120&#x27;,\n",
       "       &#x27;2013-09-24T14:10:41.508634880&#x27;, &#x27;2014-05-11T14:01:03.502896896&#x27;,\n",
       "       &#x27;2015-04-08T14:02:25.238568704&#x27;, &#x27;2015-05-02T14:02:10.928819968&#x27;,\n",
       "       &#x27;2016-06-12T14:08:28.667504896&#x27;, &#x27;2016-06-21T14:02:47.279838976&#x27;,\n",
       "       &#x27;2016-06-29T14:02:49.153263104&#x27;, &#x27;2016-06-29T14:02:25.177506048&#x27;,\n",
       "       &#x27;2016-07-23T14:02:58.401550080&#x27;, &#x27;2016-09-28T14:10:15.826789120&#x27;,\n",
       "       &#x27;2017-03-08T14:00:51.170215936&#x27;, &#x27;2017-03-28T14:00:56.170215680&#x27;,\n",
       "       &#x27;2017-04-09T09:20:15.023084032&#x27;, &#x27;2017-04-17T14:00:56.170328064&#x27;,\n",
       "       &#x27;2017-04-17T14:03:37.177678848&#x27;, &#x27;2017-04-21T09:20:15.480677120&#x27;,\n",
       "       &#x27;2017-04-25T00:02:50.282385920&#x27;, &#x27;2017-05-03T09:20:16.071468032&#x27;,\n",
       "       &#x27;2017-05-07T00:02:50.876837120&#x27;, &#x27;2017-05-15T02:00:50.170215936&#x27;,\n",
       "       &#x27;2017-05-31T00:02:52.098582272&#x27;, &#x27;2017-06-04T02:00:50.170328064&#x27;,\n",
       "       &#x27;2017-06-08T09:20:18.071277056&#x27;, &#x27;2017-06-12T00:02:52.930807040&#x27;,\n",
       "       &#x27;2017-06-20T09:20:18.817405952&#x27;, &#x27;2017-06-24T02:00:55.170507008&#x27;,\n",
       "       &#x27;2017-06-24T02:00:45.170328064&#x27;, &#x27;2017-06-24T00:02:53.591259648&#x27;,\n",
       "       &#x27;2017-07-06T00:02:54.250789888&#x27;, &#x27;2017-07-14T02:00:50.170507008&#x27;,\n",
       "       &#x27;2017-08-19T09:20:22.140303872&#x27;, &#x27;2017-08-30T14:00:44.170810112&#x27;,\n",
       "       &#x27;2017-08-30T14:10:03.975674880&#x27;, &#x27;2017-10-14T14:03:12.434516992&#x27;,\n",
       "       &#x27;2017-10-14T14:02:48.462993920&#x27;, &#x27;2017-11-23T14:00:44.170918912&#x27;,\n",
       "       &#x27;2017-12-06T02:00:45.170918912&#x27;, &#x27;2018-01-26T14:02:46.627106048&#x27;,\n",
       "       &#x27;2018-02-09T02:00:50.180126720&#x27;, &#x27;2018-02-11T14:02:12.836626944&#x27;,\n",
       "       &#x27;2018-03-11T02:00:50.180220928&#x27;, &#x27;2018-03-23T14:00:49.180126976&#x27;,\n",
       "       &#x27;2018-04-02T14:00:56.180220928&#x27;, &#x27;2018-04-05T02:00:50.180220928&#x27;,\n",
       "       &#x27;2018-04-20T02:00:55.180327936&#x27;, &#x27;2018-04-22T14:00:49.180328192&#x27;,\n",
       "       &#x27;2018-05-02T14:02:07.337032192&#x27;, &#x27;2018-05-10T14:02:01.673700096&#x27;,\n",
       "       &#x27;2018-05-15T02:00:55.180512000&#x27;, &#x27;2018-05-26T14:01:51.852726784&#x27;,\n",
       "       &#x27;2018-05-26T14:01:27.879087104&#x27;, &#x27;2018-06-03T14:02:14.519867904&#x27;,\n",
       "       &#x27;2018-06-19T14:01:40.725254656&#x27;, &#x27;2018-07-21T14:02:34.972747008&#x27;,\n",
       "       &#x27;2018-07-31T14:00:56.180512000&#x27;, &#x27;2018-08-03T02:00:50.180517120&#x27;,\n",
       "       &#x27;2018-08-05T14:00:49.180517120&#x27;, &#x27;2018-08-06T14:02:25.151774976&#x27;,\n",
       "       &#x27;2018-08-14T14:02:19.488528128&#x27;, &#x27;2018-08-14T14:01:55.512768000&#x27;,\n",
       "       &#x27;2018-09-07T14:02:08.359054080&#x27;, &#x27;2018-10-04T14:00:51.180919040&#x27;,\n",
       "       &#x27;2018-10-22T02:00:50.181018880&#x27;, &#x27;2018-10-24T14:00:46.180919040&#x27;,\n",
       "       &#x27;2018-10-24T14:00:51.181018880&#x27;, &#x27;2018-10-27T02:00:50.181024000&#x27;,\n",
       "       &#x27;2018-11-08T14:00:46.181018880&#x27;, &#x27;2018-11-11T02:00:45.181024000&#x27;,\n",
       "       &#x27;2018-11-13T14:00:46.181029376&#x27;, &#x27;2018-11-28T14:00:51.181018880&#x27;,\n",
       "       &#x27;2018-12-01T02:00:50.181024000&#x27;, &#x27;2018-12-03T14:00:51.181029120&#x27;,\n",
       "       &#x27;2018-12-18T14:00:46.181127936&#x27;, &#x27;2019-01-05T02:00:50.181018880&#x27;,\n",
       "       &#x27;2019-01-07T14:00:49.181024000&#x27;, &#x27;2019-01-12T14:08:35.233935872&#x27;,\n",
       "       &#x27;2019-01-25T02:00:45.181127936&#x27;, &#x27;2019-02-14T02:00:50.190106880&#x27;,\n",
       "       &#x27;2019-04-20T02:00:55.190322944&#x27;, &#x27;2019-06-06T14:00:54.190322688&#x27;,\n",
       "       &#x27;2019-09-24T14:00:59.190819840&#x27;, &#x27;2019-12-18T13:58:49.191028992&#x27;,\n",
       "       &#x27;2020-01-20T01:58:45.200101888&#x27;, &#x27;2020-04-29T09:20:37.827311104&#x27;,\n",
       "       &#x27;2020-05-23T09:20:39.169659904&#x27;, &#x27;2020-05-30T14:08:24.289006080&#x27;,\n",
       "       &#x27;2020-06-07T14:08:27.323486976&#x27;, &#x27;2020-06-28T09:20:41.190839040&#x27;,\n",
       "       &#x27;2020-07-09T14:08:36.175726080&#x27;, &#x27;2020-07-28T02:01:00.200724992&#x27;,\n",
       "       &#x27;2020-08-29T14:01:01.200730112&#x27;, &#x27;2020-09-04T14:03:09.871563008&#x27;,\n",
       "       &#x27;2020-09-04T14:02:45.895802880&#x27;, &#x27;2020-09-13T14:00:59.200724736&#x27;,\n",
       "       &#x27;2020-09-16T02:01:00.200730112&#x27;, &#x27;2020-09-20T14:02:51.417906944&#x27;,\n",
       "       &#x27;2020-09-20T14:03:15.387312896&#x27;, &#x27;2020-10-16T02:01:00.200928256&#x27;,\n",
       "       &#x27;2020-11-05T02:00:55.200730112&#x27;, &#x27;2020-12-05T02:00:55.200928000&#x27;,\n",
       "       &#x27;2020-12-22T14:00:54.201102080&#x27;, &#x27;2020-12-30T02:00:55.200928000&#x27;,\n",
       "       &#x27;2021-01-16T14:00:54.201102080&#x27;, &#x27;2021-01-25T14:08:55.679889920&#x27;,\n",
       "       &#x27;2021-03-07T14:00:49.210210048&#x27;, &#x27;2021-04-06T14:00:49.210401024&#x27;,\n",
       "       &#x27;2021-05-14T02:00:55.210210048&#x27;, &#x27;2021-05-17T14:08:54.364303872&#x27;,\n",
       "       &#x27;2021-06-08T02:00:55.210401024&#x27;, &#x27;2021-06-13T02:00:35.210401024&#x27;,\n",
       "       &#x27;2021-06-25T14:00:34.210401024&#x27;, &#x27;2021-07-12T14:08:44.122251008&#x27;,\n",
       "       &#x27;2021-08-06T14:02:40.784208640&#x27;, &#x27;2021-08-06T14:03:04.759968768&#x27;,\n",
       "       &#x27;2021-08-19T14:00:41.210813696&#x27;, &#x27;2021-08-22T14:02:46.222813952&#x27;,\n",
       "       &#x27;2021-09-01T02:00:40.210813952&#x27;, &#x27;2021-09-06T02:00:20.210823936&#x27;,\n",
       "       &#x27;2021-10-09T14:03:14.522573056&#x27;, &#x27;2021-11-02T14:03:09.149243904&#x27;,\n",
       "       &#x27;2021-11-05T14:08:59.326223104&#x27;, &#x27;2021-11-07T14:00:36.210823936&#x27;,\n",
       "       &#x27;2021-11-17T14:00:56.210813952&#x27;, &#x27;2021-11-20T02:00:35.210918144&#x27;,\n",
       "       &#x27;2021-11-22T14:00:36.210823936&#x27;, &#x27;2021-11-26T14:02:38.860225024&#x27;,\n",
       "       &#x27;2021-11-26T14:03:02.833867008&#x27;, &#x27;2021-12-04T14:02:41.133965056&#x27;,\n",
       "       &#x27;2021-12-05T02:00:35.210918144&#x27;, &#x27;2021-12-16T14:02:57.085885952&#x27;,\n",
       "       &#x27;2021-12-16T14:02:33.112256000&#x27;, &#x27;2021-12-20T02:00:55.210813952&#x27;,\n",
       "       &#x27;2021-12-24T14:02:35.385997056&#x27;, &#x27;2021-12-25T02:00:35.210823936&#x27;,\n",
       "       &#x27;2021-12-31T14:08:40.290598912&#x27;, &#x27;2022-01-06T14:00:34.210917888&#x27;,\n",
       "       &#x27;2022-01-21T14:03:09.431980032&#x27;, &#x27;2022-02-05T14:00:51.220121088&#x27;,\n",
       "       &#x27;2022-02-05T14:08:57.912832000&#x27;, &#x27;2022-02-10T14:03:08.301616128&#x27;,\n",
       "       &#x27;2022-02-10T14:03:03.683998976&#x27;, &#x27;2022-02-13T14:09:06.082394880&#x27;,\n",
       "       &#x27;2022-02-14T14:03:04.067568128&#x27;, &#x27;2022-02-14T14:03:19.531324928&#x27;,\n",
       "       &#x27;2022-02-17T14:08:57.613480704&#x27;, &#x27;2022-02-22T14:02:57.833542144&#x27;,\n",
       "       &#x27;2022-03-06T14:02:58.319587328&#x27;, &#x27;2022-03-10T02:00:50.220121088&#x27;,\n",
       "       &#x27;2022-03-17T14:08:42.872955904&#x27;, &#x27;2022-03-25T02:00:50.220219904&#x27;,\n",
       "       &#x27;2022-03-25T14:08:42.642470912&#x27;, &#x27;2022-03-30T14:02:52.004399104&#x27;,\n",
       "       &#x27;2022-03-30T14:02:28.032887040&#x27;, &#x27;2022-04-11T14:03:26.129437696&#x27;,\n",
       "       &#x27;2022-04-30T14:09:08.664752128&#x27;, &#x27;2022-05-01T13:59:06.220121088&#x27;,\n",
       "       &#x27;2022-05-04T14:08:44.281606912&#x27;, &#x27;2022-05-04T14:09:00.195837952&#x27;,\n",
       "       &#x27;2022-05-04T14:08:27.602799104&#x27;, &#x27;2022-05-05T14:03:20.765026048&#x27;,\n",
       "       &#x27;2022-05-16T13:59:06.220219904&#x27;, &#x27;2022-05-20T14:08:56.200190976&#x27;,\n",
       "       &#x27;2022-05-25T14:02:39.244381952&#x27;, &#x27;2022-05-25T14:03:03.220130304&#x27;,\n",
       "       &#x27;2022-05-29T14:03:14.449838080&#x27;, &#x27;2022-05-29T14:02:50.480432128&#x27;,\n",
       "       &#x27;2022-06-14T14:03:23.987036928&#x27;, &#x27;2022-06-14T14:02:57.472257024&#x27;,\n",
       "       &#x27;2022-06-17T14:09:11.454739968&#x27;, &#x27;2022-06-17T14:08:53.394595072&#x27;,\n",
       "       &#x27;2022-06-18T01:59:05.220425984&#x27;, &#x27;2022-06-18T14:03:08.701966080&#x27;,\n",
       "       &#x27;2022-06-18T14:02:44.732572928&#x27;, &#x27;2022-06-21T14:08:44.925680896&#x27;,\n",
       "       &#x27;2022-06-25T14:08:49.629519104&#x27;, &#x27;2022-06-29T14:08:41.160605184&#x27;,\n",
       "       &#x27;2022-07-03T14:09:07.459094272&#x27;, &#x27;2022-07-08T14:03:17.671849984&#x27;,\n",
       "       &#x27;2022-07-23T14:08:45.683539968&#x27;, &#x27;2022-07-28T14:03:11.923976704&#x27;,\n",
       "       &#x27;2022-07-31T14:08:46.565105664&#x27;, &#x27;2022-08-12T14:08:52.419506944&#x27;,\n",
       "       &#x27;2022-08-13T14:03:19.918085888&#x27;, &#x27;2022-08-13T14:02:55.944456960&#x27;,\n",
       "       &#x27;2022-09-05T14:09:11.475632128&#x27;, &#x27;2022-09-09T14:09:03.006725888&#x27;,\n",
       "       &#x27;2022-09-13T14:08:57.824007936&#x27;, &#x27;2022-09-22T14:03:23.140098048&#x27;,\n",
       "       &#x27;2022-09-25T14:09:18.211599872&#x27;, &#x27;2022-09-26T01:57:15.220808960&#x27;,\n",
       "       &#x27;2022-09-26T14:03:34.369815040&#x27;, &#x27;2022-10-12T14:03:37.776432896&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.544e+05 4.545e+05 4.546e+05</div><input id='attrs-3679d3a4-9053-49ac-a40a-02aadc6eaa00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3679d3a4-9053-49ac-a40a-02aadc6eaa00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e6a3c4e-9cd2-4ddd-8e3c-672fd78c4138' class='xr-var-data-in' type='checkbox'><label for='data-6e6a3c4e-9cd2-4ddd-8e3c-672fd78c4138' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([454372.5, 454492.5, 454612.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.884e+06 3.884e+06 3.884e+06</div><input id='attrs-32893208-c5b8-4a11-ba5d-1e729e821d9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32893208-c5b8-4a11-ba5d-1e729e821d9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75199c20-6d38-40fb-97e5-0cdfeb423318' class='xr-var-data-in' type='checkbox'><label for='data-75199c20-6d38-40fb-97e5-0cdfeb423318' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([3883987.5, 3883867.5, 3883747.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img_separation</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>193.0 81.0 40.0 ... 95.0 81.0 48.0</div><input id='attrs-db477115-5f9f-4c34-b9f4-d9627e3930d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db477115-5f9f-4c34-b9f4-d9627e3930d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0889eb29-4933-44ec-9305-eb49d1d566ff' class='xr-var-data-in' type='checkbox'><label for='data-0889eb29-4933-44ec-9305-eb49d1d566ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([193.,  81.,  40., 129.,  49.,  72.,  16.,   8.,  32.,  16.,  17.,\n",
       "        49.,  65.,  65.,  17.,   9.,  40.,  81.,  13.,  41.,  41.,  13.,\n",
       "        13.,  13.,  13., 175.,  13., 135.,  13.,  13.,  13.,  95., 175.,\n",
       "        13.,  13., 135.,  13.,  40.,  41.,  49.,  49., 131., 156., 160.,\n",
       "        26., 192.,  35., 110.,  81.,  85.,  46.,  50.,  32.,  48.,   5.,\n",
       "        16.,  16.,  96.,  65., 193., 160., 156., 160., 161., 145., 145.,\n",
       "        97.,  30.,   5.,  70.,  10.,   6.,  40.,  35.,  30.,  80.,  76.,\n",
       "        70.,  41., 155., 150.,  48., 116.,  75.,  56., 151.,  70., 100.,\n",
       "        35.,  13.,  13.,  65.,  81.,  13.,  17.,   6.,  60.,  17.,  17.,\n",
       "       100.,  95.,  17.,  17.,  35., 195., 135., 100., 185., 150.,  32.,\n",
       "        50.,  10., 186., 193., 136., 145., 170.,  81.,  17.,  17.,  10.,\n",
       "        17.,  35.,  25., 113., 161., 153., 151., 190., 126., 181., 208.,\n",
       "       208., 192., 156., 248., 248., 255., 232., 246., 264., 221.,  96.,\n",
       "        30.,  32., 361., 136., 353.,  48., 369., 361., 353.,  88.,  95.,\n",
       "       112.,  65.,  64.,  40.,  40., 257., 201., 200., 144., 208.,  16.,\n",
       "       209., 170., 177., 153., 153., 161., 161., 289., 113., 297., 105.,\n",
       "       105., 121., 121., 113.,  89.,  97., 265., 241., 145., 201.,  33.,\n",
       "       185.,   9.,   9.,  56.,  49., 121.,  89.,  97.,  95.,  81.,  48.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.005e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-5e67e9b6-116f-466e-8409-605ac7e3f1b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e67e9b6-116f-466e-8409-605ac7e3f1b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19c2e865-d34b-4ffb-b84d-4b398bb1415f' class='xr-var-data-in' type='checkbox'><label for='data-19c2e865-d34b-4ffb-b84d-4b398bb1415f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.386301, 2005.761644, 2005.816438, 2005.936986, 2006.989041,\n",
       "       2007.087671, 2013.731507, 2014.358904, 2015.268493, 2015.334247,\n",
       "       2016.449315, 2016.473973, 2016.49589 , 2016.49589 , 2016.561644,\n",
       "       2016.745205, 2017.183562, 2017.238356, 2017.271233, 2017.293151,\n",
       "       2017.293151, 2017.30411 , 2017.315068, 2017.336986, 2017.347945,\n",
       "       2017.369863, 2017.413699, 2017.424658, 2017.435616, 2017.446575,\n",
       "       2017.468493, 2017.479452, 2017.479452, 2017.479452, 2017.512329,\n",
       "       2017.534247, 2017.632877, 2017.663014, 2017.663014, 2017.786301,\n",
       "       2017.786301, 2017.89589 , 2017.931507, 2018.071233, 2018.109589,\n",
       "       2018.115068, 2018.191781, 2018.224658, 2018.252055, 2018.260274,\n",
       "       2018.30137 , 2018.306849, 2018.334247, 2018.356164, 2018.369863,\n",
       "       2018.4     , 2018.4     , 2018.421918, 2018.465753, 2018.553425,\n",
       "       2018.580822, 2018.589041, 2018.594521, 2018.59726 , 2018.619178,\n",
       "       2018.619178, 2018.684932, 2018.758904, 2018.808219, 2018.813699,\n",
       "       2018.813699, 2018.821918, 2018.854795, 2018.863014, 2018.868493,\n",
       "       2018.909589, 2018.917808, 2018.923288, 2018.964384, 2019.013699,\n",
       "       2019.019178, 2019.032877, 2019.068493, 2019.123288, 2019.30137 ,\n",
       "       2019.430137, 2019.731507, 2019.964384, 2020.054795, 2020.328767,\n",
       "       2020.394521, 2020.413699, 2020.435616, 2020.493151, 2020.523288,\n",
       "       2020.575342, 2020.663014, 2020.679452, 2020.679452, 2020.70411 ,\n",
       "       2020.712329, 2020.723288, 2020.723288, 2020.794521, 2020.849315,\n",
       "       2020.931507, 2020.978082, 2021.      , 2021.043836, 2021.068493,\n",
       "       2021.180822, 2021.263014, 2021.367123, 2021.375342, 2021.435616,\n",
       "       2021.449315, 2021.482192, 2021.528767, 2021.59726 , 2021.59726 ,\n",
       "       2021.632877, 2021.641096, 2021.668493, 2021.682192, 2021.772603,\n",
       "       2021.838356, 2021.846575, 2021.852055, 2021.879452, 2021.887671,\n",
       "       2021.893151, 2021.90411 , 2021.90411 , 2021.926027, 2021.928767,\n",
       "       2021.958904, 2021.958904, 2021.969863, 2021.980822, 2021.983562,\n",
       "       2022.      , 2022.016438, 2022.057534, 2022.09863 , 2022.09863 ,\n",
       "       2022.112329, 2022.112329, 2022.120548, 2022.123288, 2022.123288,\n",
       "       2022.131507, 2022.145205, 2022.178082, 2022.189041, 2022.208219,\n",
       "       2022.230137, 2022.230137, 2022.243836, 2022.243836, 2022.276712,\n",
       "       2022.328767, 2022.331507, 2022.339726, 2022.339726, 2022.339726,\n",
       "       2022.342466, 2022.372603, 2022.383562, 2022.39726 , 2022.39726 ,\n",
       "       2022.408219, 2022.408219, 2022.452055, 2022.452055, 2022.460274,\n",
       "       2022.460274, 2022.463014, 2022.463014, 2022.463014, 2022.471233,\n",
       "       2022.482192, 2022.493151, 2022.50411 , 2022.517808, 2022.558904,\n",
       "       2022.572603, 2022.580822, 2022.613699, 2022.616438, 2022.616438,\n",
       "       2022.679452, 2022.690411, 2022.70137 , 2022.726027, 2022.734247,\n",
       "       2022.736986, 2022.736986, 2022.780822])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obs_id</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10 15 16 18 20 ... 501 502 503 507</div><input id='attrs-a38864ff-58ab-49c1-af2d-60f10d4bffb7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a38864ff-58ab-49c1-af2d-60f10d4bffb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e1e7d37-a990-4278-a653-e2b10f2124ec' class='xr-var-data-in' type='checkbox'><label for='data-7e1e7d37-a990-4278-a653-e2b10f2124ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 10,  15,  16,  18,  20,  21,  24,  27,  35,  36,  47,  49,  51,\n",
       "        52,  53,  54,  62,  65,  67,  69,  70,  71,  72,  73,  74,  75,\n",
       "        80,  83,  85,  86,  87,  88,  89,  91,  92,  93,  99, 101, 102,\n",
       "       110, 111, 120, 122, 129, 131, 132, 138, 142, 144, 145, 148, 149,\n",
       "       151, 153, 154, 155, 156, 157, 160, 166, 167, 168, 170, 172, 174,\n",
       "       175, 180, 183, 185, 186, 187, 188, 190, 192, 193, 195, 197, 198,\n",
       "       200, 204, 205, 208, 211, 214, 229, 239, 260, 271, 275, 288, 292,\n",
       "       293, 295, 297, 298, 300, 303, 304, 305, 307, 308, 310, 311, 316,\n",
       "       320, 326, 328, 331, 333, 335, 341, 349, 354, 355, 359, 363, 365,\n",
       "       369, 373, 374, 377, 379, 381, 383, 390, 395, 396, 397, 400, 401,\n",
       "       402, 404, 405, 406, 407, 410, 411, 412, 414, 415, 416, 417, 418,\n",
       "       420, 421, 424, 425, 426, 427, 428, 429, 430, 432, 433, 434, 436,\n",
       "       437, 439, 440, 442, 444, 446, 447, 448, 449, 450, 451, 453, 455,\n",
       "       456, 457, 458, 460, 461, 463, 464, 466, 467, 468, 469, 471, 472,\n",
       "       474, 477, 481, 483, 484, 486, 487, 488, 497, 498, 499, 500, 501,\n",
       "       502, 503, 507])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mapping</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bebbbffc-5fca-4a4b-ade1-294ec8520d96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bebbbffc-5fca-4a4b-ade1-294ec8520d96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67ecc9bc-132a-4115-9580-f3234428ee6e' class='xr-var-data-in' type='checkbox'><label for='data-67ecc9bc-132a-4115-9580-f3234428ee6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19S&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,10000000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32719&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 19S</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-69.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>10000000.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19S&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,10000000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32719&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>454312.5 120.0 0.0 3884047.5 0.0 -120.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0919857e-4eea-4632-ad90-d0de594d317a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0919857e-4eea-4632-ad90-d0de594d317a' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>99.0 100.0 103.0 ... 125.0 nan nan</div><input id='attrs-16e092ca-97de-404b-b35b-4dbf6c130496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16e092ca-97de-404b-b35b-4dbf6c130496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a59a6bc-8233-49dc-8749-c9475d41979b' class='xr-var-data-in' type='checkbox'><label for='data-9a59a6bc-8233-49dc-8749-c9475d41979b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity magnitude</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[ 99., 100., 103.],\n",
       "        [106., 103., 107.],\n",
       "        [113., 106., 109.]],\n",
       "\n",
       "       [[102., 103., 110.],\n",
       "        [106., 107., 116.],\n",
       "        [116., 117., 120.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [139., 123., 107.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[222., 234., 225.],\n",
       "        [156., 211., 241.],\n",
       "        [149., 179., 225.]],\n",
       "\n",
       "       [[271., 257., 228.],\n",
       "        [281., 254., 228.],\n",
       "        [266., 263., 231.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [125.,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vy</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-96.0 -96.0 -96.0 ... nan nan</div><input id='attrs-c38b2382-80e0-46b0-8d4b-d1a6003249b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c38b2382-80e0-46b0-8d4b-d1a6003249b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e510ca3-a814-4a5d-a942-936fb381f808' class='xr-var-data-in' type='checkbox'><label for='data-9e510ca3-a814-4a5d-a942-936fb381f808' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity component in y direction</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_y_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[ -96.,  -96.,  -96.],\n",
       "        [-105.,  -99.,  -97.],\n",
       "        [-112., -101.,  -96.]],\n",
       "\n",
       "       [[ -93.,  -90.,  -92.],\n",
       "        [ -98.,  -94.,  -96.],\n",
       "        [-112., -109., -107.]],\n",
       "\n",
       "       [[  nan,   nan,   nan],\n",
       "        [  nan,   nan,   nan],\n",
       "        [-132., -106.,  -62.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-169., -181., -180.],\n",
       "        [-141., -172., -188.],\n",
       "        [-144., -155., -174.]],\n",
       "\n",
       "       [[-197., -197., -180.],\n",
       "        [-201., -188., -180.],\n",
       "        [-197., -197., -184.]],\n",
       "\n",
       "       [[  nan,   nan,   nan],\n",
       "        [  nan,   nan,   nan],\n",
       "        [-124.,   nan,   nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vx</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-23.0 -28.0 -36.0 ... -14.0 nan nan</div><input id='attrs-e2c4b1bd-495a-4653-9a3a-8cd187ab4e29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2c4b1bd-495a-4653-9a3a-8cd187ab4e29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34e098d1-a1c4-471e-aab9-6123c0be0b32' class='xr-var-data-in' type='checkbox'><label for='data-34e098d1-a1c4-471e-aab9-6123c0be0b32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity component in x direction</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_x_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[-23., -28., -36.],\n",
       "        [ -8., -26., -47.],\n",
       "        [-17., -35., -52.]],\n",
       "\n",
       "       [[ 42.,  50.,  61.],\n",
       "        [ 38.,  50.,  65.],\n",
       "        [ 30.,  42.,  54.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [-44., -63., -87.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[144., 148., 135.],\n",
       "        [ 67., 122., 151.],\n",
       "        [ 38.,  90., 142.]],\n",
       "\n",
       "       [[187., 166., 140.],\n",
       "        [196., 170., 140.],\n",
       "        [179., 174., 140.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [-14.,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_error</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.0 34.0 34.0 ... 45.0 nan nan</div><input id='attrs-1bc66bcf-ec36-48b1-bdc0-0662f376c9a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bc66bcf-ec36-48b1-bdc0-0662f376c9a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d059a62-6cfd-4958-81e9-96f1b171b27c' class='xr-var-data-in' type='checkbox'><label for='data-1d059a62-6cfd-4958-81e9-96f1b171b27c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity magnitude error</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>velocity_error</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[34., 34., 34.],\n",
       "        [33., 34., 34.],\n",
       "        [34., 34., 34.]],\n",
       "\n",
       "       [[31., 31., 31.],\n",
       "        [32., 31., 31.],\n",
       "        [32., 32., 31.]],\n",
       "\n",
       "       [[nan, nan, nan],\n",
       "        [nan, nan, nan],\n",
       "        [72., 80., 97.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[46., 46., 46.],\n",
       "        [47., 46., 46.],\n",
       "        [47., 47., 46.]],\n",
       "\n",
       "       [[30., 30., 30.],\n",
       "        [30., 30., 30.],\n",
       "        [30., 30., 31.]],\n",
       "\n",
       "       [[nan, nan, nan],\n",
       "        [nan, nan, nan],\n",
       "        [45., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satellite_img1</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2A&#x27; &#x27;8&#x27; &#x27;8&#x27;</div><input id='attrs-0a6be035-d7b8-4664-9cf9-372ff6111731' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a6be035-d7b8-4664-9cf9-372ff6111731' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c64017dc-caa7-4a30-b8fd-502a51b3dd0d' class='xr-var-data-in' type='checkbox'><label for='data-c64017dc-caa7-4a30-b8fd-502a51b3dd0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>id of the satellite that acquired image 1</dd><dt><span>standard_name :</span></dt><dd>image1_satellite</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;1A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1A&#x27;, &#x27;1A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;1B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satellite_img2</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2B&#x27; &#x27;8&#x27; &#x27;8&#x27;</div><input id='attrs-4662352e-b04d-4d26-adc9-8688a1e0349f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4662352e-b04d-4d26-adc9-8688a1e0349f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ec85319-6abe-4a3e-8895-bac33344cc74' class='xr-var-data-in' type='checkbox'><label for='data-4ec85319-6abe-4a3e-8895-bac33344cc74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>id of the satellite that acquired image 2</dd><dt><span>standard_name :</span></dt><dd>image2_satellite</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;8&#x27;, &#x27;7&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;7&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;7&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;1A&#x27;, &#x27;2B&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;1A&#x27;, &#x27;1A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;7&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;1B&#x27;, &#x27;1B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acquisition_date_img1</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-02-14T13:55:19.335019008 .....</div><input id='attrs-2bd82003-da1c-4162-8ff3-165a11973200' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bd82003-da1c-4162-8ff3-165a11973200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d760ab06-c318-4559-bf2f-8700f71a0a1e' class='xr-var-data-in' type='checkbox'><label for='data-d760ab06-c318-4559-bf2f-8700f71a0a1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-02-14T13:55:19.335019008&#x27;, &#x27;2005-08-26T13:51:50.091519872&#x27;,\n",
       "       &#x27;2005-10-05T13:50:39.712999936&#x27;, &#x27;2005-10-05T13:50:39.712999936&#x27;,\n",
       "       &#x27;2006-12-03T13:52:41.298648064&#x27;, &#x27;2006-12-27T13:57:21.876056064&#x27;,\n",
       "       &#x27;2013-09-16T14:10:43.906659072&#x27;, &#x27;2014-05-07T14:02:12.261967872&#x27;,\n",
       "       &#x27;2015-03-23T14:02:31.445444096&#x27;, &#x27;2015-04-24T14:02:18.731047680&#x27;,\n",
       "       &#x27;2016-06-04T14:08:26.525222912&#x27;, &#x27;2016-05-28T14:02:37.871211008&#x27;,\n",
       "       &#x27;2016-05-28T14:02:37.871211008&#x27;, &#x27;2016-05-28T14:02:13.891217920&#x27;,\n",
       "       &#x27;2016-07-15T14:02:56.367411968&#x27;, &#x27;2016-09-24T14:08:59.990775040&#x27;,\n",
       "       &#x27;2017-02-16T14:00:51.000000000&#x27;, &#x27;2017-02-16T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-04-03T09:20:14.619289088&#x27;, &#x27;2017-03-28T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-03-28T14:02:10.970647040&#x27;, &#x27;2017-04-15T09:20:15.086074368&#x27;,\n",
       "       &#x27;2017-04-19T00:02:49.861679360&#x27;, &#x27;2017-04-27T09:20:15.534450944&#x27;,\n",
       "       &#x27;2017-05-01T00:02:50.362253824&#x27;, &#x27;2017-02-16T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-05-25T00:02:51.403804928&#x27;, &#x27;2017-03-28T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-06-02T09:20:17.459141120&#x27;, &#x27;2017-06-06T00:02:52.452308992&#x27;,\n",
       "       &#x27;2017-06-14T09:20:18.342210048&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-03-28T14:00:51.000000000&#x27;, &#x27;2017-06-18T00:02:53.068093952&#x27;,\n",
       "       &#x27;2017-06-30T00:02:53.773188864&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-08-13T09:20:21.639132928&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-08-10T14:08:47.411077888&#x27;, &#x27;2017-09-20T14:03:08.592884992&#x27;,\n",
       "       &#x27;2017-09-20T14:02:44.617125888&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:00:39.000000000&#x27;, &#x27;2017-11-07T14:03:15.934309120&#x27;,\n",
       "       &#x27;2018-01-27T14:00:49.000000000&#x27;, &#x27;2017-11-07T14:02:51.967021056&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-01-27T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-02-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-03-28T14:00:49.000000000&#x27;, &#x27;2018-03-28T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-04-16T14:02:16.977689856&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-18T14:01:57.335540992&#x27;,\n",
       "       &#x27;2018-05-18T14:01:33.364018944&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-18T14:01:33.364018944&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-17T14:00:49.000000000&#x27;, &#x27;2018-05-18T14:01:57.335540992&#x27;,\n",
       "       &#x27;2018-06-03T14:01:46.008876800&#x27;, &#x27;2018-06-03T14:01:22.033117952&#x27;,\n",
       "       &#x27;2018-07-21T14:01:47.725454080&#x27;, &#x27;2018-09-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-09-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-24T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-24T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-10-29T14:00:51.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-10-29T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-12-19T14:08:38.390475008&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-08-20T14:00:58.999999744&#x27;, &#x27;2019-10-29T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-01-02T14:00:51.000000000&#x27;, &#x27;2020-04-23T09:20:37.314803968&#x27;,\n",
       "       &#x27;2020-05-17T09:20:38.514753024&#x27;, &#x27;2020-04-28T14:08:15.236611072&#x27;,\n",
       "       &#x27;2020-04-28T14:08:15.236611072&#x27;, &#x27;2020-06-22T09:20:40.675356928&#x27;,\n",
       "       &#x27;2020-07-01T14:08:32.940545024&#x27;, &#x27;2020-07-25T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-08-27T14:03:06.368505088&#x27;,\n",
       "       &#x27;2020-08-27T14:02:42.388508928&#x27;, &#x27;2020-07-25T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-09-12T14:02:49.001443072&#x27;,\n",
       "       &#x27;2020-09-12T14:03:12.972966912&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2021-01-09T14:08:59.173716992&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:08:51.765843968&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-06-02T14:08:31.280954880&#x27;,\n",
       "       &#x27;2021-07-29T14:02:37.408684032&#x27;, &#x27;2021-07-29T14:03:01.384444160&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-14T14:02:43.738276096&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:03:07.714035968&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-08-24T14:00:21.000000000&#x27;, &#x27;2021-08-14T14:02:43.738276096&#x27;,\n",
       "       &#x27;2021-08-14T14:03:07.714035968&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-14T14:02:43.738276096&#x27;, &#x27;2021-08-14T14:01:01.000000000&#x27;,\n",
       "       &#x27;2021-08-30T14:02:48.285724928&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-02-20T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-03-10T14:02:33.560546048&#x27;, &#x27;2021-12-04T14:03:20.909481984&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-01-20T14:09:01.688460032&#x27;,\n",
       "       &#x27;2022-04-26T14:08:31.147535104&#x27;, &#x27;2022-01-21T14:03:10.162823680&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-02-21T14:08:53.696965120&#x27;,\n",
       "       &#x27;2022-03-10T14:02:33.560546048&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-04-26T14:08:31.147535104&#x27;,\n",
       "       &#x27;2022-04-26T14:00:49.000000000&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:08:31.147535104&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-05-12T14:08:23.617210880&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-05-12T14:08:23.617210880&#x27;,\n",
       "       &#x27;2022-08-09T14:03:08.467568896&#x27;, &#x27;2022-08-09T14:02:44.487597312&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-09T13:57:21.000000256&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-09-18T14:03:37.740020992&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acquisition_date_img2</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-08-25T13:56:51.517069056 .....</div><input id='attrs-00343311-2e49-4394-a9a4-77ec7ce610a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00343311-2e49-4394-a9a4-77ec7ce610a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89033d7a-408e-4b4b-b175-8e023371c71f' class='xr-var-data-in' type='checkbox'><label for='data-89033d7a-408e-4b4b-b175-8e023371c71f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-08-25T13:56:51.517069056&#x27;, &#x27;2005-11-14T13:52:03.952635008&#x27;,\n",
       "       &#x27;2005-11-13T13:57:06.239049984&#x27;, &#x27;2006-02-10T13:53:00.896068992&#x27;,\n",
       "       &#x27;2007-01-20T13:52:49.836163072&#x27;, &#x27;2007-03-08T14:03:42.782043904&#x27;,\n",
       "       &#x27;2013-10-02T14:10:38.848780032&#x27;, &#x27;2014-05-15T13:59:54.462811904&#x27;,\n",
       "       &#x27;2015-04-24T14:02:18.731047680&#x27;, &#x27;2015-05-10T14:02:02.825743104&#x27;,\n",
       "       &#x27;2016-06-20T14:08:30.488578048&#x27;, &#x27;2016-07-15T14:02:56.367411968&#x27;,\n",
       "       &#x27;2016-07-31T14:03:00.114257920&#x27;, &#x27;2016-07-31T14:02:36.142736896&#x27;,\n",
       "       &#x27;2016-07-31T14:03:00.114257920&#x27;, &#x27;2016-10-02T14:11:31.340954880&#x27;,\n",
       "       &#x27;2017-03-28T14:00:51.000000000&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-04-15T09:20:15.086074368&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-05-07T14:05:03.044055808&#x27;, &#x27;2017-04-27T09:20:15.534450944&#x27;,\n",
       "       &#x27;2017-05-01T00:02:50.362253824&#x27;, &#x27;2017-05-09T09:20:16.267631360&#x27;,\n",
       "       &#x27;2017-05-13T00:02:51.050416896&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-06-06T00:02:52.452308992&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-06-14T09:20:18.342210048&#x27;, &#x27;2017-06-18T00:02:53.068093952&#x27;,\n",
       "       &#x27;2017-06-26T09:20:18.951375104&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:00:39.000000000&#x27;, &#x27;2017-06-30T00:02:53.773188864&#x27;,\n",
       "       &#x27;2017-07-12T00:02:54.387130880&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-08-25T09:20:22.299848960&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:11:20.198651904&#x27;, &#x27;2017-11-07T14:03:15.934309120&#x27;,\n",
       "       &#x27;2017-11-07T14:02:51.967021056&#x27;, &#x27;2018-01-27T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-05-18T14:01:33.364018944&#x27;,\n",
       "       &#x27;2018-03-28T14:00:49.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-18T14:01:57.335540992&#x27;, &#x27;2018-06-03T14:01:46.008876800&#x27;,\n",
       "       &#x27;2018-05-17T14:00:49.000000000&#x27;, &#x27;2018-06-03T14:01:46.008876800&#x27;,\n",
       "       &#x27;2018-06-03T14:01:22.033117952&#x27;, &#x27;2018-07-21T14:02:11.701212928&#x27;,\n",
       "       &#x27;2018-07-21T14:01:47.725454080&#x27;, &#x27;2018-10-25T14:02:52.606972160&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-10-25T14:02:52.606972160&#x27;,\n",
       "       &#x27;2018-10-25T14:02:52.606972160&#x27;, &#x27;2018-10-25T14:02:28.631212032&#x27;,\n",
       "       &#x27;2018-10-25T14:02:28.631212032&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-11-28T14:00:41.000000000&#x27;,\n",
       "       &#x27;2018-10-29T14:00:51.000000000&#x27;, &#x27;2018-10-29T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2018-11-28T14:00:41.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-01-07T14:00:51.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-01-07T14:00:51.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-02-05T14:08:31.714960128&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-05-17T14:01:01.000000000&#x27;, &#x27;2019-08-20T14:00:58.999999744&#x27;,\n",
       "       &#x27;2019-10-29T14:00:58.999999744&#x27;, &#x27;2020-02-06T13:56:39.000000000&#x27;,\n",
       "       &#x27;2020-02-06T13:56:39.000000000&#x27;, &#x27;2020-05-05T09:20:37.938970880&#x27;,\n",
       "       &#x27;2020-05-29T09:20:39.423532032&#x27;, &#x27;2020-07-01T14:08:32.940545024&#x27;,\n",
       "       &#x27;2020-07-17T14:08:39.009505792&#x27;, &#x27;2020-07-04T09:20:41.305076736&#x27;,\n",
       "       &#x27;2020-07-17T14:08:39.009505792&#x27;, &#x27;2020-07-30T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-09-28T14:01:01.000000000&#x27;, &#x27;2020-09-12T14:03:12.972966912&#x27;,\n",
       "       &#x27;2020-09-12T14:02:49.001443072&#x27;, &#x27;2020-11-02T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2020-09-28T14:02:53.432547072&#x27;,\n",
       "       &#x27;2020-09-28T14:03:17.399834880&#x27;, &#x27;2020-11-02T14:00:58.999999744&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:08:51.765843968&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-04-11T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2021-08-14T14:02:43.738276096&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-24T14:00:21.000000000&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2022-01-21T14:03:10.162823680&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-02-20T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-04-19T14:02:46.036108032&#x27;, &#x27;2022-08-08T14:09:15.200804096&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-16T14:08:58.262974976&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-04-19T14:02:46.036108032&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-04-26T14:08:31.147535104&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-09T13:57:21.000000256&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-09T13:57:21.000000256&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-08-09T14:02:44.487597312&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-11-05T14:03:37.371009024&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-08-08T14:09:15.200804096&#x27;,\n",
       "       &#x27;2022-08-09T13:57:21.000000256&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-17T14:03:06.959698944&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-10-03T14:09:07.308845056&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-08-16T14:08:58.262974976&#x27;, &#x27;2022-11-12T14:09:20.780780032&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-10-03T14:09:07.308845056&#x27;, &#x27;2022-10-03T14:09:07.308845056&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-12T13:57:09.000000256&#x27;,\n",
       "       &#x27;2022-11-05T14:03:37.371009024&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img1_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.005e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-0e0f7942-0090-4d51-958e-bfab56065285' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0e0f7942-0090-4d51-958e-bfab56065285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e57617ae-ec5d-4986-9987-7d927af29ec4' class='xr-var-data-in' type='checkbox'><label for='data-e57617ae-ec5d-4986-9987-7d927af29ec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.12328767, 2005.65205479, 2005.76164384, 2005.76164384,\n",
       "       2006.92328767, 2006.9890411 , 2013.70958904, 2014.34794521,\n",
       "       2015.22465753, 2015.31232877, 2016.42739726, 2016.40821918,\n",
       "       2016.40821918, 2016.40821918, 2016.53972603, 2016.73424658,\n",
       "       2017.12876712, 2017.12876712, 2017.25479452, 2017.23835616,\n",
       "       2017.23835616, 2017.28767123, 2017.29863014, 2017.32054795,\n",
       "       2017.33150685, 2017.12876712, 2017.39726027, 2017.23835616,\n",
       "       2017.41917808, 2017.43013699, 2017.45205479, 2017.34794521,\n",
       "       2017.23835616, 2017.4630137 , 2017.49589041, 2017.34794521,\n",
       "       2017.61643836, 2017.60821918, 2017.60821918, 2017.72054795,\n",
       "       2017.72054795, 2017.71780822, 2017.71780822, 2017.85205479,\n",
       "       2018.0739726 , 2017.85205479, 2018.14246575, 2018.0739726 ,\n",
       "       2018.14246575, 2018.14246575, 2018.23835616, 2018.23835616,\n",
       "       2018.29041096, 2018.29041096, 2018.36164384, 2018.37808219,\n",
       "       2018.37808219, 2018.29041096, 2018.37808219, 2018.29041096,\n",
       "       2018.36164384, 2018.37534247, 2018.37534247, 2018.37808219,\n",
       "       2018.42191781, 2018.42191781, 2018.55342466, 2018.71780822,\n",
       "       2018.8       , 2018.71780822, 2018.8       , 2018.81369863,\n",
       "       2018.8       , 2018.81369863, 2018.82739726, 2018.8       ,\n",
       "       2018.81369863, 2018.82739726, 2018.90958904, 2018.8       ,\n",
       "...\n",
       "       2021.61917808, 2021.61917808, 2021.61917808, 2021.64657534,\n",
       "       2021.61917808, 2021.61917808, 2021.63835616, 2021.64657534,\n",
       "       2021.61917808, 2021.71506849, 2021.64657534, 2021.61917808,\n",
       "       2021.61917808, 2021.6630137 , 2021.71506849, 2021.61917808,\n",
       "       2021.61917808, 2021.61917808, 2021.6630137 , 2021.64657534,\n",
       "       2021.63835616, 2021.71506849, 2021.9260274 , 2022.05753425,\n",
       "       2022.05479452, 2021.61917808, 2021.9260274 , 2021.63835616,\n",
       "       2022.05753425, 2021.61917808, 2021.63835616, 2021.6630137 ,\n",
       "       2022.05753425, 2022.05753425, 2022.05479452, 2022.13972603,\n",
       "       2022.14246575, 2022.1890411 , 2022.1890411 , 2021.9260274 ,\n",
       "       2022.05479452, 2022.05753425, 2022.14246575, 2022.05479452,\n",
       "       2022.31780822, 2022.05753425, 2022.13972603, 2022.14246575,\n",
       "       2022.1890411 , 2022.1890411 , 2022.1890411 , 2022.1890411 ,\n",
       "       2022.05753425, 2022.29863014, 2022.05479452, 2022.31780822,\n",
       "       2022.31780822, 2022.29863014, 2022.29863014, 2022.31780822,\n",
       "       2022.36164384, 2022.36164384, 2022.14246575, 2022.1890411 ,\n",
       "       2022.36164384, 2022.29863014, 2022.5369863 , 2022.36164384,\n",
       "       2022.60547945, 2022.60547945, 2022.60273973, 2022.62465753,\n",
       "       2022.5369863 , 2022.60547945, 2022.60273973, 2022.60547945,\n",
       "       2022.62739726, 2022.71506849])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img2_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.006e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-13a2247c-c332-4b9a-805c-1ca35b01637f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13a2247c-c332-4b9a-805c-1ca35b01637f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05c8f2e5-7b4b-4f7d-8428-ba1c81d71276' class='xr-var-data-in' type='checkbox'><label for='data-05c8f2e5-7b4b-4f7d-8428-ba1c81d71276' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.64931507, 2005.87123288, 2005.86849315, 2006.11232877,\n",
       "       2007.05479452, 2007.18356164, 2013.75342466, 2014.36986301,\n",
       "       2015.31232877, 2015.35616438, 2016.47123288, 2016.53972603,\n",
       "       2016.58356164, 2016.58356164, 2016.58356164, 2016.75616438,\n",
       "       2017.23835616, 2017.34794521, 2017.28767123, 2017.34794521,\n",
       "       2017.34794521, 2017.32054795, 2017.33150685, 2017.35342466,\n",
       "       2017.36438356, 2017.60821918, 2017.43013699, 2017.60821918,\n",
       "       2017.45205479, 2017.4630137 , 2017.48493151, 2017.60821918,\n",
       "       2017.71780822, 2017.49589041, 2017.52876712, 2017.71780822,\n",
       "       2017.64931507, 2017.71780822, 2017.71780822, 2017.85205479,\n",
       "       2017.85205479, 2018.0739726 , 2018.14246575, 2018.29041096,\n",
       "       2018.14246575, 2018.37808219, 2018.23835616, 2018.37534247,\n",
       "       2018.36164384, 2018.37534247, 2018.36164384, 2018.37534247,\n",
       "       2018.37808219, 2018.42191781, 2018.37534247, 2018.42191781,\n",
       "       2018.42191781, 2018.55342466, 2018.55342466, 2018.81643836,\n",
       "       2018.8       , 2018.8       , 2018.81369863, 2018.81643836,\n",
       "       2018.81643836, 2018.81643836, 2018.81643836, 2018.8       ,\n",
       "       2018.81369863, 2018.90958904, 2018.82739726, 2018.82739726,\n",
       "       2018.90958904, 2018.90958904, 2018.90958904, 2019.01917808,\n",
       "       2019.01917808, 2019.01917808, 2019.01917808, 2019.22465753,\n",
       "...\n",
       "       2021.64657534, 2021.6630137 , 2021.71506849, 2021.71506849,\n",
       "       2021.9260274 , 2022.05753425, 2022.05479452, 2022.05753425,\n",
       "       2022.13972603, 2022.05753425, 2022.13972603, 2022.1890411 ,\n",
       "       2022.1890411 , 2022.1890411 , 2022.13972603, 2022.29863014,\n",
       "       2022.29863014, 2022.31780822, 2022.29863014, 2022.31780822,\n",
       "       2022.36164384, 2022.31780822, 2022.1890411 , 2022.13972603,\n",
       "       2022.14246575, 2022.60547945, 2022.29863014, 2022.60273973,\n",
       "       2022.1890411 , 2022.62739726, 2022.62465753, 2022.62739726,\n",
       "       2022.29863014, 2022.31780822, 2022.36164384, 2022.31780822,\n",
       "       2022.31780822, 2022.29863014, 2022.29863014, 2022.62739726,\n",
       "       2022.60273973, 2022.60547945, 2022.5369863 , 2022.62465753,\n",
       "       2022.36164384, 2022.62739726, 2022.60547945, 2022.62465753,\n",
       "       2022.60547945, 2022.60547945, 2022.62739726, 2022.62739726,\n",
       "       2022.84657534, 2022.60547945, 2022.86575342, 2022.60273973,\n",
       "       2022.60547945, 2022.62739726, 2022.62739726, 2022.62465753,\n",
       "       2022.60273973, 2022.62465753, 2022.86575342, 2022.84657534,\n",
       "       2022.75616438, 2022.84657534, 2022.62465753, 2022.86575342,\n",
       "       2022.62739726, 2022.62739726, 2022.75616438, 2022.75616438,\n",
       "       2022.86575342, 2022.84657534, 2022.86575342, 2022.86575342,\n",
       "       2022.84657534, 2022.84657534])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a59d7663-484d-4d76-957b-3cfa7e60d6a8' class='xr-section-summary-in' type='checkbox'  ><label for='section-a59d7663-484d-4d76-957b-3cfa7e60d6a8' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e4fcec62-e6c0-4c3a-bad5-c9e4d39c4211' class='xr-index-data-in' type='checkbox'/><label for='index-e4fcec62-e6c0-4c3a-bad5-c9e4d39c4211' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([454372.5, 454492.5, 454612.5], dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cfbdee0c-2985-4e8c-9b2f-dc07f0e5302c' class='xr-index-data-in' type='checkbox'/><label for='index-cfbdee0c-2985-4e8c-9b2f-dc07f0e5302c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([3883987.5, 3883867.5, 3883747.5], dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_numeric</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7a78fcd0-632c-462a-91f0-4f607ec214db' class='xr-index-data-in' type='checkbox'/><label for='index-7a78fcd0-632c-462a-91f0-4f607ec214db' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 2005.386301369863, 2005.7616438356165, 2005.8164383561643,\n",
       "              2005.9369863013699, 2006.9890410958903, 2007.0876712328768,\n",
       "               2013.731506849315,  2014.358904109589,  2015.268493150685,\n",
       "              2015.3342465753424,\n",
       "              ...\n",
       "              2022.6164383561643, 2022.6164383561643, 2022.6794520547944,\n",
       "               2022.690410958904, 2022.7013698630137, 2022.7260273972602,\n",
       "              2022.7342465753425, 2022.7369863013698, 2022.7369863013698,\n",
       "              2022.7808219178082],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;time_numeric&#x27;, length=198))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3a1df6ef-b8d1-4084-a627-6fecae35d4d9' class='xr-section-summary-in' type='checkbox'  ><label for='section-3a1df6ef-b8d1-4084-a627-6fecae35d4d9' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>GDAL_AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>author :</span></dt><dd>ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)</dd><dt><span>autoRIFT_parameter_file :</span></dt><dd>http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp</dd><dt><span>datacube_software_version :</span></dt><dd>1.0</dd><dt><span>date_created :</span></dt><dd>25-Sep-2023 21:37:37</dd><dt><span>date_updated :</span></dt><dd>25-Sep-2023 21:37:37</dd><dt><span>geo_polygon :</span></dt><dd>[[-70.60078205943937, -55.93497611862378], [-70.20070183190748, -55.93952502816395], [-69.80052280365415, -55.94277482238424], [-69.40027787994103, -55.944724928236276], [-69.0, -55.945375001747436], [-69.0, -55.72074525699316], [-69.0, -55.496107242929824], [-69.0, -55.271460933938485], [-69.0, -55.046806304905594], [-69.39126769136433, -55.04617758528721], [-69.78250486813727, -55.04429153326065], [-70.17368103065434, -55.04114846924806], [-70.5647657090867, -55.036748927074505], [-70.57358098427152, -55.261319623859315], [-70.5825205211217, -55.48588105060886], [-70.59158672366492, -55.710433213476286], [-70.60078205943937, -55.93497611862378]]</dd><dt><span>institution :</span></dt><dd>NASA Jet Propulsion Laboratory (JPL), California Institute of Technology</dd><dt><span>latitude :</span></dt><dd>-55.49</dd><dt><span>longitude :</span></dt><dd>-69.79</dd><dt><span>proj_polygon :</span></dt><dd>[[400000, 3800000], [425000.0, 3800000.0], [450000.0, 3800000.0], [475000.0, 3800000.0], [500000, 3800000], [500000.0, 3825000.0], [500000.0, 3850000.0], [500000.0, 3875000.0], [500000, 3900000], [475000.0, 3900000.0], [450000.0, 3900000.0], [425000.0, 3900000.0], [400000, 3900000], [400000.0, 3875000.0], [400000.0, 3850000.0], [400000.0, 3825000.0], [400000, 3800000]]</dd><dt><span>projection :</span></dt><dd>32719</dd><dt><span>s3 :</span></dt><dd>s3://its-live-data/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.zarr</dd><dt><span>skipped_granules :</span></dt><dd>s3://its-live-data/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.json</dd><dt><span>time_standard_img1 :</span></dt><dd>UTC</dd><dt><span>time_standard_img2 :</span></dt><dd>UTC</dd><dt><span>title :</span></dt><dd>ITS_LIVE datacube of image pair velocities</dd><dt><span>url :</span></dt><dd>https://its-live-data.s3.amazonaws.com/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.zarr</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (time_numeric: 198, x: 3, y: 3)\n",
       "Coordinates:\n",
       "    mid_date               (time_numeric) datetime64[ns] 2005-05-21T13:56:05....\n",
       "  * x                      (x) float64 4.544e+05 4.545e+05 4.546e+05\n",
       "  * y                      (y) float64 3.884e+06 3.884e+06 3.884e+06\n",
       "    img_separation         (time_numeric) float64 193.0 81.0 40.0 ... 81.0 48.0\n",
       "  * time_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    obs_id                 (time_numeric) int64 10 15 16 18 ... 501 502 503 507\n",
       "    mapping                int64 0\n",
       "Data variables:\n",
       "    v                      (time_numeric, y, x) float32 99.0 100.0 ... nan nan\n",
       "    vy                     (time_numeric, y, x) float32 -96.0 -96.0 ... nan nan\n",
       "    vx                     (time_numeric, y, x) float32 -23.0 -28.0 ... nan nan\n",
       "    v_error                (time_numeric, y, x) float32 34.0 34.0 ... nan nan\n",
       "    satellite_img1         (time_numeric) <U2 '5' '7' '5' '5' ... '2A' '8' '8'\n",
       "    satellite_img2         (time_numeric) <U2 '5' '7' '5' '5' ... '2B' '8' '8'\n",
       "    acquisition_date_img1  (time_numeric) datetime64[ns] 2005-02-14T13:55:19....\n",
       "    acquisition_date_img2  (time_numeric) datetime64[ns] 2005-08-25T13:56:51....\n",
       "    img1_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    img2_numeric           (time_numeric) float64 2.006e+03 ... 2.023e+03\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.8\n",
       "    GDAL_AREA_OR_POINT:         Area\n",
       "    author:                     ITS_LIVE, a NASA MEaSUREs project (its-live.j...\n",
       "    autoRIFT_parameter_file:    http://its-live-data.s3.amazonaws.com/autorif...\n",
       "    datacube_software_version:  1.0\n",
       "    date_created:               25-Sep-2023 21:37:37\n",
       "    ...                         ...\n",
       "    s3:                         s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    skipped_granules:           s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    time_standard_img1:         UTC\n",
       "    time_standard_img2:         UTC\n",
       "    title:                      ITS_LIVE datacube of image pair velocities\n",
       "    url:                        https://its-live-data.s3.amazonaws.com/datacu..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier_point.cube_around_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `glacier_centerline` object contains the same RGIID and name information as the first two objects. In addition, it contains OGGM centerline data that are stored as geopandas GeodataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RGIID</th>\n",
       "      <th>SEGMENT_ID</th>\n",
       "      <th>LE_SEGMENT</th>\n",
       "      <th>MAIN</th>\n",
       "      <th>geometry</th>\n",
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       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>RGI60-17.01573</td>\n",
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       "      <td>1</td>\n",
       "      <td>LINESTRING (459379.960 3885671.535, 459381.254...</td>\n",
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      ],
      "text/plain": [
       "               RGIID  SEGMENT_ID  LE_SEGMENT  MAIN  \\\n",
       "1884  RGI60-17.01573           0     14394.0     1   \n",
       "\n",
       "                                               geometry  \n",
       "1884  LINESTRING (459379.960 3885671.535, 459381.254...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier_centerline.main_centerline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "Each of these objects are meant to act as cotainers to intuitively and efficiently store different types of data as you process and continue to work with ITS_LIVE data. \n",
    "\n",
    "The previous steps demonstrated the data access and organization functionality of ITS_LIVE_TOOl. The subsequent sections of this notebook will demonstrate different processing methodologies for working with this dataset. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### If you've selected multiple glaciers, follow these examples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#glacier0, glacier1 = obj_setup.create_multiple_glacier_objs(data_map)[0], obj_setup.create_multiple_glacier_objs(data_map)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PLEASE DON'T UNCOMMENT, WE ARE WORKING ON THIS\n",
    "\n",
    "#glacier_point_ls = obj_setup.create_multiple_glacier_point_objs(data_map)\n",
    "#glacier_pt0, glacier_pt1 = glacier_point_ls[0], glacier_point_ls[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manual/programmatic data access\n",
    "\n",
    "#create `Glacier`, `Glacier_Point`, `Glacier_Centerline` objects\n",
    "\n",
    "Create `Glacier`, `Glacier_Point`, `Glacier_Centerline` objects without using widget. Specify point coordinates (`list`), RGIID (`str`) and utm zone* (`str):\n",
    "\n",
    "*This is a temporary patch, soon won't have to specify utm zone to create object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "point = [76.36013929649597, 35.73912785079385]\n",
    "rgiid = 'RGI60-14.06794'\n",
    "utm = 'EPSG:32643'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "glacier = programmatic_access.create_glacier_obj('name',rgiid, utm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'name'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'RGI60-14.06794'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier.rgi_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "glacier.outline_prj.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "original xy [76.36013929649597, 35.73912785079385] 4326 maps to datacube (622992.2829075075, 3955867.335135076) EPSG:32643\n",
      "subset and load at   2.92 seconds\n"
     ]
    }
   ],
   "source": [
    "glacier_pt = programmatic_access.create_glacier_point_obj(point, 'label', rgiid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "glacier_centerline = programmatic_access.create_glacier_centerline_obj('label', rgiid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RGIID</th>\n",
       "      <th>SEGMENT_ID</th>\n",
       "      <th>LE_SEGMENT</th>\n",
       "      <th>MAIN</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9592</th>\n",
       "      <td>RGI60-14.06794</td>\n",
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       "      <td>20</td>\n",
       "      <td>10174.0</td>\n",
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       "      <td>22</td>\n",
       "      <td>13140.0</td>\n",
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       "      <td>18</td>\n",
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       "      <td>19</td>\n",
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       "      <td>17</td>\n",
       "      <td>14671.0</td>\n",
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       "      <td>LINESTRING (627001.605 3968640.236, 626804.459...</td>\n",
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       "    <tr>\n",
       "      <th>9598</th>\n",
       "      <td>RGI60-14.06794</td>\n",
       "      <td>5</td>\n",
       "      <td>4960.0</td>\n",
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       "    <tr>\n",
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       "      <td>RGI60-14.06794</td>\n",
       "      <td>24</td>\n",
       "      <td>15631.0</td>\n",
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       "      <td>LINESTRING (603426.064 3966501.228, 603428.936...</td>\n",
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       "    <tr>\n",
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       "      <td>RGI60-14.06794</td>\n",
       "      <td>25</td>\n",
       "      <td>21611.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (599991.544 3968852.443, 599994.416...</td>\n",
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       "    <tr>\n",
       "      <th>9601</th>\n",
       "      <td>RGI60-14.06794</td>\n",
       "      <td>26</td>\n",
       "      <td>9574.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (627091.103 3948435.425, 627088.242...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9602</th>\n",
       "      <td>RGI60-14.06794</td>\n",
       "      <td>27</td>\n",
       "      <td>23899.0</td>\n",
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       "      <td>LINESTRING (641288.283 3976848.212, 641491.189...</td>\n",
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       "      <td>28</td>\n",
       "      <td>64947.0</td>\n",
       "      <td>1</td>\n",
       "      <td>LINESTRING (659310.149 3947895.764, 659110.110...</td>\n",
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       "      <td>16</td>\n",
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       "      <td>23</td>\n",
       "      <td>13408.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (638806.752 3940600.252, 638803.897...</td>\n",
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       "    <tr>\n",
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       "      <td>15</td>\n",
       "      <td>12402.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (597955.067 3957420.789, 597957.933...</td>\n",
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       "      <td>3</td>\n",
       "      <td>4931.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (653608.911 3954816.941, 653611.776...</td>\n",
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       "      <td>13</td>\n",
       "      <td>4497.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (649356.606 3958357.387, 649156.573...</td>\n",
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       "    <tr>\n",
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       "      <td>RGI60-14.06794</td>\n",
       "      <td>12</td>\n",
       "      <td>8125.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (642681.007 3963463.546, 642683.876...</td>\n",
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       "      <td>11</td>\n",
       "      <td>7994.0</td>\n",
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       "      <td>10</td>\n",
       "      <td>6525.0</td>\n",
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       "      <td>RGI60-14.06794</td>\n",
       "      <td>9</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>0</td>\n",
       "      <td>LINESTRING (636556.684 3971978.538, 636756.709...</td>\n",
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       "    <tr>\n",
       "      <th>9613</th>\n",
       "      <td>RGI60-14.06794</td>\n",
       "      <td>8</td>\n",
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    "## Data Organization: `Glacier`, `Glacier_Centerline`, `Glacier_Point` object classes"
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    "### `Glacier_Point`\n",
    "\n",
    "This object inherits name and RGIID attributes from the `Glacier` object described aboev (or you can input them manually). It takes the coordinate information specified in the widget and list of variables of interest and returns an object containing ITS_LIVE image pair time series datasets for the specified point anda 3x3 pixel cube surrounding the specified point. Check out the docs for a description of all of the attributes and methods associated with this object. "
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       ".xr-var-data-in:checked ~ .xr-var-data,\n",
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       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
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       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
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       "  margin: 0;\n",
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       ".xr-icon-database,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (time_numeric: 198, x: 3, y: 3)\n",
       "Coordinates:\n",
       "    mid_date               (time_numeric) datetime64[ns] 2005-05-21T13:56:05....\n",
       "  * x                      (x) float64 4.544e+05 4.545e+05 4.546e+05\n",
       "  * y                      (y) float64 3.884e+06 3.884e+06 3.884e+06\n",
       "    img_separation         (time_numeric) float64 193.0 81.0 40.0 ... 81.0 48.0\n",
       "  * time_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    obs_id                 (time_numeric) int64 10 15 16 18 ... 501 502 503 507\n",
       "    mapping                int64 0\n",
       "Data variables:\n",
       "    v                      (time_numeric, y, x) float32 99.0 100.0 ... nan nan\n",
       "    vy                     (time_numeric, y, x) float32 -96.0 -96.0 ... nan nan\n",
       "    vx                     (time_numeric, y, x) float32 -23.0 -28.0 ... nan nan\n",
       "    v_error                (time_numeric, y, x) float32 34.0 34.0 ... nan nan\n",
       "    satellite_img1         (time_numeric) &lt;U2 &#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2A&#x27; &#x27;8&#x27; &#x27;8&#x27;\n",
       "    satellite_img2         (time_numeric) &lt;U2 &#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2B&#x27; &#x27;8&#x27; &#x27;8&#x27;\n",
       "    acquisition_date_img1  (time_numeric) datetime64[ns] 2005-02-14T13:55:19....\n",
       "    acquisition_date_img2  (time_numeric) datetime64[ns] 2005-08-25T13:56:51....\n",
       "    img1_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    img2_numeric           (time_numeric) float64 2.006e+03 ... 2.023e+03\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.8\n",
       "    GDAL_AREA_OR_POINT:         Area\n",
       "    author:                     ITS_LIVE, a NASA MEaSUREs project (its-live.j...\n",
       "    autoRIFT_parameter_file:    http://its-live-data.s3.amazonaws.com/autorif...\n",
       "    datacube_software_version:  1.0\n",
       "    date_created:               25-Sep-2023 21:37:37\n",
       "    ...                         ...\n",
       "    s3:                         s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    skipped_granules:           s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    time_standard_img1:         UTC\n",
       "    time_standard_img2:         UTC\n",
       "    title:                      ITS_LIVE datacube of image pair velocities\n",
       "    url:                        https://its-live-data.s3.amazonaws.com/datacu...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-00c54613-51a0-4596-8c54-8d398f071bf5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-00c54613-51a0-4596-8c54-8d398f071bf5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time_numeric</span>: 198</li><li><span class='xr-has-index'>x</span>: 3</li><li><span class='xr-has-index'>y</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-85eff717-09a1-4e28-bf9d-f4fa4747eb0b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85eff717-09a1-4e28-bf9d-f4fa4747eb0b' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mid_date</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-05-21T13:56:05.476257920 .....</div><input id='attrs-44d0109c-c730-4085-bc44-e41085e32f88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44d0109c-c730-4085-bc44-e41085e32f88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d68922-8af1-4de5-a04b-3162b837c32c' class='xr-var-data-in' type='checkbox'><label for='data-c3d68922-8af1-4de5-a04b-3162b837c32c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>midpoint of image 1 and image 2 acquisition date and time with granule&#x27;s centroid longitude and latitude as microseconds</dd><dt><span>standard_name :</span></dt><dd>image_pair_center_date_with_time_separation</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-05-21T13:56:05.476257920&#x27;, &#x27;2005-10-05T13:51:57.072903936&#x27;,\n",
       "       &#x27;2005-10-25T01:53:53.027030016&#x27;, &#x27;2005-12-08T13:51:50.355538944&#x27;,\n",
       "       &#x27;2006-12-27T13:52:45.628609024&#x27;, &#x27;2007-02-01T02:00:32.390277120&#x27;,\n",
       "       &#x27;2013-09-24T14:10:41.508634880&#x27;, &#x27;2014-05-11T14:01:03.502896896&#x27;,\n",
       "       &#x27;2015-04-08T14:02:25.238568704&#x27;, &#x27;2015-05-02T14:02:10.928819968&#x27;,\n",
       "       &#x27;2016-06-12T14:08:28.667504896&#x27;, &#x27;2016-06-21T14:02:47.279838976&#x27;,\n",
       "       &#x27;2016-06-29T14:02:49.153263104&#x27;, &#x27;2016-06-29T14:02:25.177506048&#x27;,\n",
       "       &#x27;2016-07-23T14:02:58.401550080&#x27;, &#x27;2016-09-28T14:10:15.826789120&#x27;,\n",
       "       &#x27;2017-03-08T14:00:51.170215936&#x27;, &#x27;2017-03-28T14:00:56.170215680&#x27;,\n",
       "       &#x27;2017-04-09T09:20:15.023084032&#x27;, &#x27;2017-04-17T14:00:56.170328064&#x27;,\n",
       "       &#x27;2017-04-17T14:03:37.177678848&#x27;, &#x27;2017-04-21T09:20:15.480677120&#x27;,\n",
       "       &#x27;2017-04-25T00:02:50.282385920&#x27;, &#x27;2017-05-03T09:20:16.071468032&#x27;,\n",
       "       &#x27;2017-05-07T00:02:50.876837120&#x27;, &#x27;2017-05-15T02:00:50.170215936&#x27;,\n",
       "       &#x27;2017-05-31T00:02:52.098582272&#x27;, &#x27;2017-06-04T02:00:50.170328064&#x27;,\n",
       "       &#x27;2017-06-08T09:20:18.071277056&#x27;, &#x27;2017-06-12T00:02:52.930807040&#x27;,\n",
       "       &#x27;2017-06-20T09:20:18.817405952&#x27;, &#x27;2017-06-24T02:00:55.170507008&#x27;,\n",
       "       &#x27;2017-06-24T02:00:45.170328064&#x27;, &#x27;2017-06-24T00:02:53.591259648&#x27;,\n",
       "       &#x27;2017-07-06T00:02:54.250789888&#x27;, &#x27;2017-07-14T02:00:50.170507008&#x27;,\n",
       "       &#x27;2017-08-19T09:20:22.140303872&#x27;, &#x27;2017-08-30T14:00:44.170810112&#x27;,\n",
       "       &#x27;2017-08-30T14:10:03.975674880&#x27;, &#x27;2017-10-14T14:03:12.434516992&#x27;,\n",
       "       &#x27;2017-10-14T14:02:48.462993920&#x27;, &#x27;2017-11-23T14:00:44.170918912&#x27;,\n",
       "       &#x27;2017-12-06T02:00:45.170918912&#x27;, &#x27;2018-01-26T14:02:46.627106048&#x27;,\n",
       "       &#x27;2018-02-09T02:00:50.180126720&#x27;, &#x27;2018-02-11T14:02:12.836626944&#x27;,\n",
       "       &#x27;2018-03-11T02:00:50.180220928&#x27;, &#x27;2018-03-23T14:00:49.180126976&#x27;,\n",
       "       &#x27;2018-04-02T14:00:56.180220928&#x27;, &#x27;2018-04-05T02:00:50.180220928&#x27;,\n",
       "       &#x27;2018-04-20T02:00:55.180327936&#x27;, &#x27;2018-04-22T14:00:49.180328192&#x27;,\n",
       "       &#x27;2018-05-02T14:02:07.337032192&#x27;, &#x27;2018-05-10T14:02:01.673700096&#x27;,\n",
       "       &#x27;2018-05-15T02:00:55.180512000&#x27;, &#x27;2018-05-26T14:01:51.852726784&#x27;,\n",
       "       &#x27;2018-05-26T14:01:27.879087104&#x27;, &#x27;2018-06-03T14:02:14.519867904&#x27;,\n",
       "       &#x27;2018-06-19T14:01:40.725254656&#x27;, &#x27;2018-07-21T14:02:34.972747008&#x27;,\n",
       "       &#x27;2018-07-31T14:00:56.180512000&#x27;, &#x27;2018-08-03T02:00:50.180517120&#x27;,\n",
       "       &#x27;2018-08-05T14:00:49.180517120&#x27;, &#x27;2018-08-06T14:02:25.151774976&#x27;,\n",
       "       &#x27;2018-08-14T14:02:19.488528128&#x27;, &#x27;2018-08-14T14:01:55.512768000&#x27;,\n",
       "       &#x27;2018-09-07T14:02:08.359054080&#x27;, &#x27;2018-10-04T14:00:51.180919040&#x27;,\n",
       "       &#x27;2018-10-22T02:00:50.181018880&#x27;, &#x27;2018-10-24T14:00:46.180919040&#x27;,\n",
       "       &#x27;2018-10-24T14:00:51.181018880&#x27;, &#x27;2018-10-27T02:00:50.181024000&#x27;,\n",
       "       &#x27;2018-11-08T14:00:46.181018880&#x27;, &#x27;2018-11-11T02:00:45.181024000&#x27;,\n",
       "       &#x27;2018-11-13T14:00:46.181029376&#x27;, &#x27;2018-11-28T14:00:51.181018880&#x27;,\n",
       "       &#x27;2018-12-01T02:00:50.181024000&#x27;, &#x27;2018-12-03T14:00:51.181029120&#x27;,\n",
       "       &#x27;2018-12-18T14:00:46.181127936&#x27;, &#x27;2019-01-05T02:00:50.181018880&#x27;,\n",
       "       &#x27;2019-01-07T14:00:49.181024000&#x27;, &#x27;2019-01-12T14:08:35.233935872&#x27;,\n",
       "       &#x27;2019-01-25T02:00:45.181127936&#x27;, &#x27;2019-02-14T02:00:50.190106880&#x27;,\n",
       "       &#x27;2019-04-20T02:00:55.190322944&#x27;, &#x27;2019-06-06T14:00:54.190322688&#x27;,\n",
       "       &#x27;2019-09-24T14:00:59.190819840&#x27;, &#x27;2019-12-18T13:58:49.191028992&#x27;,\n",
       "       &#x27;2020-01-20T01:58:45.200101888&#x27;, &#x27;2020-04-29T09:20:37.827311104&#x27;,\n",
       "       &#x27;2020-05-23T09:20:39.169659904&#x27;, &#x27;2020-05-30T14:08:24.289006080&#x27;,\n",
       "       &#x27;2020-06-07T14:08:27.323486976&#x27;, &#x27;2020-06-28T09:20:41.190839040&#x27;,\n",
       "       &#x27;2020-07-09T14:08:36.175726080&#x27;, &#x27;2020-07-28T02:01:00.200724992&#x27;,\n",
       "       &#x27;2020-08-29T14:01:01.200730112&#x27;, &#x27;2020-09-04T14:03:09.871563008&#x27;,\n",
       "       &#x27;2020-09-04T14:02:45.895802880&#x27;, &#x27;2020-09-13T14:00:59.200724736&#x27;,\n",
       "       &#x27;2020-09-16T02:01:00.200730112&#x27;, &#x27;2020-09-20T14:02:51.417906944&#x27;,\n",
       "       &#x27;2020-09-20T14:03:15.387312896&#x27;, &#x27;2020-10-16T02:01:00.200928256&#x27;,\n",
       "       &#x27;2020-11-05T02:00:55.200730112&#x27;, &#x27;2020-12-05T02:00:55.200928000&#x27;,\n",
       "       &#x27;2020-12-22T14:00:54.201102080&#x27;, &#x27;2020-12-30T02:00:55.200928000&#x27;,\n",
       "       &#x27;2021-01-16T14:00:54.201102080&#x27;, &#x27;2021-01-25T14:08:55.679889920&#x27;,\n",
       "       &#x27;2021-03-07T14:00:49.210210048&#x27;, &#x27;2021-04-06T14:00:49.210401024&#x27;,\n",
       "       &#x27;2021-05-14T02:00:55.210210048&#x27;, &#x27;2021-05-17T14:08:54.364303872&#x27;,\n",
       "       &#x27;2021-06-08T02:00:55.210401024&#x27;, &#x27;2021-06-13T02:00:35.210401024&#x27;,\n",
       "       &#x27;2021-06-25T14:00:34.210401024&#x27;, &#x27;2021-07-12T14:08:44.122251008&#x27;,\n",
       "       &#x27;2021-08-06T14:02:40.784208640&#x27;, &#x27;2021-08-06T14:03:04.759968768&#x27;,\n",
       "       &#x27;2021-08-19T14:00:41.210813696&#x27;, &#x27;2021-08-22T14:02:46.222813952&#x27;,\n",
       "       &#x27;2021-09-01T02:00:40.210813952&#x27;, &#x27;2021-09-06T02:00:20.210823936&#x27;,\n",
       "       &#x27;2021-10-09T14:03:14.522573056&#x27;, &#x27;2021-11-02T14:03:09.149243904&#x27;,\n",
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       "       &#x27;2022-02-10T14:03:03.683998976&#x27;, &#x27;2022-02-13T14:09:06.082394880&#x27;,\n",
       "       &#x27;2022-02-14T14:03:04.067568128&#x27;, &#x27;2022-02-14T14:03:19.531324928&#x27;,\n",
       "       &#x27;2022-02-17T14:08:57.613480704&#x27;, &#x27;2022-02-22T14:02:57.833542144&#x27;,\n",
       "       &#x27;2022-03-06T14:02:58.319587328&#x27;, &#x27;2022-03-10T02:00:50.220121088&#x27;,\n",
       "       &#x27;2022-03-17T14:08:42.872955904&#x27;, &#x27;2022-03-25T02:00:50.220219904&#x27;,\n",
       "       &#x27;2022-03-25T14:08:42.642470912&#x27;, &#x27;2022-03-30T14:02:52.004399104&#x27;,\n",
       "       &#x27;2022-03-30T14:02:28.032887040&#x27;, &#x27;2022-04-11T14:03:26.129437696&#x27;,\n",
       "       &#x27;2022-04-30T14:09:08.664752128&#x27;, &#x27;2022-05-01T13:59:06.220121088&#x27;,\n",
       "       &#x27;2022-05-04T14:08:44.281606912&#x27;, &#x27;2022-05-04T14:09:00.195837952&#x27;,\n",
       "       &#x27;2022-05-04T14:08:27.602799104&#x27;, &#x27;2022-05-05T14:03:20.765026048&#x27;,\n",
       "       &#x27;2022-05-16T13:59:06.220219904&#x27;, &#x27;2022-05-20T14:08:56.200190976&#x27;,\n",
       "       &#x27;2022-05-25T14:02:39.244381952&#x27;, &#x27;2022-05-25T14:03:03.220130304&#x27;,\n",
       "       &#x27;2022-05-29T14:03:14.449838080&#x27;, &#x27;2022-05-29T14:02:50.480432128&#x27;,\n",
       "       &#x27;2022-06-14T14:03:23.987036928&#x27;, &#x27;2022-06-14T14:02:57.472257024&#x27;,\n",
       "       &#x27;2022-06-17T14:09:11.454739968&#x27;, &#x27;2022-06-17T14:08:53.394595072&#x27;,\n",
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       "       &#x27;2022-06-18T14:02:44.732572928&#x27;, &#x27;2022-06-21T14:08:44.925680896&#x27;,\n",
       "       &#x27;2022-06-25T14:08:49.629519104&#x27;, &#x27;2022-06-29T14:08:41.160605184&#x27;,\n",
       "       &#x27;2022-07-03T14:09:07.459094272&#x27;, &#x27;2022-07-08T14:03:17.671849984&#x27;,\n",
       "       &#x27;2022-07-23T14:08:45.683539968&#x27;, &#x27;2022-07-28T14:03:11.923976704&#x27;,\n",
       "       &#x27;2022-07-31T14:08:46.565105664&#x27;, &#x27;2022-08-12T14:08:52.419506944&#x27;,\n",
       "       &#x27;2022-08-13T14:03:19.918085888&#x27;, &#x27;2022-08-13T14:02:55.944456960&#x27;,\n",
       "       &#x27;2022-09-05T14:09:11.475632128&#x27;, &#x27;2022-09-09T14:09:03.006725888&#x27;,\n",
       "       &#x27;2022-09-13T14:08:57.824007936&#x27;, &#x27;2022-09-22T14:03:23.140098048&#x27;,\n",
       "       &#x27;2022-09-25T14:09:18.211599872&#x27;, &#x27;2022-09-26T01:57:15.220808960&#x27;,\n",
       "       &#x27;2022-09-26T14:03:34.369815040&#x27;, &#x27;2022-10-12T14:03:37.776432896&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.544e+05 4.545e+05 4.546e+05</div><input id='attrs-951e5823-db9a-43cd-a09d-97dbc53c5357' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-951e5823-db9a-43cd-a09d-97dbc53c5357' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-294a8f60-94a6-4150-85e8-a724d3284bf7' class='xr-var-data-in' type='checkbox'><label for='data-294a8f60-94a6-4150-85e8-a724d3284bf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([454372.5, 454492.5, 454612.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.884e+06 3.884e+06 3.884e+06</div><input id='attrs-0174e567-ac84-49b1-85ed-4a25ed0cc739' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0174e567-ac84-49b1-85ed-4a25ed0cc739' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d6a7960-423c-4d75-a6a1-b36e523090d5' class='xr-var-data-in' type='checkbox'><label for='data-8d6a7960-423c-4d75-a6a1-b36e523090d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([3883987.5, 3883867.5, 3883747.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img_separation</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>193.0 81.0 40.0 ... 95.0 81.0 48.0</div><input id='attrs-5fb572e0-8879-4105-b75b-50d6e9d5dfd3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fb572e0-8879-4105-b75b-50d6e9d5dfd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5978a0d7-b4e8-45b0-972b-89ea7fe2b794' class='xr-var-data-in' type='checkbox'><label for='data-5978a0d7-b4e8-45b0-972b-89ea7fe2b794' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([193.,  81.,  40., 129.,  49.,  72.,  16.,   8.,  32.,  16.,  17.,\n",
       "        49.,  65.,  65.,  17.,   9.,  40.,  81.,  13.,  41.,  41.,  13.,\n",
       "        13.,  13.,  13., 175.,  13., 135.,  13.,  13.,  13.,  95., 175.,\n",
       "        13.,  13., 135.,  13.,  40.,  41.,  49.,  49., 131., 156., 160.,\n",
       "        26., 192.,  35., 110.,  81.,  85.,  46.,  50.,  32.,  48.,   5.,\n",
       "        16.,  16.,  96.,  65., 193., 160., 156., 160., 161., 145., 145.,\n",
       "        97.,  30.,   5.,  70.,  10.,   6.,  40.,  35.,  30.,  80.,  76.,\n",
       "        70.,  41., 155., 150.,  48., 116.,  75.,  56., 151.,  70., 100.,\n",
       "        35.,  13.,  13.,  65.,  81.,  13.,  17.,   6.,  60.,  17.,  17.,\n",
       "       100.,  95.,  17.,  17.,  35., 195., 135., 100., 185., 150.,  32.,\n",
       "        50.,  10., 186., 193., 136., 145., 170.,  81.,  17.,  17.,  10.,\n",
       "        17.,  35.,  25., 113., 161., 153., 151., 190., 126., 181., 208.,\n",
       "       208., 192., 156., 248., 248., 255., 232., 246., 264., 221.,  96.,\n",
       "        30.,  32., 361., 136., 353.,  48., 369., 361., 353.,  88.,  95.,\n",
       "       112.,  65.,  64.,  40.,  40., 257., 201., 200., 144., 208.,  16.,\n",
       "       209., 170., 177., 153., 153., 161., 161., 289., 113., 297., 105.,\n",
       "       105., 121., 121., 113.,  89.,  97., 265., 241., 145., 201.,  33.,\n",
       "       185.,   9.,   9.,  56.,  49., 121.,  89.,  97.,  95.,  81.,  48.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.005e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-ca30a750-3f33-4977-8e70-1014205572b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca30a750-3f33-4977-8e70-1014205572b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14c7abb0-3841-4975-84e6-6efdd14661e8' class='xr-var-data-in' type='checkbox'><label for='data-14c7abb0-3841-4975-84e6-6efdd14661e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.386301, 2005.761644, 2005.816438, 2005.936986, 2006.989041,\n",
       "       2007.087671, 2013.731507, 2014.358904, 2015.268493, 2015.334247,\n",
       "       2016.449315, 2016.473973, 2016.49589 , 2016.49589 , 2016.561644,\n",
       "       2016.745205, 2017.183562, 2017.238356, 2017.271233, 2017.293151,\n",
       "       2017.293151, 2017.30411 , 2017.315068, 2017.336986, 2017.347945,\n",
       "       2017.369863, 2017.413699, 2017.424658, 2017.435616, 2017.446575,\n",
       "       2017.468493, 2017.479452, 2017.479452, 2017.479452, 2017.512329,\n",
       "       2017.534247, 2017.632877, 2017.663014, 2017.663014, 2017.786301,\n",
       "       2017.786301, 2017.89589 , 2017.931507, 2018.071233, 2018.109589,\n",
       "       2018.115068, 2018.191781, 2018.224658, 2018.252055, 2018.260274,\n",
       "       2018.30137 , 2018.306849, 2018.334247, 2018.356164, 2018.369863,\n",
       "       2018.4     , 2018.4     , 2018.421918, 2018.465753, 2018.553425,\n",
       "       2018.580822, 2018.589041, 2018.594521, 2018.59726 , 2018.619178,\n",
       "       2018.619178, 2018.684932, 2018.758904, 2018.808219, 2018.813699,\n",
       "       2018.813699, 2018.821918, 2018.854795, 2018.863014, 2018.868493,\n",
       "       2018.909589, 2018.917808, 2018.923288, 2018.964384, 2019.013699,\n",
       "       2019.019178, 2019.032877, 2019.068493, 2019.123288, 2019.30137 ,\n",
       "       2019.430137, 2019.731507, 2019.964384, 2020.054795, 2020.328767,\n",
       "       2020.394521, 2020.413699, 2020.435616, 2020.493151, 2020.523288,\n",
       "       2020.575342, 2020.663014, 2020.679452, 2020.679452, 2020.70411 ,\n",
       "       2020.712329, 2020.723288, 2020.723288, 2020.794521, 2020.849315,\n",
       "       2020.931507, 2020.978082, 2021.      , 2021.043836, 2021.068493,\n",
       "       2021.180822, 2021.263014, 2021.367123, 2021.375342, 2021.435616,\n",
       "       2021.449315, 2021.482192, 2021.528767, 2021.59726 , 2021.59726 ,\n",
       "       2021.632877, 2021.641096, 2021.668493, 2021.682192, 2021.772603,\n",
       "       2021.838356, 2021.846575, 2021.852055, 2021.879452, 2021.887671,\n",
       "       2021.893151, 2021.90411 , 2021.90411 , 2021.926027, 2021.928767,\n",
       "       2021.958904, 2021.958904, 2021.969863, 2021.980822, 2021.983562,\n",
       "       2022.      , 2022.016438, 2022.057534, 2022.09863 , 2022.09863 ,\n",
       "       2022.112329, 2022.112329, 2022.120548, 2022.123288, 2022.123288,\n",
       "       2022.131507, 2022.145205, 2022.178082, 2022.189041, 2022.208219,\n",
       "       2022.230137, 2022.230137, 2022.243836, 2022.243836, 2022.276712,\n",
       "       2022.328767, 2022.331507, 2022.339726, 2022.339726, 2022.339726,\n",
       "       2022.342466, 2022.372603, 2022.383562, 2022.39726 , 2022.39726 ,\n",
       "       2022.408219, 2022.408219, 2022.452055, 2022.452055, 2022.460274,\n",
       "       2022.460274, 2022.463014, 2022.463014, 2022.463014, 2022.471233,\n",
       "       2022.482192, 2022.493151, 2022.50411 , 2022.517808, 2022.558904,\n",
       "       2022.572603, 2022.580822, 2022.613699, 2022.616438, 2022.616438,\n",
       "       2022.679452, 2022.690411, 2022.70137 , 2022.726027, 2022.734247,\n",
       "       2022.736986, 2022.736986, 2022.780822])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obs_id</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10 15 16 18 20 ... 501 502 503 507</div><input id='attrs-dee243b8-0242-4c1e-bd5a-e800a8f94ddf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dee243b8-0242-4c1e-bd5a-e800a8f94ddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f1e8117-bd48-4257-ac61-a40030d3e0de' class='xr-var-data-in' type='checkbox'><label for='data-4f1e8117-bd48-4257-ac61-a40030d3e0de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 10,  15,  16,  18,  20,  21,  24,  27,  35,  36,  47,  49,  51,\n",
       "        52,  53,  54,  62,  65,  67,  69,  70,  71,  72,  73,  74,  75,\n",
       "        80,  83,  85,  86,  87,  88,  89,  91,  92,  93,  99, 101, 102,\n",
       "       110, 111, 120, 122, 129, 131, 132, 138, 142, 144, 145, 148, 149,\n",
       "       151, 153, 154, 155, 156, 157, 160, 166, 167, 168, 170, 172, 174,\n",
       "       175, 180, 183, 185, 186, 187, 188, 190, 192, 193, 195, 197, 198,\n",
       "       200, 204, 205, 208, 211, 214, 229, 239, 260, 271, 275, 288, 292,\n",
       "       293, 295, 297, 298, 300, 303, 304, 305, 307, 308, 310, 311, 316,\n",
       "       320, 326, 328, 331, 333, 335, 341, 349, 354, 355, 359, 363, 365,\n",
       "       369, 373, 374, 377, 379, 381, 383, 390, 395, 396, 397, 400, 401,\n",
       "       402, 404, 405, 406, 407, 410, 411, 412, 414, 415, 416, 417, 418,\n",
       "       420, 421, 424, 425, 426, 427, 428, 429, 430, 432, 433, 434, 436,\n",
       "       437, 439, 440, 442, 444, 446, 447, 448, 449, 450, 451, 453, 455,\n",
       "       456, 457, 458, 460, 461, 463, 464, 466, 467, 468, 469, 471, 472,\n",
       "       474, 477, 481, 483, 484, 486, 487, 488, 497, 498, 499, 500, 501,\n",
       "       502, 503, 507])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mapping</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-55447a7a-7ca1-49c1-9685-27656988092f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55447a7a-7ca1-49c1-9685-27656988092f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7445f3df-7014-45e6-9194-36cb20acdd07' class='xr-var-data-in' type='checkbox'><label for='data-7445f3df-7014-45e6-9194-36cb20acdd07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19S&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,10000000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32719&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 19S</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-69.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>10000000.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 19S&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-69],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,10000000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32719&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>454312.5 120.0 0.0 3884047.5 0.0 -120.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35089e74-ccf2-4fa2-b1e1-cb5f12c1a1c7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35089e74-ccf2-4fa2-b1e1-cb5f12c1a1c7' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>99.0 100.0 103.0 ... 125.0 nan nan</div><input id='attrs-51e90a99-97c8-452a-b648-e387346c5bc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51e90a99-97c8-452a-b648-e387346c5bc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12a453c6-03b5-463a-94c8-3f2d38e32b74' class='xr-var-data-in' type='checkbox'><label for='data-12a453c6-03b5-463a-94c8-3f2d38e32b74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity magnitude</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[ 99., 100., 103.],\n",
       "        [106., 103., 107.],\n",
       "        [113., 106., 109.]],\n",
       "\n",
       "       [[102., 103., 110.],\n",
       "        [106., 107., 116.],\n",
       "        [116., 117., 120.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [139., 123., 107.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[222., 234., 225.],\n",
       "        [156., 211., 241.],\n",
       "        [149., 179., 225.]],\n",
       "\n",
       "       [[271., 257., 228.],\n",
       "        [281., 254., 228.],\n",
       "        [266., 263., 231.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [125.,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vy</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-96.0 -96.0 -96.0 ... nan nan</div><input id='attrs-007f232b-5b39-4dc2-a3d3-eeac4d896abb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-007f232b-5b39-4dc2-a3d3-eeac4d896abb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34a8cdf5-e672-4b04-9a1f-6c71b46f17f8' class='xr-var-data-in' type='checkbox'><label for='data-34a8cdf5-e672-4b04-9a1f-6c71b46f17f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity component in y direction</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_y_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[ -96.,  -96.,  -96.],\n",
       "        [-105.,  -99.,  -97.],\n",
       "        [-112., -101.,  -96.]],\n",
       "\n",
       "       [[ -93.,  -90.,  -92.],\n",
       "        [ -98.,  -94.,  -96.],\n",
       "        [-112., -109., -107.]],\n",
       "\n",
       "       [[  nan,   nan,   nan],\n",
       "        [  nan,   nan,   nan],\n",
       "        [-132., -106.,  -62.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-169., -181., -180.],\n",
       "        [-141., -172., -188.],\n",
       "        [-144., -155., -174.]],\n",
       "\n",
       "       [[-197., -197., -180.],\n",
       "        [-201., -188., -180.],\n",
       "        [-197., -197., -184.]],\n",
       "\n",
       "       [[  nan,   nan,   nan],\n",
       "        [  nan,   nan,   nan],\n",
       "        [-124.,   nan,   nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vx</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-23.0 -28.0 -36.0 ... -14.0 nan nan</div><input id='attrs-755b077a-bd24-42c3-bb97-cbb0db87d598' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-755b077a-bd24-42c3-bb97-cbb0db87d598' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a48d3082-29d3-4c6c-9c8b-eb8f56616aa4' class='xr-var-data-in' type='checkbox'><label for='data-a48d3082-29d3-4c6c-9c8b-eb8f56616aa4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity component in x direction</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>land_ice_surface_x_velocity</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[-23., -28., -36.],\n",
       "        [ -8., -26., -47.],\n",
       "        [-17., -35., -52.]],\n",
       "\n",
       "       [[ 42.,  50.,  61.],\n",
       "        [ 38.,  50.,  65.],\n",
       "        [ 30.,  42.,  54.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [-44., -63., -87.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[144., 148., 135.],\n",
       "        [ 67., 122., 151.],\n",
       "        [ 38.,  90., 142.]],\n",
       "\n",
       "       [[187., 166., 140.],\n",
       "        [196., 170., 140.],\n",
       "        [179., 174., 140.]],\n",
       "\n",
       "       [[ nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan],\n",
       "        [-14.,  nan,  nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_error</span></div><div class='xr-var-dims'>(time_numeric, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.0 34.0 34.0 ... 45.0 nan nan</div><input id='attrs-437e0aad-60cf-4b53-89d6-68d563a37fa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-437e0aad-60cf-4b53-89d6-68d563a37fa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c31e026-7e93-48b5-ba80-f05ed427e8ff' class='xr-var-data-in' type='checkbox'><label for='data-7c31e026-7e93-48b5-ba80-f05ed427e8ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>velocity magnitude error</dd><dt><span>grid_mapping :</span></dt><dd>mapping</dd><dt><span>standard_name :</span></dt><dd>velocity_error</dd><dt><span>units :</span></dt><dd>meter/year</dd></dl></div><div class='xr-var-data'><pre>array([[[34., 34., 34.],\n",
       "        [33., 34., 34.],\n",
       "        [34., 34., 34.]],\n",
       "\n",
       "       [[31., 31., 31.],\n",
       "        [32., 31., 31.],\n",
       "        [32., 32., 31.]],\n",
       "\n",
       "       [[nan, nan, nan],\n",
       "        [nan, nan, nan],\n",
       "        [72., 80., 97.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[46., 46., 46.],\n",
       "        [47., 46., 46.],\n",
       "        [47., 47., 46.]],\n",
       "\n",
       "       [[30., 30., 30.],\n",
       "        [30., 30., 30.],\n",
       "        [30., 30., 31.]],\n",
       "\n",
       "       [[nan, nan, nan],\n",
       "        [nan, nan, nan],\n",
       "        [45., nan, nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satellite_img1</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2A&#x27; &#x27;8&#x27; &#x27;8&#x27;</div><input id='attrs-1f80c220-ab6f-48d6-84f5-de2b98f48990' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f80c220-ab6f-48d6-84f5-de2b98f48990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-503c52f0-b111-421c-bd4b-c9e623a02de3' class='xr-var-data-in' type='checkbox'><label for='data-503c52f0-b111-421c-bd4b-c9e623a02de3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>id of the satellite that acquired image 1</dd><dt><span>standard_name :</span></dt><dd>image1_satellite</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;1A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1A&#x27;, &#x27;1A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;1B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>satellite_img2</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;5&#x27; &#x27;7&#x27; &#x27;5&#x27; &#x27;5&#x27; ... &#x27;2B&#x27; &#x27;8&#x27; &#x27;8&#x27;</div><input id='attrs-cd84e837-a7ec-4eb7-a1e3-dc62d82e1068' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd84e837-a7ec-4eb7-a1e3-dc62d82e1068' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64238a3f-460a-47f8-a610-099effa259f4' class='xr-var-data-in' type='checkbox'><label for='data-64238a3f-460a-47f8-a610-099effa259f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>id of the satellite that acquired image 2</dd><dt><span>standard_name :</span></dt><dd>image2_satellite</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;5&#x27;, &#x27;7&#x27;, &#x27;5&#x27;, &#x27;8&#x27;, &#x27;7&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;7&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;1B&#x27;, &#x27;2A&#x27;, &#x27;7&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;1A&#x27;, &#x27;2B&#x27;, &#x27;1B&#x27;, &#x27;1A&#x27;, &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;1A&#x27;, &#x27;1A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;1B&#x27;, &#x27;2B&#x27;, &#x27;7&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;1B&#x27;, &#x27;1B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;1B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2A&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;2A&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;2B&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;2B&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;,\n",
       "       &#x27;9&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2A&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;8&#x27;, &#x27;9&#x27;, &#x27;9&#x27;, &#x27;8&#x27;,\n",
       "       &#x27;8&#x27;, &#x27;8&#x27;, &#x27;2B&#x27;, &#x27;8&#x27;, &#x27;8&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acquisition_date_img1</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-02-14T13:55:19.335019008 .....</div><input id='attrs-a979d2ea-eba6-4627-af12-27f003cd4c68' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a979d2ea-eba6-4627-af12-27f003cd4c68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c15d178-6a77-484b-bd2b-1067604ed31f' class='xr-var-data-in' type='checkbox'><label for='data-9c15d178-6a77-484b-bd2b-1067604ed31f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-02-14T13:55:19.335019008&#x27;, &#x27;2005-08-26T13:51:50.091519872&#x27;,\n",
       "       &#x27;2005-10-05T13:50:39.712999936&#x27;, &#x27;2005-10-05T13:50:39.712999936&#x27;,\n",
       "       &#x27;2006-12-03T13:52:41.298648064&#x27;, &#x27;2006-12-27T13:57:21.876056064&#x27;,\n",
       "       &#x27;2013-09-16T14:10:43.906659072&#x27;, &#x27;2014-05-07T14:02:12.261967872&#x27;,\n",
       "       &#x27;2015-03-23T14:02:31.445444096&#x27;, &#x27;2015-04-24T14:02:18.731047680&#x27;,\n",
       "       &#x27;2016-06-04T14:08:26.525222912&#x27;, &#x27;2016-05-28T14:02:37.871211008&#x27;,\n",
       "       &#x27;2016-05-28T14:02:37.871211008&#x27;, &#x27;2016-05-28T14:02:13.891217920&#x27;,\n",
       "       &#x27;2016-07-15T14:02:56.367411968&#x27;, &#x27;2016-09-24T14:08:59.990775040&#x27;,\n",
       "       &#x27;2017-02-16T14:00:51.000000000&#x27;, &#x27;2017-02-16T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-04-03T09:20:14.619289088&#x27;, &#x27;2017-03-28T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-03-28T14:02:10.970647040&#x27;, &#x27;2017-04-15T09:20:15.086074368&#x27;,\n",
       "       &#x27;2017-04-19T00:02:49.861679360&#x27;, &#x27;2017-04-27T09:20:15.534450944&#x27;,\n",
       "       &#x27;2017-05-01T00:02:50.362253824&#x27;, &#x27;2017-02-16T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-05-25T00:02:51.403804928&#x27;, &#x27;2017-03-28T14:00:51.000000000&#x27;,\n",
       "       &#x27;2017-06-02T09:20:17.459141120&#x27;, &#x27;2017-06-06T00:02:52.452308992&#x27;,\n",
       "       &#x27;2017-06-14T09:20:18.342210048&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-03-28T14:00:51.000000000&#x27;, &#x27;2017-06-18T00:02:53.068093952&#x27;,\n",
       "       &#x27;2017-06-30T00:02:53.773188864&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-08-13T09:20:21.639132928&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-08-10T14:08:47.411077888&#x27;, &#x27;2017-09-20T14:03:08.592884992&#x27;,\n",
       "       &#x27;2017-09-20T14:02:44.617125888&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:00:39.000000000&#x27;, &#x27;2017-11-07T14:03:15.934309120&#x27;,\n",
       "       &#x27;2018-01-27T14:00:49.000000000&#x27;, &#x27;2017-11-07T14:02:51.967021056&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-01-27T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-02-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-03-28T14:00:49.000000000&#x27;, &#x27;2018-03-28T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-04-16T14:02:16.977689856&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-18T14:01:57.335540992&#x27;,\n",
       "       &#x27;2018-05-18T14:01:33.364018944&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-18T14:01:33.364018944&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-17T14:00:49.000000000&#x27;, &#x27;2018-05-18T14:01:57.335540992&#x27;,\n",
       "       &#x27;2018-06-03T14:01:46.008876800&#x27;, &#x27;2018-06-03T14:01:22.033117952&#x27;,\n",
       "       &#x27;2018-07-21T14:01:47.725454080&#x27;, &#x27;2018-09-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-09-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-24T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-24T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-10-29T14:00:51.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-10-29T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-12-19T14:08:38.390475008&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-08-20T14:00:58.999999744&#x27;, &#x27;2019-10-29T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-01-02T14:00:51.000000000&#x27;, &#x27;2020-04-23T09:20:37.314803968&#x27;,\n",
       "       &#x27;2020-05-17T09:20:38.514753024&#x27;, &#x27;2020-04-28T14:08:15.236611072&#x27;,\n",
       "       &#x27;2020-04-28T14:08:15.236611072&#x27;, &#x27;2020-06-22T09:20:40.675356928&#x27;,\n",
       "       &#x27;2020-07-01T14:08:32.940545024&#x27;, &#x27;2020-07-25T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-08-27T14:03:06.368505088&#x27;,\n",
       "       &#x27;2020-08-27T14:02:42.388508928&#x27;, &#x27;2020-07-25T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-09-12T14:02:49.001443072&#x27;,\n",
       "       &#x27;2020-09-12T14:03:12.972966912&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-07-30T14:01:01.000000000&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2020-09-28T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2021-01-09T14:08:59.173716992&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:08:51.765843968&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-06-02T14:08:31.280954880&#x27;,\n",
       "       &#x27;2021-07-29T14:02:37.408684032&#x27;, &#x27;2021-07-29T14:03:01.384444160&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-14T14:02:43.738276096&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:03:07.714035968&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-08-24T14:00:21.000000000&#x27;, &#x27;2021-08-14T14:02:43.738276096&#x27;,\n",
       "       &#x27;2021-08-14T14:03:07.714035968&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-14T14:02:43.738276096&#x27;, &#x27;2021-08-14T14:01:01.000000000&#x27;,\n",
       "       &#x27;2021-08-30T14:02:48.285724928&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-21T14:08:56.542343936&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-02-20T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-03-10T14:02:33.560546048&#x27;, &#x27;2021-12-04T14:03:20.909481984&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-01-20T14:09:01.688460032&#x27;,\n",
       "       &#x27;2022-04-26T14:08:31.147535104&#x27;, &#x27;2022-01-21T14:03:10.162823680&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-02-21T14:08:53.696965120&#x27;,\n",
       "       &#x27;2022-03-10T14:02:33.560546048&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-01-21T14:03:10.162823680&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-04-26T14:08:31.147535104&#x27;,\n",
       "       &#x27;2022-04-26T14:00:49.000000000&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:08:31.147535104&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-05-12T14:08:23.617210880&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-03-10T14:02:57.532069888&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-05-12T14:08:23.617210880&#x27;,\n",
       "       &#x27;2022-08-09T14:03:08.467568896&#x27;, &#x27;2022-08-09T14:02:44.487597312&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-09T13:57:21.000000256&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-09-18T14:03:37.740020992&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acquisition_date_img2</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2005-08-25T13:56:51.517069056 .....</div><input id='attrs-cd0448b6-0a7b-4ccc-8acc-b26104576fce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd0448b6-0a7b-4ccc-8acc-b26104576fce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d34e7788-8f42-481a-84cb-050276c2c243' class='xr-var-data-in' type='checkbox'><label for='data-d34e7788-8f42-481a-84cb-050276c2c243' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2005-08-25T13:56:51.517069056&#x27;, &#x27;2005-11-14T13:52:03.952635008&#x27;,\n",
       "       &#x27;2005-11-13T13:57:06.239049984&#x27;, &#x27;2006-02-10T13:53:00.896068992&#x27;,\n",
       "       &#x27;2007-01-20T13:52:49.836163072&#x27;, &#x27;2007-03-08T14:03:42.782043904&#x27;,\n",
       "       &#x27;2013-10-02T14:10:38.848780032&#x27;, &#x27;2014-05-15T13:59:54.462811904&#x27;,\n",
       "       &#x27;2015-04-24T14:02:18.731047680&#x27;, &#x27;2015-05-10T14:02:02.825743104&#x27;,\n",
       "       &#x27;2016-06-20T14:08:30.488578048&#x27;, &#x27;2016-07-15T14:02:56.367411968&#x27;,\n",
       "       &#x27;2016-07-31T14:03:00.114257920&#x27;, &#x27;2016-07-31T14:02:36.142736896&#x27;,\n",
       "       &#x27;2016-07-31T14:03:00.114257920&#x27;, &#x27;2016-10-02T14:11:31.340954880&#x27;,\n",
       "       &#x27;2017-03-28T14:00:51.000000000&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-04-15T09:20:15.086074368&#x27;, &#x27;2017-05-07T14:01:01.000000000&#x27;,\n",
       "       &#x27;2017-05-07T14:05:03.044055808&#x27;, &#x27;2017-04-27T09:20:15.534450944&#x27;,\n",
       "       &#x27;2017-05-01T00:02:50.362253824&#x27;, &#x27;2017-05-09T09:20:16.267631360&#x27;,\n",
       "       &#x27;2017-05-13T00:02:51.050416896&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-06-06T00:02:52.452308992&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-06-14T09:20:18.342210048&#x27;, &#x27;2017-06-18T00:02:53.068093952&#x27;,\n",
       "       &#x27;2017-06-26T09:20:18.951375104&#x27;, &#x27;2017-08-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:00:39.000000000&#x27;, &#x27;2017-06-30T00:02:53.773188864&#x27;,\n",
       "       &#x27;2017-07-12T00:02:54.387130880&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-08-25T09:20:22.299848960&#x27;, &#x27;2017-09-19T14:00:39.000000000&#x27;,\n",
       "       &#x27;2017-09-19T14:11:20.198651904&#x27;, &#x27;2017-11-07T14:03:15.934309120&#x27;,\n",
       "       &#x27;2017-11-07T14:02:51.967021056&#x27;, &#x27;2018-01-27T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-04-16T14:02:16.977689856&#x27;,\n",
       "       &#x27;2018-02-21T14:00:51.000000000&#x27;, &#x27;2018-05-18T14:01:33.364018944&#x27;,\n",
       "       &#x27;2018-03-28T14:00:49.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-12T14:01:01.000000000&#x27;, &#x27;2018-05-17T14:00:49.000000000&#x27;,\n",
       "       &#x27;2018-05-18T14:01:57.335540992&#x27;, &#x27;2018-06-03T14:01:46.008876800&#x27;,\n",
       "       &#x27;2018-05-17T14:00:49.000000000&#x27;, &#x27;2018-06-03T14:01:46.008876800&#x27;,\n",
       "       &#x27;2018-06-03T14:01:22.033117952&#x27;, &#x27;2018-07-21T14:02:11.701212928&#x27;,\n",
       "       &#x27;2018-07-21T14:01:47.725454080&#x27;, &#x27;2018-10-25T14:02:52.606972160&#x27;,\n",
       "       &#x27;2018-10-19T14:00:51.000000000&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-10-25T14:02:52.606972160&#x27;,\n",
       "       &#x27;2018-10-25T14:02:52.606972160&#x27;, &#x27;2018-10-25T14:02:28.631212032&#x27;,\n",
       "       &#x27;2018-10-25T14:02:28.631212032&#x27;, &#x27;2018-10-19T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-10-24T14:00:49.000000000&#x27;, &#x27;2018-11-28T14:00:41.000000000&#x27;,\n",
       "       &#x27;2018-10-29T14:00:51.000000000&#x27;, &#x27;2018-10-29T14:00:51.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2018-11-28T14:00:41.000000000&#x27;,\n",
       "       &#x27;2018-11-28T14:00:41.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-01-07T14:00:51.000000000&#x27;, &#x27;2019-01-07T14:00:51.000000000&#x27;,\n",
       "       &#x27;2019-01-07T14:00:51.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-02-05T14:08:31.714960128&#x27;,\n",
       "       &#x27;2019-03-23T14:00:49.000000000&#x27;, &#x27;2019-03-23T14:00:49.000000000&#x27;,\n",
       "       &#x27;2019-05-17T14:01:01.000000000&#x27;, &#x27;2019-08-20T14:00:58.999999744&#x27;,\n",
       "       &#x27;2019-10-29T14:00:58.999999744&#x27;, &#x27;2020-02-06T13:56:39.000000000&#x27;,\n",
       "       &#x27;2020-02-06T13:56:39.000000000&#x27;, &#x27;2020-05-05T09:20:37.938970880&#x27;,\n",
       "       &#x27;2020-05-29T09:20:39.423532032&#x27;, &#x27;2020-07-01T14:08:32.940545024&#x27;,\n",
       "       &#x27;2020-07-17T14:08:39.009505792&#x27;, &#x27;2020-07-04T09:20:41.305076736&#x27;,\n",
       "       &#x27;2020-07-17T14:08:39.009505792&#x27;, &#x27;2020-07-30T14:01:01.000000000&#x27;,\n",
       "       &#x27;2020-09-28T14:01:01.000000000&#x27;, &#x27;2020-09-12T14:03:12.972966912&#x27;,\n",
       "       &#x27;2020-09-12T14:02:49.001443072&#x27;, &#x27;2020-11-02T14:00:58.999999744&#x27;,\n",
       "       &#x27;2020-11-02T14:00:58.999999744&#x27;, &#x27;2020-09-28T14:02:53.432547072&#x27;,\n",
       "       &#x27;2020-09-28T14:03:17.399834880&#x27;, &#x27;2020-11-02T14:00:58.999999744&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-02-10T14:00:49.000000000&#x27;, &#x27;2021-04-01T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-02-10T14:08:51.765843968&#x27;,\n",
       "       &#x27;2021-04-01T14:00:49.000000000&#x27;, &#x27;2021-04-11T14:00:49.000000000&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2021-08-14T14:01:01.000000000&#x27;, &#x27;2021-08-24T14:00:21.000000000&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-08-21T14:08:56.542343936&#x27;,\n",
       "       &#x27;2021-08-14T14:02:43.738276096&#x27;, &#x27;2021-08-14T14:03:07.714035968&#x27;,\n",
       "       &#x27;2021-08-24T14:00:21.000000000&#x27;, &#x27;2021-08-30T14:02:48.285724928&#x27;,\n",
       "       &#x27;2021-09-18T14:00:19.000000000&#x27;, &#x27;2021-09-18T14:00:19.000000000&#x27;,\n",
       "       &#x27;2021-12-04T14:03:20.909481984&#x27;, &#x27;2022-01-21T14:03:10.162823680&#x27;,\n",
       "       &#x27;2022-01-20T14:09:01.688460032&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-01-21T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-03-10T14:02:33.560546048&#x27;,\n",
       "       &#x27;2022-02-20T14:00:51.000000000&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-02-20T14:00:51.000000000&#x27;,\n",
       "       &#x27;2022-02-21T14:08:53.696965120&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-04-19T14:02:46.036108032&#x27;, &#x27;2022-08-08T14:09:15.200804096&#x27;,\n",
       "       &#x27;2022-03-10T14:02:57.532069888&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-16T14:08:58.262974976&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-04-19T14:02:46.036108032&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-04-26T14:00:49.000000000&#x27;,\n",
       "       &#x27;2022-04-26T14:08:31.147535104&#x27;, &#x27;2022-04-19T14:02:46.036108032&#x27;,\n",
       "       &#x27;2022-04-19T14:02:22.064608000&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-09T13:57:21.000000256&#x27;,\n",
       "       &#x27;2022-07-15T14:08:34.425807104&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-05-12T14:08:23.617210880&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-09T13:57:21.000000256&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-08-09T14:02:44.487597312&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-11-05T14:03:37.371009024&#x27;, &#x27;2022-08-09T14:03:08.467568896&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-08-08T14:09:15.200804096&#x27;,\n",
       "       &#x27;2022-08-09T13:57:21.000000256&#x27;, &#x27;2022-08-17T14:03:30.926985728&#x27;,\n",
       "       &#x27;2022-08-17T14:03:06.959698944&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-08-08T14:09:15.200804096&#x27;, &#x27;2022-08-16T14:08:58.262974976&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-10-03T14:09:07.308845056&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-08-16T14:08:58.262974976&#x27;, &#x27;2022-11-12T14:09:20.780780032&#x27;,\n",
       "       &#x27;2022-08-17T14:03:30.926985728&#x27;, &#x27;2022-08-17T14:03:06.959698944&#x27;,\n",
       "       &#x27;2022-10-03T14:09:07.308845056&#x27;, &#x27;2022-10-03T14:09:07.308845056&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;,\n",
       "       &#x27;2022-11-12T14:09:20.780780032&#x27;, &#x27;2022-11-12T13:57:09.000000256&#x27;,\n",
       "       &#x27;2022-11-05T14:03:37.371009024&#x27;, &#x27;2022-11-05T14:03:37.371009024&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img1_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.005e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-82616c40-fd3e-48ff-a1ef-4b847a221097' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-82616c40-fd3e-48ff-a1ef-4b847a221097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56779f1f-6a4e-4ba1-bc1f-11df0419218e' class='xr-var-data-in' type='checkbox'><label for='data-56779f1f-6a4e-4ba1-bc1f-11df0419218e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.12328767, 2005.65205479, 2005.76164384, 2005.76164384,\n",
       "       2006.92328767, 2006.9890411 , 2013.70958904, 2014.34794521,\n",
       "       2015.22465753, 2015.31232877, 2016.42739726, 2016.40821918,\n",
       "       2016.40821918, 2016.40821918, 2016.53972603, 2016.73424658,\n",
       "       2017.12876712, 2017.12876712, 2017.25479452, 2017.23835616,\n",
       "       2017.23835616, 2017.28767123, 2017.29863014, 2017.32054795,\n",
       "       2017.33150685, 2017.12876712, 2017.39726027, 2017.23835616,\n",
       "       2017.41917808, 2017.43013699, 2017.45205479, 2017.34794521,\n",
       "       2017.23835616, 2017.4630137 , 2017.49589041, 2017.34794521,\n",
       "       2017.61643836, 2017.60821918, 2017.60821918, 2017.72054795,\n",
       "       2017.72054795, 2017.71780822, 2017.71780822, 2017.85205479,\n",
       "       2018.0739726 , 2017.85205479, 2018.14246575, 2018.0739726 ,\n",
       "       2018.14246575, 2018.14246575, 2018.23835616, 2018.23835616,\n",
       "       2018.29041096, 2018.29041096, 2018.36164384, 2018.37808219,\n",
       "       2018.37808219, 2018.29041096, 2018.37808219, 2018.29041096,\n",
       "       2018.36164384, 2018.37534247, 2018.37534247, 2018.37808219,\n",
       "       2018.42191781, 2018.42191781, 2018.55342466, 2018.71780822,\n",
       "       2018.8       , 2018.71780822, 2018.8       , 2018.81369863,\n",
       "       2018.8       , 2018.81369863, 2018.82739726, 2018.8       ,\n",
       "       2018.81369863, 2018.82739726, 2018.90958904, 2018.8       ,\n",
       "...\n",
       "       2021.61917808, 2021.61917808, 2021.61917808, 2021.64657534,\n",
       "       2021.61917808, 2021.61917808, 2021.63835616, 2021.64657534,\n",
       "       2021.61917808, 2021.71506849, 2021.64657534, 2021.61917808,\n",
       "       2021.61917808, 2021.6630137 , 2021.71506849, 2021.61917808,\n",
       "       2021.61917808, 2021.61917808, 2021.6630137 , 2021.64657534,\n",
       "       2021.63835616, 2021.71506849, 2021.9260274 , 2022.05753425,\n",
       "       2022.05479452, 2021.61917808, 2021.9260274 , 2021.63835616,\n",
       "       2022.05753425, 2021.61917808, 2021.63835616, 2021.6630137 ,\n",
       "       2022.05753425, 2022.05753425, 2022.05479452, 2022.13972603,\n",
       "       2022.14246575, 2022.1890411 , 2022.1890411 , 2021.9260274 ,\n",
       "       2022.05479452, 2022.05753425, 2022.14246575, 2022.05479452,\n",
       "       2022.31780822, 2022.05753425, 2022.13972603, 2022.14246575,\n",
       "       2022.1890411 , 2022.1890411 , 2022.1890411 , 2022.1890411 ,\n",
       "       2022.05753425, 2022.29863014, 2022.05479452, 2022.31780822,\n",
       "       2022.31780822, 2022.29863014, 2022.29863014, 2022.31780822,\n",
       "       2022.36164384, 2022.36164384, 2022.14246575, 2022.1890411 ,\n",
       "       2022.36164384, 2022.29863014, 2022.5369863 , 2022.36164384,\n",
       "       2022.60547945, 2022.60547945, 2022.60273973, 2022.62465753,\n",
       "       2022.5369863 , 2022.60547945, 2022.60273973, 2022.60547945,\n",
       "       2022.62739726, 2022.71506849])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>img2_numeric</span></div><div class='xr-var-dims'>(time_numeric)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.006e+03 2.006e+03 ... 2.023e+03</div><input id='attrs-4e3d9644-0170-406e-be05-a53989cf9f26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e3d9644-0170-406e-be05-a53989cf9f26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5cdcf66-9646-463a-8f95-a784a3461a74' class='xr-var-data-in' type='checkbox'><label for='data-f5cdcf66-9646-463a-8f95-a784a3461a74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2005.64931507, 2005.87123288, 2005.86849315, 2006.11232877,\n",
       "       2007.05479452, 2007.18356164, 2013.75342466, 2014.36986301,\n",
       "       2015.31232877, 2015.35616438, 2016.47123288, 2016.53972603,\n",
       "       2016.58356164, 2016.58356164, 2016.58356164, 2016.75616438,\n",
       "       2017.23835616, 2017.34794521, 2017.28767123, 2017.34794521,\n",
       "       2017.34794521, 2017.32054795, 2017.33150685, 2017.35342466,\n",
       "       2017.36438356, 2017.60821918, 2017.43013699, 2017.60821918,\n",
       "       2017.45205479, 2017.4630137 , 2017.48493151, 2017.60821918,\n",
       "       2017.71780822, 2017.49589041, 2017.52876712, 2017.71780822,\n",
       "       2017.64931507, 2017.71780822, 2017.71780822, 2017.85205479,\n",
       "       2017.85205479, 2018.0739726 , 2018.14246575, 2018.29041096,\n",
       "       2018.14246575, 2018.37808219, 2018.23835616, 2018.37534247,\n",
       "       2018.36164384, 2018.37534247, 2018.36164384, 2018.37534247,\n",
       "       2018.37808219, 2018.42191781, 2018.37534247, 2018.42191781,\n",
       "       2018.42191781, 2018.55342466, 2018.55342466, 2018.81643836,\n",
       "       2018.8       , 2018.8       , 2018.81369863, 2018.81643836,\n",
       "       2018.81643836, 2018.81643836, 2018.81643836, 2018.8       ,\n",
       "       2018.81369863, 2018.90958904, 2018.82739726, 2018.82739726,\n",
       "       2018.90958904, 2018.90958904, 2018.90958904, 2019.01917808,\n",
       "       2019.01917808, 2019.01917808, 2019.01917808, 2019.22465753,\n",
       "...\n",
       "       2021.64657534, 2021.6630137 , 2021.71506849, 2021.71506849,\n",
       "       2021.9260274 , 2022.05753425, 2022.05479452, 2022.05753425,\n",
       "       2022.13972603, 2022.05753425, 2022.13972603, 2022.1890411 ,\n",
       "       2022.1890411 , 2022.1890411 , 2022.13972603, 2022.29863014,\n",
       "       2022.29863014, 2022.31780822, 2022.29863014, 2022.31780822,\n",
       "       2022.36164384, 2022.31780822, 2022.1890411 , 2022.13972603,\n",
       "       2022.14246575, 2022.60547945, 2022.29863014, 2022.60273973,\n",
       "       2022.1890411 , 2022.62739726, 2022.62465753, 2022.62739726,\n",
       "       2022.29863014, 2022.31780822, 2022.36164384, 2022.31780822,\n",
       "       2022.31780822, 2022.29863014, 2022.29863014, 2022.62739726,\n",
       "       2022.60273973, 2022.60547945, 2022.5369863 , 2022.62465753,\n",
       "       2022.36164384, 2022.62739726, 2022.60547945, 2022.62465753,\n",
       "       2022.60547945, 2022.60547945, 2022.62739726, 2022.62739726,\n",
       "       2022.84657534, 2022.60547945, 2022.86575342, 2022.60273973,\n",
       "       2022.60547945, 2022.62739726, 2022.62739726, 2022.62465753,\n",
       "       2022.60273973, 2022.62465753, 2022.86575342, 2022.84657534,\n",
       "       2022.75616438, 2022.84657534, 2022.62465753, 2022.86575342,\n",
       "       2022.62739726, 2022.62739726, 2022.75616438, 2022.75616438,\n",
       "       2022.86575342, 2022.84657534, 2022.86575342, 2022.86575342,\n",
       "       2022.84657534, 2022.84657534])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc4cdd76-7acf-419c-9bcc-03af5fbec92e' class='xr-section-summary-in' type='checkbox'  ><label for='section-cc4cdd76-7acf-419c-9bcc-03af5fbec92e' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-606ad609-7845-4590-b930-1158b447247a' class='xr-index-data-in' type='checkbox'/><label for='index-606ad609-7845-4590-b930-1158b447247a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([454372.5, 454492.5, 454612.5], dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4629c168-6e98-46d1-a6d4-22f00a54c1a8' class='xr-index-data-in' type='checkbox'/><label for='index-4629c168-6e98-46d1-a6d4-22f00a54c1a8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([3883987.5, 3883867.5, 3883747.5], dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_numeric</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b6714382-489b-4612-b048-f73f44aef74d' class='xr-index-data-in' type='checkbox'/><label for='index-b6714382-489b-4612-b048-f73f44aef74d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 2005.386301369863, 2005.7616438356165, 2005.8164383561643,\n",
       "              2005.9369863013699, 2006.9890410958903, 2007.0876712328768,\n",
       "               2013.731506849315,  2014.358904109589,  2015.268493150685,\n",
       "              2015.3342465753424,\n",
       "              ...\n",
       "              2022.6164383561643, 2022.6164383561643, 2022.6794520547944,\n",
       "               2022.690410958904, 2022.7013698630137, 2022.7260273972602,\n",
       "              2022.7342465753425, 2022.7369863013698, 2022.7369863013698,\n",
       "              2022.7808219178082],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;time_numeric&#x27;, length=198))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d12d83ff-1fdd-414a-b0a4-bf5bc45504e9' class='xr-section-summary-in' type='checkbox'  ><label for='section-d12d83ff-1fdd-414a-b0a4-bf5bc45504e9' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>GDAL_AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>author :</span></dt><dd>ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)</dd><dt><span>autoRIFT_parameter_file :</span></dt><dd>http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp</dd><dt><span>datacube_software_version :</span></dt><dd>1.0</dd><dt><span>date_created :</span></dt><dd>25-Sep-2023 21:37:37</dd><dt><span>date_updated :</span></dt><dd>25-Sep-2023 21:37:37</dd><dt><span>geo_polygon :</span></dt><dd>[[-70.60078205943937, -55.93497611862378], [-70.20070183190748, -55.93952502816395], [-69.80052280365415, -55.94277482238424], [-69.40027787994103, -55.944724928236276], [-69.0, -55.945375001747436], [-69.0, -55.72074525699316], [-69.0, -55.496107242929824], [-69.0, -55.271460933938485], [-69.0, -55.046806304905594], [-69.39126769136433, -55.04617758528721], [-69.78250486813727, -55.04429153326065], [-70.17368103065434, -55.04114846924806], [-70.5647657090867, -55.036748927074505], [-70.57358098427152, -55.261319623859315], [-70.5825205211217, -55.48588105060886], [-70.59158672366492, -55.710433213476286], [-70.60078205943937, -55.93497611862378]]</dd><dt><span>institution :</span></dt><dd>NASA Jet Propulsion Laboratory (JPL), California Institute of Technology</dd><dt><span>latitude :</span></dt><dd>-55.49</dd><dt><span>longitude :</span></dt><dd>-69.79</dd><dt><span>proj_polygon :</span></dt><dd>[[400000, 3800000], [425000.0, 3800000.0], [450000.0, 3800000.0], [475000.0, 3800000.0], [500000, 3800000], [500000.0, 3825000.0], [500000.0, 3850000.0], [500000.0, 3875000.0], [500000, 3900000], [475000.0, 3900000.0], [450000.0, 3900000.0], [425000.0, 3900000.0], [400000, 3900000], [400000.0, 3875000.0], [400000.0, 3850000.0], [400000.0, 3825000.0], [400000, 3800000]]</dd><dt><span>projection :</span></dt><dd>32719</dd><dt><span>s3 :</span></dt><dd>s3://its-live-data/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.zarr</dd><dt><span>skipped_granules :</span></dt><dd>s3://its-live-data/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.json</dd><dt><span>time_standard_img1 :</span></dt><dd>UTC</dd><dt><span>time_standard_img2 :</span></dt><dd>UTC</dd><dt><span>title :</span></dt><dd>ITS_LIVE datacube of image pair velocities</dd><dt><span>url :</span></dt><dd>https://its-live-data.s3.amazonaws.com/datacubes/v2/S50W060/ITS_LIVE_vel_EPSG32719_G0120_X450000_Y3850000.zarr</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (time_numeric: 198, x: 3, y: 3)\n",
       "Coordinates:\n",
       "    mid_date               (time_numeric) datetime64[ns] 2005-05-21T13:56:05....\n",
       "  * x                      (x) float64 4.544e+05 4.545e+05 4.546e+05\n",
       "  * y                      (y) float64 3.884e+06 3.884e+06 3.884e+06\n",
       "    img_separation         (time_numeric) float64 193.0 81.0 40.0 ... 81.0 48.0\n",
       "  * time_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    obs_id                 (time_numeric) int64 10 15 16 18 ... 501 502 503 507\n",
       "    mapping                int64 0\n",
       "Data variables:\n",
       "    v                      (time_numeric, y, x) float32 99.0 100.0 ... nan nan\n",
       "    vy                     (time_numeric, y, x) float32 -96.0 -96.0 ... nan nan\n",
       "    vx                     (time_numeric, y, x) float32 -23.0 -28.0 ... nan nan\n",
       "    v_error                (time_numeric, y, x) float32 34.0 34.0 ... nan nan\n",
       "    satellite_img1         (time_numeric) <U2 '5' '7' '5' '5' ... '2A' '8' '8'\n",
       "    satellite_img2         (time_numeric) <U2 '5' '7' '5' '5' ... '2B' '8' '8'\n",
       "    acquisition_date_img1  (time_numeric) datetime64[ns] 2005-02-14T13:55:19....\n",
       "    acquisition_date_img2  (time_numeric) datetime64[ns] 2005-08-25T13:56:51....\n",
       "    img1_numeric           (time_numeric) float64 2.005e+03 ... 2.023e+03\n",
       "    img2_numeric           (time_numeric) float64 2.006e+03 ... 2.023e+03\n",
       "Attributes: (12/19)\n",
       "    Conventions:                CF-1.8\n",
       "    GDAL_AREA_OR_POINT:         Area\n",
       "    author:                     ITS_LIVE, a NASA MEaSUREs project (its-live.j...\n",
       "    autoRIFT_parameter_file:    http://its-live-data.s3.amazonaws.com/autorif...\n",
       "    datacube_software_version:  1.0\n",
       "    date_created:               25-Sep-2023 21:37:37\n",
       "    ...                         ...\n",
       "    s3:                         s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    skipped_granules:           s3://its-live-data/datacubes/v2/S50W060/ITS_L...\n",
       "    time_standard_img1:         UTC\n",
       "    time_standard_img2:         UTC\n",
       "    title:                      ITS_LIVE datacube of image pair velocities\n",
       "    url:                        https://its-live-data.s3.amazonaws.com/datacu..."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier_point.cube_around_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `Glacier_Centerline`\n",
    "\n",
    "Similarly to the `Glacier_Point` object, a `Glacier_Centerline` object inherits some basic information from a `Glacier` object, but this can also be specified manually if you don't want to create a `Glacier` method beforehand. A `Glacier_Centerline` object has attributes called `centerlines` and `main_centerline`. These are both `Geopandas.GeoDataframe` objects containing OGGM flowline data associated with this glacier. They also contain ITS_LIVE image pair velocity time series clipped to the centerline (**still being implemented**)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "glacier_centerline = programmatic_access.create_glacier_centerline_obj('Jorge Montt', 'RGI60-17.06074')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ITS_LIVE_TOOL.obj_setup.Glacier_Centerline at 0x7fe6850a5000>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glacier_centerline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each of these objects are meant to act as cotainers to intuitively and efficiently store different types of data as you process and continue to work with ITS_LIVE data. \n",
    "\n",
    "The previous steps demonstrated the data access and organization functionality of ITS_LIVE_TOOl. The subsequent sections of this notebook will demonstrate different processing methodologies for working with this dataset. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Section 2: Data Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Filtering + Inspection \n",
    "\n",
    "Examples of situations where outlier detection may be necessary. We present 3 methods for outlier detection. \n",
    "\n",
    "```{note}\n",
    "IN PROGRESS\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Section 3: Datacube Inversion\n",
    "\n",
    "#### *To dive into the theory of the inversion, check-out the '06_inversion.ipynb' notebook*\n",
    "<br>\n",
    "\n",
    "#### **Problem:**\n",
    "\n",
    "*Find a smooth regularly spaced timeseries of velocities given a set of average measurements of possibly overlapping and variable length time intervals*\n",
    "\n",
    "<br>\n",
    "\n",
    "\n",
    "#### **Inversion applied to ITS_LIVE:**\n",
    "\n",
    "ITS_LIVE is a great dataset that achieves high-density measurements globally, on a long timescale, using the same sensors and method.\n",
    "However it suffers from one main problem: **mid_dates** (timestamps), its attribution of a timestamp for a measurement. For example, if ITS_LIVE uses two images a month apart, it really measures the average velocity for this whole month. Instead, ITS_LIVE attributes to the velocity a timestamp in the middle of the month. \n",
    "\n",
    "The inversion computes all the timestamps and the satellite-pairs length, and calculates a solution depending on all the available values.\n",
    "\n",
    "<br>\n",
    "\n",
    "\n",
    "\n",
    "### **Input your parameters below**\n",
    "\n",
    "*Useful information:*\n",
    "\n",
    "- GPU generally runs the inversion faster, but might be slower when using the spatial regularization.\n",
    "- High lambda encouraged for non-surging glacier\n",
    "- spatial_shape 'cross' is hard-coded because 'ring' would take a lot of RAM and the code would be much more complicated.\n",
    "- spatial_regularization: False if you want a faster computation, slightly less accurate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You have 1 glaciers selected\n"
     ]
    }
   ],
   "source": [
    "# In case you didn't run the cell that grabs the urls\n",
    "#coords, gpdf, urls = obj_setup.return_clicked_info(data_map)\n",
    "\n",
    "# In case you haven't created the centerline\n",
    "#glacier_centerline = obj_setup.create_glacier_centerline_from_click(data_map, 0)\n",
    "\n",
    "###### INPUT YOUR PARAMETERS #######\n",
    "\n",
    "name_cube = 'Weird' # Name of the dataset\n",
    "\n",
    "mission = None # 'None' if you want all the data, 'S1' for Sentinel-1 only, 'L' for Landsat only, etc.. .\n",
    "\n",
    "lamb = 5 # Smoothing coefficient: the higher the value, the more the inversion favors a smooth output. BAD for surging glaciers, GOOD for non-surging glaciers\n",
    "\n",
    "derivative = 2 # Derivative degree for the inversion. Doesn't change much unless you have a specific reason to choose 1 or 2 (1st or 2nd derivative)\n",
    "\n",
    "day_interval = 60 # Amount of days in between each inversion value. The higher, the faster the inversion. But you also lose in temporal resolution. 12 here because Sentinel-1 repeat-time is 12.\n",
    "\n",
    "sdate = '2019-01-01' # Start date, format 'YYYY-MM-DD' OR None if you want to grab the entire timeseries available\n",
    "\n",
    "edate = None # End date, format 'YYYY-MM-DD' OR None if you want to grab the entire timeseries available\n",
    "\n",
    "GPU = True # True if you want to use GPU, False if you want to use CPU\n",
    "\n",
    "spatial_regularization = False # True if you want to use spatial regularization, False if you only want to use temporal regularization\n",
    "\n",
    "if spatial_regularization:\n",
    "    derivative = 2 # It is better to do a central difference scheme than forward difference in this case\n",
    "    spatial_shape = 'cross' # 'ring' has not been implemented yet, and tests show a huge in increase in computation time\n",
    "    nb_pts_tot = 5\n",
    "else:\n",
    "    nb_pts_tot = 1\n",
    "    spatial_shape = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create dictionnaries to hold variables for each datacube**\n",
    "\n",
    "Each datacube has multiple variables associated with it. We gather all these variables in dictionnaries such as 1 datacube = 1 dictionnary.\n",
    "We then gather all the dictionnaries into one for easier organization.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "X_tot, Y_tot, X_valid, Y_valid, data_dict, urls = invert.create_data_dict(urls, mission, lamb, derivative, day_interval, data_map)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Datacubes Extent and Point Validity\n",
    "\n",
    "Designed to grab the extents of the datacubes, and determines which pixel belongs to the GOI (Glacier Of Interest). This way we do not lose time inverting for empty pixels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:04<00:00,  4.00s/it]\n"
     ]
    }
   ],
   "source": [
    "for url in tqdm(range(len(urls))):\n",
    "    X_tot, Y_tot, X_valid, Y_valid = invert.get_extents(urls[url], X_tot, Y_tot, X_valid, Y_valid, mission, lamb, derivative, day_interval, data_map, data_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Map the valid indices in a new array\n",
    "\n",
    "This new array spans all the datacubes. We take the footprint of the GOI, insert-it in an array, and map in this array which pixel is on-glacier.\n",
    "It allows to run the inversion for glacier-points only, accross all the datacubes, and store the inversion output in an array that represents the glacier's shape."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "space_interval, min_date, max_date, template, P, neighbor_idx, x_indices_centerline, y_indices_centerline, X_arr, X_MIN, X_MAX, Y_arr, Y_MIN, Y_MAX, x_matches, y_matches = invert.cubes_intersection(X_tot, Y_tot, X_valid, Y_valid, data_dict, urls, spatial_regularization, mission, lamb, derivative, day_interval, sdate, edate, nb_pts_tot, glacier_centerline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## Design Matrices\n",
    "\n",
    "This function creates 1 design matrix per cube. Knowing that each cube has different time stamps (different image pairs), but the possible dates for the image pairs are the same for every pixel of the datacube, we can pre-compute 1 design-matrix for each cube. We will simply mask-out the rows that represent time steps for which our point being inverted does not have any value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "reg_mat_space, reg_mat_time, dates_nonum, dates, data_dict = invert.design_matrices(urls, min_date, max_date, mission, lamb, derivative, day_interval, space_interval, sdate, edate, data_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "#### Design Matrix components\n",
    "\n",
    "Build the last bricks of the design matrix depending on how many points we use in the regularization & initialize host arrays for the inversion outputs\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "vxInv, vyInv, len_pt_inverted, SRT, SRS, space_reg_mat, time_reg_mat =  invert.extend_Matrices(reg_mat_time, nb_pts_tot, reg_mat_space, spatial_regularization, dates, template)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Function to loop through every valid on-glacier pixel and save the dataset\n",
    "\n",
    "The following function calls the point's timeseries from ITS_LIVE, assembles the design matrix, and calls the inversion function. Once it is done, it stores the inversion output in the host matrices (vx & vy). It saves a copy of the matrices as a netcdf object every 10k iterations, and creates a text file printing how many iterations have been computed, every 100 iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 4802/4802 [09:06<00:00,  8.79it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing to Datacubes\n",
      "[########################################] | 100% Completed | 205.00 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Determine the GPU in your system if you have one\n",
    "if GPU:     \n",
    "    import torch\n",
    "    device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "else:\n",
    "    device = None\n",
    "\n",
    "# Run the inversions for vx and vy and populate vxInv, vyInv\n",
    "for i in tqdm(range(len(y_matches))):\n",
    "\n",
    "    vxInv, vyInv = invert.looper(i, name_cube, vxInv, vyInv, GPU, spatial_regularization, nb_pts_tot, time_reg_mat, space_reg_mat, len_pt_inverted, data_dict, urls, P, neighbor_idx, x_matches, y_matches, X_arr, X_MIN, X_MAX, Y_arr, Y_MIN, Y_MAX, device, dates_nonum, x_indices_centerline, y_indices_centerline, SRT, SRS)\n",
    "    \n",
    "invert.save_dataset(name_cube, vxInv, vyInv, dates_nonum, X_arr, Y_arr, X_MIN, X_MAX, Y_MIN, Y_MAX, x_indices_centerline, y_indices_centerline, data_dict, urls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}