area2_estimate.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "\n",
    "ee.Initialize()\n",
    "from IPython.display import display, Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scale = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "roi = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/area2\")\n",
    "s2TNI = ee.Image(\"users/nkeikon/myanmar_sr/s2image\").clip(roi)\n",
    "classified = ee.Image(\"users/nkeikon/myanmar_sr/area2_classified\")\n",
    "PA = ee.FeatureCollection(\"WCMC/WDPA/current/polygons\")\n",
    "palm = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/palm_area2\")\n",
    "rubber = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/rubber_area2\")\n",
    "other = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/other_area2\")\n",
    "bare = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/bare_area2\")\n",
    "water = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/water_area2\")\n",
    "shrub = ee.FeatureCollection(\"users/nkeikon/myanmar_sr/shrub_area2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Image(url=classified.randomVisualizer().getThumbUrl({\"size\": \"400\"}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the area by class\n",
    "names = [\"1 oil palm\", \"2 rubber\", \"3 other\", \"4 shrub\", \"5 bare\", \"6 water\"]\n",
    "count = classified.eq([1, 2, 3, 4, 5, 6]).rename(names)\n",
    "total = count.multiply(ee.Image.pixelArea())\n",
    "areaM2 = total.reduceRegion(ee.Reducer.sum(), roi, scale, None, None, False, 1e13, 3)\n",
    "areaPixel = count.reduceRegion(ee.Reducer.sum(), roi, scale, None, None, False, 1e13, 3)\n",
    "\n",
    "# Create feature collections\n",
    "featureM2 = ee.Feature(None)\n",
    "featureM2 = featureM2.set(\"areaM2\", areaM2)\n",
    "area_M2 = ee.FeatureCollection(featureM2)\n",
    "\n",
    "featurePixel = ee.Feature(None)\n",
    "featurePixel = featurePixel.set(\"areaPixel\", areaPixel)\n",
    "area_Pixel = ee.FeatureCollection(featurePixel)\n",
    "\n",
    "# Export as csv\n",
    "export1 = ee.batch.Export.table.toDrive(\n",
    "    collection=area_M2,\n",
    "    description=\"export_area2_m2\",\n",
    "    fileNamePrefix=\"Kawthaung_area2_m2\",\n",
    ")\n",
    "export1.start()\n",
    "export2 = ee.batch.Export.table.toDrive(\n",
    "    collection=area_Pixel,\n",
    "    description=\"export_area2_pixel\",\n",
    "    fileNamePrefix=\"Kawthaung_area2_pixel\",\n",
    ")\n",
    "export2.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# query current tasks\n",
    "tasks = ee.batch.Task.list()\n",
    "print(tasks[0])\n",
    "print(tasks[1])\n",
    "print(tasks[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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