RIOXARRAY-RES-TEST.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "14beb38c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rioxarray\n",
    "import xarray as xr\n",
    "import numpy as np\n",
    "from richardutils import tif_dict\n",
    "import os\n",
    "from rasterio.enums import Resampling\n",
    "from rioxarray.merge import merge_arrays\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from osgeo import gdal, osr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "613af680",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Helper functions\n",
    "https://github.com/RichardScottOZ/richardutils\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9255e342",
   "metadata": {},
   "source": [
    "## Data\n",
    "National-Scale Geophysical, Geologic, and Mineral Resource Data and Grids for the United States, Canada, and Australia: Data in Support of the Tri-National Critical Minerals Mapping Initiative  \n",
    "https://www.sciencebase.gov/catalog/item/6193e9f3d34eb622f68f13a5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7e26c41c",
   "metadata": {},
   "outputs": [],
   "source": [
    "usgs = tif_dict(r'D:\\Geophysics')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1dacacf5",
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     "text": [
      "GeophysicsGravity_HGM_AusCan.tif (0.031, -0.031) (-168.1285, -43.6635, 159.1075, 83.12650000000001) (4090, 10556)\n",
      "GeophysicsGravity_Australia.tif (0.00553, -0.00553) (112.919835, -43.65658499999999, 159.100865, -9.221274999999999) (6227, 8351)\n",
      "GeophysicsGravity_HGM_Australia.tif (0.00553, -0.00553) (112.919835, -43.65658499999999, 159.100865, -9.221274999999999) (6227, 8351)\n",
      "GeophysicsGravity_UpCont30km_Australia.tif (0.00553, -0.00553) (112.919835, -43.65658499999999, 159.100865, -9.221274999999999) (6227, 8351)\n",
      "GeophysicsGravity_UpCont30km_HGM_Australia.tif (0.00553, -0.00553) (112.919835, -43.65658499999999, 159.100865, -9.221274999999999) (6227, 8351)\n",
      "GeophysicsSatelliteGravity_ShapeIndex_Australia.tif (0.2, -0.2) (113.0, -43.60000000000001, 153.6, -10.600000000000001) (165, 203)\n",
      "GeophysicsSatelliteGravity_ShapeIndex_USCanada.tif (0.2, -0.2) (-178.2, 21.800000000000004, -52.59999999999999, 83.2) (307, 628)\n",
      "GeophysicsGravity_HGM_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "GeophysicsGravity_UpCont30km_HGM_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "GeophysicsGravity_UpCont30km_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "GeophysicsGravity_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "GeophysicsMagRTP_Australia.tif (0.0024999, -0.0024999) (112.91847325, -43.64094395000001, 153.63184465, -10.049787649999999) (13437, 16286)\n",
      "GeophysicsMagRTP_DeepSources_Australia.tif (0.00806, -0.00806) (112.91657, -43.64087, 153.62762999999998, -10.054850000000002) (4167, 5051)\n",
      "GeophysicsMagRTP_HGMDeepSources_Australia.tif (0.00828, -0.00828) (112.9185, -43.63974, 153.63126, -10.04778000000001) (4057, 4917)\n",
      "GeophysicsMagRTP_HGM_Australia.tif (0.00806, -0.00806) (112.91657, -43.64087, 153.62762999999998, -10.054850000000002) (4167, 5051)\n",
      "GeophysicsMagRTP_VD_Australia.tif (0.0024999, -0.0024999) (112.91847325, -43.64094395000001, 153.63184465, -10.049787649999999) (13437, 16286)\n",
      "GeophysicsMagRTP_DeepSources_USCanada.tif (0.0181, -0.0181) (-191.00025, 17.348849999999988, -8.98664999999997, 90.05655) (4017, 10056)\n",
      "GeophysicsMagRTP_HGMDeepSources_USCanada.tif (0.0189, -0.0189) (-189.38745, 15.69645, -11.04705, 88.85835) (3871, 9436)\n",
      "GeophysicsMagRTP_HGM_USCanada.tif (0.0151, -0.0151) (-187.50425, 23.17095000000001, -52.631049999999995, 83.10285) (3969, 8932)\n",
      "GeophysicsMagRTP_USCanada.tif (0.0151, -0.0151) (-187.50425, 23.17095000000001, -52.631049999999995, 83.10285) (3969, 8932)\n",
      "GeophysicsMagRTP_VD_USCanada.tif (0.0151, -0.0151) (-187.50425, 23.17095000000001, -52.631049999999995, 83.10285) (3969, 8932)\n",
      "GeophysicsMag_USCanada.tif (0.0151, -0.0151) (-187.50425, 23.17095000000001, -52.631049999999995, 83.10285) (3969, 8932)\n",
      "GeophysicsLAB_Australia.tif (0.1, -0.1) (112.95, -43.64999999999999, 153.65, -10.049999999999997) (336, 407)\n",
      "GeophysicsLAB_USCanada.tif (0.1, -0.1) (-178.85, 21.750000000000004, -52.64999999999998, 83.15) (614, 1262)\n",
      "GeophysicsMoho_Australia.tif (0.1, -0.1) (112.95, -43.64999999999999, 153.65, -9.349999999999994) (343, 407)\n",
      "GeophysicsMoho_USCanada.tif (0.25, -0.25) (-173.125, 25.125, -52.625, 83.125) (232, 482)\n",
      "GeophysicsGravity_AustraliaUSCanada.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_AustraliaUSCanada_clip.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_AustraliaUSCanada_clip9999.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_HGM_AustraliaUSCanada.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_HGM_AustraliaUSCanada_clip.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_HGM_AustraliaUSCanada_clip9999.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_AustraliaUSCanada.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_AustraliaUSCanada_clip.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_AustraliaUSCanada_clip9999.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_HGM_AustraliaUSCanada.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_HGM_AustraliaUSCanada_clip.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsGravity_UpCont30km_HGM_AustraliaUSCanada_clip9999.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeophysicsLAB_AustraliaUSCanada.tif (0.1, -0.1) (-178.85, -43.64999999999999, 153.65000000000006, 83.15) (1268, 3325)\n",
      "GeophysicsLAB_AustraliaUSCanada_clip.tif (0.1, -0.1) (-178.85, -43.64999999999999, 153.65000000000006, 83.15) (1268, 3325)\n",
      "GeophysicsLAB_AustraliaUSCanada_clip9999.tif (0.1, -0.1) (-178.85, -43.64999999999999, 153.65000000000006, 83.15) (1268, 3325)\n",
      "GeophysicsMagRTP_AustraliaUSCanada.tif (0.0049998, -0.0049998) (-187.50425, -43.642080000000014, 153.63710380000003, 83.10285) (25350, 68231)\n",
      "GeophysicsMagRTP_AustraliaUSCanada_clip.tif (0.0049998, -0.0049998) (-180.00455000000002, -43.642080000000014, 153.6371038, 83.10285) (25350, 66731)\n",
      "GeophysicsMagRTP_AustraliaUSCanada_clip9999.tif (0.0049998, -0.0049998) (-180.00455000000002, -43.642080000000014, 153.6371038, 83.10285) (25350, 66731)\n",
      "GeophysicsMagRTP_DeepSources_AustraliaUSCanada.tif (0.00806, -0.00806) (-191.00025, -43.642729999999986, 153.62923, 90.05655) (16588, 42758)\n",
      "GeophysicsMagRTP_DeepSources_AustraliaUSCanada_clip.tif (0.00806, -0.00806) (-180.00641, -43.642729999999986, 153.62922999999998, 90.00013) (16581, 41394)\n",
      "GeophysicsMagRTP_HGMDeepSources_AustraliaUSCanada.tif (0.00828, -0.00828) (-189.38745, -43.63820999999998, 153.62811, 88.85835) (16002, 41427)\n",
      "GeophysicsMagRTP_HGMDeepSources_AustraliaUSCanada_clip.tif (0.00828, -0.00828) (-180.00621, -43.63820999999998, 153.62811, 88.85835) (16002, 40294)\n",
      "GeophysicsMagRTP_HGM_AustraliaUSCanada.tif (0.00806, -0.00806) (-187.50425, -43.640649999999994, 153.62718999999998, 83.10285) (15725, 42324)\n",
      "GeophysicsMagRTP_HGM_AustraliaUSCanada_clip.tif (0.00806, -0.00806) (-180.00039, -43.640649999999994, 153.62718999999996, 83.10285) (15725, 41393)\n",
      "GeophysicsMagRTP_VD_AustraliaUSCanada.tif (0.0049998, -0.0049998) (-187.50425, -43.642080000000014, 153.63710380000003, 83.10285) (25350, 68231)\n",
      "GeophysicsMagRTP_VD_AustraliaUSCanada_clip.tif (0.0049998, -0.0049998) (-180.00455000000002, -43.642080000000014, 153.6371038, 83.10285) (25350, 66731)\n",
      "GeophysicsMoho_AustraliaUSCanada.tif (0.10000000000000002, -0.1) (-173.125, -43.675, 153.67500000000007, 83.125) (1268, 3268)\n",
      "GeophysicsMoho_AustraliaUSCanada_clip.tif (0.10000000000000002, -0.1) (-173.125, -43.675, 153.67500000000007, 83.125) (1268, 3268)\n",
      "GeophysicsSatelliteGravity_ShapeIndex_AustraliaUSCanada.tif (0.2, -0.2) (-178.2, -43.6, 153.60000000000002, 83.2) (634, 1659)\n",
      "GeophysicsSatelliteGravity_ShapeIndex_AustraliaUSCanada_clip.tif (0.2, -0.2) (-178.2, -43.6, 153.60000000000002, 83.2) (634, 1659)\n",
      "mask_AustraliaUSCanada_grav.tif (0.00553, -0.00553) (-168.1285, -43.654279999999986, 159.09819000000002, 83.12650000000001) (22926, 59173)\n",
      "GeologyCMMI.tif (-0.00806, 0.00806) (-180.01203999999998, -43.6449, 153.63165999999998, 90.00601999999998) (16582, 41395)\n",
      "GeologyCMMI_0.tif (-0.00806, 0.00806) (-180.01203999999998, -43.6449, 153.63165999999998, 90.00601999999998) (16582, 41395)\n",
      "GeologyFaults.tif (-0.00806, 0.00806) (-180.01203999999998, -43.6449, 153.63165999999998, 90.00601999999998) (16582, 41395)\n",
      "GeologyPassiveMarginsModern_World.tif (-0.1, 0.1) (-173.20000000000002, -43.70000000000001, 153.70000000000002, 83.2) (1269, 3269)\n",
      "GeophysicsMagRTP_DeepSources_AustraliaUSCanada_clip9999.tif (0.00806, -0.00806) (-180.00641, -43.642729999999986, 153.62922999999998, 90.00013) (16581, 41394)\n",
      "GeophysicsMagRTP_HGMDeepSources_AustraliaUSCanada_clip9999.tif (0.00828, -0.00828) (-180.00621, -43.63820999999998, 153.62811, 88.85835) (16002, 40294)\n",
      "GeophysicsMagRTP_HGM_AustraliaUSCanada_clip9999.tif (0.00806, -0.00806) (-180.00039, -43.640649999999994, 153.62718999999996, 83.10285) (15725, 41393)\n",
      "GeophysicsMagRTP_VD_AustraliaUSCanada_clip9999.tif (0.0049998, -0.0049998) (-180.00455000000002, -43.642080000000014, 153.6371038, 83.10285) (25350, 66731)\n",
      "GeophysicsMoho_AustraliaUSCanada_clip9999.tif (0.10000000000000002, -0.1) (-173.125, -43.675, 153.67500000000007, 83.125) (1268, 3268)\n",
      "GeophysicsSatelliteGravity_ShapeIndex_AustraliaUSCanada_clip9999.tif (0.2, -0.2) (-178.2, -43.6, 153.60000000000002, 83.2) (634, 1659)\n",
      "GeophysicsGravity_Up30km_HGM_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "GeophysicsGravity_Up30km_USCanada.tif (0.031, -0.031) (-168.1285, 23.57550000000001, -50.3905, 83.12650000000001) (1921, 3798)\n",
      "USCanada_Moho.tif (0.25, -0.25) (-173.125, 25.125, -52.625, 83.125) (232, 482)\n"
     ]
    }
   ],
   "source": [
    "for tif in usgs:\n",
    "    print(tif, usgs[tif].rio.resolution(),usgs[tif].rio.bounds(),usgs[tif].squeeze().shape)"
   ]
  },
  {
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     "text": [
      "5.605786618444846\n",
      "1489.7106451612906 1110.8164516129034\n"
     ]
    }
   ],
   "source": [
    "upscale_factor = usgs['GeophysicsGravity_HGM_USCanada.tif'].rio.resolution()[0]/usgs['GeophysicsGravity_HGM_Australia.tif'].rio.resolution()[0]\n",
    "print(upscale_factor)\n",
    "new_width = usgs['GeophysicsGravity_HGM_Australia.tif'].rio.width / upscale_factor\n",
    "new_height = usgs['GeophysicsGravity_HGM_Australia.tif'].rio.height / upscale_factor\n",
    "print(new_width, new_height)\n",
    "\n",
    "\n",
    "aus_downsampled = usgs['GeophysicsGravity_HGM_Australia.tif'].rio.reproject(\n",
    "    usgs['GeophysicsGravity_HGM_Australia.tif'].rio.crs,\n",
    "    shape=(int(new_height)+1, int(new_width)+1),\n",
    "    resampling=Resampling.bilinear,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
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   "id": "5d19f11c",
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   "outputs": [
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       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  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",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\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",
       "}\n",
       "\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",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\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",
       "}\n",
       "\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",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\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",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 1, y: 1111, x: 1490)&gt;\n",
       "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * x            (x) float64 112.9 113.0 113.0 113.0 ... 159.0 159.0 159.1 159.1\n",
       "  * y            (y) float64 -9.237 -9.268 -9.299 -9.33 ... -43.58 -43.61 -43.64\n",
       "  * band         (band) int32 1\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    AREA_OR_POINT:           Area\n",
       "    STATISTICS_COVARIANCES:  5.856919861077052e-05\n",
       "    STATISTICS_MAXIMUM:      0.1543258279562\n",
       "    STATISTICS_MEAN:         0.0087725620798214\n",
       "    STATISTICS_MINIMUM:      8.7451635408797e-06\n",
       "    STATISTICS_SKIPFACTORX:  1\n",
       "    STATISTICS_SKIPFACTORY:  1\n",
       "    STATISTICS_STDDEV:       0.0076530515881425\n",
       "    scale_factor:            1.0\n",
       "    add_offset:              0.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 1111</li><li><span class='xr-has-index'>x</span>: 1490</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-042df8a0-9744-4fdc-ad68-65f9acbc36fa' class='xr-array-in' type='checkbox' checked><label for='section-042df8a0-9744-4fdc-ad68-65f9acbc36fa' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-db065b88-9248-45eb-9057-dfbb61218688' class='xr-section-summary-in' type='checkbox'  checked><label for='section-db065b88-9248-45eb-9057-dfbb61218688' class='xr-section-summary' >Coordinates: <span>(4)</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 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'>112.9 113.0 113.0 ... 159.1 159.1</div><input id='attrs-ca2ca7d0-93ba-4f44-8fe3-06656d9213c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca2ca7d0-93ba-4f44-8fe3-06656d9213c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad4d69be-5132-49fb-a0c9-19cd2ba0d090' class='xr-var-data-in' type='checkbox'><label for='data-ad4d69be-5132-49fb-a0c9-19cd2ba0d090' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([112.935332, 112.966326, 112.99732 , ..., 159.02338 , 159.054374,\n",
       "       159.085368])</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'>-9.237 -9.268 ... -43.61 -43.64</div><input id='attrs-8cddc883-449d-4bd6-ab85-4471be1b1f01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cddc883-449d-4bd6-ab85-4471be1b1f01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9033938-a574-4f8e-937e-02df9fccac54' class='xr-var-data-in' type='checkbox'><label for='data-c9033938-a574-4f8e-937e-02df9fccac54' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ -9.236772,  -9.267767,  -9.298762, ..., -43.579098, -43.610093,\n",
       "       -43.641088])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-36e14287-b3bb-4dd0-bfaa-bf9b4234e20d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36e14287-b3bb-4dd0-bfaa-bf9b4234e20d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52a42c03-69cf-4665-a92f-fed5b65f05fa' class='xr-var-data-in' type='checkbox'><label for='data-52a42c03-69cf-4665-a92f-fed5b65f05fa' 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([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-7b8114e7-5e3f-4f2f-ae58-d21a9bec7b3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b8114e7-5e3f-4f2f-ae58-d21a9bec7b3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96a7ab6c-c46a-4cd6-9ae2-ff3bc5cbb03e' class='xr-var-data-in' type='checkbox'><label for='data-96a7ab6c-c46a-4cd6-9ae2-ff3bc5cbb03e' 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>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;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>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;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>112.919835 0.030993979865771817 0.0 -9.221274999999999 0.0 -0.030994878487848782</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-afbf7d7c-80c5-4943-8e67-35734f804322' class='xr-section-summary-in' type='checkbox'  ><label for='section-afbf7d7c-80c5-4943-8e67-35734f804322' 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-6a1e5788-b117-45fd-9358-e2c18fdb3825' class='xr-index-data-in' type='checkbox'/><label for='index-6a1e5788-b117-45fd-9358-e2c18fdb3825' 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([112.93533198993289, 112.96632596979866, 112.99731994966443,\n",
       "               113.0283139295302, 113.05930790939598, 113.09030188926175,\n",
       "              113.12129586912752, 113.15228984899329, 113.18328382885906,\n",
       "              113.21427780872483,\n",
       "              ...\n",
       "              158.80642219127517, 158.83741617114094,  158.8684101510067,\n",
       "              158.89940413087248, 158.93039811073828, 158.96139209060402,\n",
       "              158.99238607046982,  159.0233800503356, 159.05437403020136,\n",
       "              159.08536801006713],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1490))</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-a7e17a5b-80aa-4a22-ada8-691d5492aad8' class='xr-index-data-in' type='checkbox'/><label for='index-a7e17a5b-80aa-4a22-ada8-691d5492aad8' 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([ -9.236772439243923,  -9.267767317731773,   -9.29876219621962,\n",
       "                -9.32975707470747,  -9.360751953195319,  -9.391746831683166,\n",
       "               -9.422741710171016,  -9.453736588658865,  -9.484731467146714,\n",
       "               -9.515726345634562,\n",
       "              ...\n",
       "               -43.36213365436543,  -43.39312853285328,  -43.42412341134113,\n",
       "              -43.455118289828974,  -43.48611316831683,  -43.51710804680467,\n",
       "              -43.548102925292525,  -43.57909780378037, -43.610092682268224,\n",
       "               -43.64108756075607],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=1111))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>band</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aab2d0f0-c0d1-484d-899c-b8e495f534fb' class='xr-index-data-in' type='checkbox'/><label for='index-aab2d0f0-c0d1-484d-899c-b8e495f534fb' 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(Int64Index([1], dtype=&#x27;int64&#x27;, name=&#x27;band&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-689d8f8b-d26c-4cd1-867f-013e0b5de0ff' class='xr-section-summary-in' type='checkbox'  ><label for='section-689d8f8b-d26c-4cd1-867f-013e0b5de0ff' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>STATISTICS_COVARIANCES :</span></dt><dd>5.856919861077052e-05</dd><dt><span>STATISTICS_MAXIMUM :</span></dt><dd>0.1543258279562</dd><dt><span>STATISTICS_MEAN :</span></dt><dd>0.0087725620798214</dd><dt><span>STATISTICS_MINIMUM :</span></dt><dd>8.7451635408797e-06</dd><dt><span>STATISTICS_SKIPFACTORX :</span></dt><dd>1</dd><dt><span>STATISTICS_SKIPFACTORY :</span></dt><dd>1</dd><dt><span>STATISTICS_STDDEV :</span></dt><dd>0.0076530515881425</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>add_offset :</span></dt><dd>0.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (band: 1, y: 1111, x: 1490)>\n",
       "array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * x            (x) float64 112.9 113.0 113.0 113.0 ... 159.0 159.0 159.1 159.1\n",
       "  * y            (y) float64 -9.237 -9.268 -9.299 -9.33 ... -43.58 -43.61 -43.64\n",
       "  * band         (band) int32 1\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    AREA_OR_POINT:           Area\n",
       "    STATISTICS_COVARIANCES:  5.856919861077052e-05\n",
       "    STATISTICS_MAXIMUM:      0.1543258279562\n",
       "    STATISTICS_MEAN:         0.0087725620798214\n",
       "    STATISTICS_MINIMUM:      8.7451635408797e-06\n",
       "    STATISTICS_SKIPFACTORX:  1\n",
       "    STATISTICS_SKIPFACTORY:  1\n",
       "    STATISTICS_STDDEV:       0.0076530515881425\n",
       "    scale_factor:            1.0\n",
       "    add_offset:              0.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aus_downsampled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c3015df4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.030993979865771817, -0.030994878487848782)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aus_downsampled.rio.resolution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a16e7e23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.031, -0.031)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usgs['GeophysicsGravity_HGM_USCanada.tif'].rio.resolution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c9aa3835",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.031, -0.031)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gravdir = r'D:\\Geophysics\\_GeophysicalDatGravAus'\n",
    "source_ds = gdal.Open(gravdir + \"\\\\\" + 'GeophysicsGravity_HGM_Australia.tif')\n",
    "\n",
    "gravdir = r'D:\\\\Geophysics\\_GeophysicalDatGrav'\n",
    "\n",
    "# Open the target raster to get its geotransform and spatial reference\n",
    "target_ds = gdal.Open(gravdir + \"\\\\\" + 'GeophysicsGravity_HGM_USCanada.tif')\n",
    "target_geo_transform = target_ds.GetGeoTransform()\n",
    "target_spatial_ref = target_ds.GetSpatialRef()\n",
    "\n",
    "# Create a new dataset for the reprojected raster\n",
    "reproj_ds = gdal.Warp('reprojected.tif', source_ds,\n",
    "                      format='GTiff',\n",
    "                      xRes=target_geo_transform[1],\n",
    "                      yRes=target_geo_transform[5],\n",
    "                      dstSRS=target_spatial_ref)\n",
    "\n",
    "# Close the datasets\n",
    "source_ds = None\n",
    "target_ds = None\n",
    "reproj_ds = None\n",
    "\n",
    "reproj = rioxarray.open_rasterio('reprojected.tif')\n",
    "reproj.rio.resolution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "37c2e409",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x22380cd1a30>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reproj.plot(vmin=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "13bfb50c",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "negative dimensions are not allowed",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[19], line 8\u001b[0m\n\u001b[0;32m      5\u001b[0m usgs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mGeophysicsGravity_HGM_USCanada.tif\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124muscan\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m      7\u001b[0m \u001b[38;5;66;03m#auscan = xr.concat([reproj, usgs['GeophysicsGravity_HGM_USCanada.tif']],dim='band')\u001b[39;00m\n\u001b[1;32m----> 8\u001b[0m auscan \u001b[38;5;241m=\u001b[39m \u001b[43mmerge_arrays\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdataarrays\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mreproj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43musgs\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mGeophysicsGravity_HGM_USCanada.tif\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mres\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mreproj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresolution\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mEPSG:4326\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m     10\u001b[0m auscan\n",
      "File \u001b[1;32m~\\AppData\\Local\\miniconda3\\envs\\pangeo\\lib\\site-packages\\rioxarray\\merge.py:174\u001b[0m, in \u001b[0;36mmerge_arrays\u001b[1;34m(dataarrays, bounds, res, nodata, precision, method, crs, parse_coordinates)\u001b[0m\n\u001b[0;32m    171\u001b[0m         rioduckarrays\u001b[38;5;241m.\u001b[39mappend(RasterioDatasetDuck(dataarray))\n\u001b[0;32m    173\u001b[0m \u001b[38;5;66;03m# use rasterio to merge\u001b[39;00m\n\u001b[1;32m--> 174\u001b[0m merged_data, merged_transform \u001b[38;5;241m=\u001b[39m _rio_merge(\n\u001b[0;32m    175\u001b[0m     rioduckarrays,\n\u001b[0;32m    176\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m{key: val \u001b[38;5;28;01mfor\u001b[39;00m key, val \u001b[38;5;129;01min\u001b[39;00m input_kwargs\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m val \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m},\n\u001b[0;32m    177\u001b[0m )\n\u001b[0;32m    178\u001b[0m \u001b[38;5;66;03m# generate merged data array\u001b[39;00m\n\u001b[0;32m    179\u001b[0m representative_array \u001b[38;5;241m=\u001b[39m rioduckarrays[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39m_xds\n",
      "File \u001b[1;32m~\\AppData\\Local\\miniconda3\\envs\\pangeo\\lib\\site-packages\\rasterio\\merge.py:293\u001b[0m, in \u001b[0;36mmerge\u001b[1;34m(datasets, bounds, res, nodata, dtype, precision, indexes, output_count, resampling, method, target_aligned_pixels, dst_path, dst_kwds)\u001b[0m\n\u001b[0;32m    290\u001b[0m     out_profile[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnodata\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m nodata\n\u001b[0;32m    292\u001b[0m \u001b[38;5;66;03m# create destination array\u001b[39;00m\n\u001b[1;32m--> 293\u001b[0m dest \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mzeros\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43moutput_count\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput_height\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput_width\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    295\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m nodata \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    296\u001b[0m     nodataval \u001b[38;5;241m=\u001b[39m nodata\n",
      "\u001b[1;31mValueError\u001b[0m: negative dimensions are not allowed"
     ]
    }
   ],
   "source": [
    "#auscan.name = 'auscan'\n",
    "reproj.name ='aus'\n",
    "usgs['GeophysicsGravity_HGM_USCanada.tif'].name = 'uscan'\n",
    "\n",
    "#auscan = xr.concat([reproj, usgs['GeophysicsGravity_HGM_USCanada.tif']],dim='band')\n",
    "auscan = merge_arrays(dataarrays = [reproj, usgs['GeophysicsGravity_HGM_USCanada.tif']], res = reproj.rio.resolution(), crs=\"EPSG:4326\")\n",
    "\n",
    "auscan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7f092ec4",
   "metadata": {},
   "outputs": [
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       "array([[[-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        ...,\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * x            (x) float64 -168.1 -168.1 -168.1 -168.0 ... 159.0 159.1 159.1\n",
       "  * y            (y) float64 83.11 83.08 83.05 83.02 ... -43.59 -43.62 -43.65\n",
       "  * band         (band) int32 1\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    AREA_OR_POINT:  Area\n",
       "    _FillValue:     -3.4028235e+38\n",
       "    scale_factor:   1.0\n",
       "    add_offset:     0.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'aus'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 4090</li><li><span class='xr-has-index'>x</span>: 10556</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9c57ac1a-b54d-43be-b65f-5e92c79cca1d' class='xr-array-in' type='checkbox' checked><label for='section-9c57ac1a-b54d-43be-b65f-5e92c79cca1d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-3.403e+38 -3.403e+38 -3.403e+38 ... -3.403e+38 -3.403e+38 -3.403e+38</span></div><div class='xr-array-data'><pre>array([[[-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        ...,\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-ffb27e80-7010-492a-9bbf-730ccd1880d4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffb27e80-7010-492a-9bbf-730ccd1880d4' class='xr-section-summary' >Coordinates: <span>(4)</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 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'>-168.1 -168.1 ... 159.1 159.1</div><input id='attrs-d890250b-1cc0-49b7-a5d9-b9e785f3f7d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d890250b-1cc0-49b7-a5d9-b9e785f3f7d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b73e757e-e751-438b-86b1-296c74ad4b34' class='xr-var-data-in' type='checkbox'><label for='data-b73e757e-e751-438b-86b1-296c74ad4b34' 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([-168.113, -168.082, -168.051, ...,  159.03 ,  159.061,  159.092])</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'>83.11 83.08 83.05 ... -43.62 -43.65</div><input id='attrs-a05033c1-1632-42bd-a0cf-e9287290a7e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a05033c1-1632-42bd-a0cf-e9287290a7e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e44f353a-317a-4ae4-89ac-dc8bb2480d06' class='xr-var-data-in' type='checkbox'><label for='data-e44f353a-317a-4ae4-89ac-dc8bb2480d06' 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([ 83.111,  83.08 ,  83.049, ..., -43.586, -43.617, -43.648])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-68f40c6e-518b-4335-9d3a-d531e39a33cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68f40c6e-518b-4335-9d3a-d531e39a33cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1d97963-f0eb-4d12-96db-44e0802d2ee4' class='xr-var-data-in' type='checkbox'><label for='data-f1d97963-f0eb-4d12-96db-44e0802d2ee4' 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([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-8ec33484-af2e-4919-8aaa-282d461c9b24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ec33484-af2e-4919-8aaa-282d461c9b24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e29897cd-9dbc-4fb6-956b-09e60ff99884' class='xr-var-data-in' type='checkbox'><label for='data-e29897cd-9dbc-4fb6-956b-09e60ff99884' 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>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;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>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;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>-168.1285 0.031 0.0 83.12650000000001 0.0 -0.031</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-874ef5ba-141c-4c29-9733-46451cdf6fdf' class='xr-section-summary-in' type='checkbox'  ><label for='section-874ef5ba-141c-4c29-9733-46451cdf6fdf' 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-61bc7881-6044-4050-908a-c357eeaca60d' class='xr-index-data-in' type='checkbox'/><label for='index-61bc7881-6044-4050-908a-c357eeaca60d' 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([          -168.113,           -168.082,           -168.051,\n",
       "                         -168.02,           -167.989,           -167.958,\n",
       "                        -167.927,           -167.896,           -167.865,\n",
       "                        -167.834,\n",
       "              ...\n",
       "                         158.813,            158.844,            158.875,\n",
       "                         158.906,            158.937, 158.96800000000002,\n",
       "              158.99900000000002, 159.02999999999997, 159.06099999999998,\n",
       "              159.09199999999998],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=10556))</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-65a4e70d-4d4e-4ae1-8854-7991de1bbf40' class='xr-index-data-in' type='checkbox'/><label for='index-65a4e70d-4d4e-4ae1-8854-7991de1bbf40' 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([             83.111,               83.08,              83.049,\n",
       "                           83.018,   82.98700000000001,              82.956,\n",
       "                           82.925,              82.894,              82.863,\n",
       "                82.83200000000001,\n",
       "              ...\n",
       "                          -43.369,  -43.39999999999999,             -43.431,\n",
       "               -43.46199999999999, -43.492999999999995,             -43.524,\n",
       "               -43.55499999999999,             -43.586,  -43.61699999999999,\n",
       "              -43.647999999999996],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=4090))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>band</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-74b39ce0-ff5d-470d-a173-53771c6d1c5a' class='xr-index-data-in' type='checkbox'/><label for='index-74b39ce0-ff5d-470d-a173-53771c6d1c5a' 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(Int64Index([1], dtype=&#x27;int64&#x27;, name=&#x27;band&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6467582c-b66f-4374-bd09-978109c4e5ce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6467582c-b66f-4374-bd09-978109c4e5ce' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>_FillValue :</span></dt><dd>-3.4028235e+38</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>add_offset :</span></dt><dd>0.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'aus' (band: 1, y: 4090, x: 10556)>\n",
       "array([[[-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        ...,\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38],\n",
       "        [-3.4028235e+38, -3.4028235e+38, -3.4028235e+38, ...,\n",
       "         -3.4028235e+38, -3.4028235e+38, -3.4028235e+38]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * x            (x) float64 -168.1 -168.1 -168.1 -168.0 ... 159.0 159.1 159.1\n",
       "  * y            (y) float64 83.11 83.08 83.05 83.02 ... -43.59 -43.62 -43.65\n",
       "  * band         (band) int32 1\n",
       "    spatial_ref  int32 0\n",
       "Attributes:\n",
       "    AREA_OR_POINT:  Area\n",
       "    _FillValue:     -3.4028235e+38\n",
       "    scale_factor:   1.0\n",
       "    add_offset:     0.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#auscan.name = 'auscan'\n",
    "reproj.name ='aus'\n",
    "usgs['GeophysicsGravity_HGM_USCanada.tif'].name = 'uscan'\n",
    "\n",
    "#auscan = xr.concat([reproj, usgs['GeophysicsGravity_HGM_USCanada.tif']],dim='band')\n",
    "auscan = merge_arrays(dataarrays = [reproj, usgs['GeophysicsGravity_HGM_USCanada.tif']], res = (0.031, 0.031), crs=\"EPSG:4326\")\n",
    "\n",
    "auscan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87adcb34",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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