Repository: corteva/rioxarray

Issue:
Add estimate UTM CRS method
Essentially would be: https://github.com/geopandas/geopandas/pull/1646

Could use the `bounds()` to get the centroid.

Discussion:

Patch:
diff --git a/.travis.yml b/.travis.yml
index e9dbd6fc..8c32b17b 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -54,7 +54,7 @@ before_install:
 - conda config --add channels conda-forge
 - conda config --set channel_priority strict
 # Create conda environment
-- conda create -n test python=$PYTHON_VERSION rasterio scipy xarray netcdf4 dask pandoc
+- conda create -n test python=$PYTHON_VERSION rasterio xarray scipy pyproj netcdf4 dask pandoc
 - source $HOME/miniconda/bin/activate test
 
 install:
diff --git a/docs/examples/reproject.ipynb b/docs/examples/reproject.ipynb
index ebe8f31f..cc5c269c 100644
--- a/docs/examples/reproject.ipynb
+++ b/docs/examples/reproject.ipynb
@@ -32,7 +32,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "xds = xarray.open_dataset(\"PLANET_SCOPE_3D.nc\")"
+    "xds = xarray.open_dataset(\"../../test/test_data/input/PLANET_SCOPE_3D.nc\")"
    ]
   },
   {
@@ -42,13 +42,458 @@
    "outputs": [
     {
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+       "}\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",
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+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2 {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
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+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:      (time: 2, x: 10, y: 10)\n",
+       "Coordinates:\n",
+       "    spatial_ref  int64 0\n",
+       "  * x            (x) float64 4.663e+05 4.663e+05 ... 4.663e+05 4.663e+05\n",
+       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T...\n",
+       "  * y            (y) float64 8.085e+06 8.085e+06 ... 8.085e+06 8.085e+06\n",
+       "Data variables:\n",
+       "    blue         (time, y, x) float64 6.611 5.581 0.3996 ... 3.491 5.056 3.368\n",
+       "    green        (time, y, x) float64 7.921 66.15 30.1 ... 21.76 27.29 18.41</pre><div class='xr-wrap' hidden><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-7fce09ea-485c-462c-b766-40d73f423ae5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7fce09ea-485c-462c-b766-40d73f423ae5' 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</span>: 2</li><li><span class='xr-has-index'>x</span>: 10</li><li><span class='xr-has-index'>y</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1c3bc2fa-dde8-4af5-8a89-5fb0d74e6e4a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c3bc2fa-dde8-4af5-8a89-5fb0d74e6e4a' 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>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-223a52d2-8493-46ce-993c-489e0e3abc1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-223a52d2-8493-46ce-993c-489e0e3abc1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-629c7ec7-1616-4e7f-9659-f593c8ac2c38' class='xr-var-data-in' type='checkbox'><label for='data-629c7ec7-1616-4e7f-9659-f593c8ac2c38' 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>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 22S&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;,-51],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;32722&quot;]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</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'>4.663e+05 4.663e+05 ... 4.663e+05</div><input id='attrs-df75e8f6-f822-46ec-b934-b01e3bdb67e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df75e8f6-f822-46ec-b934-b01e3bdb67e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd5182b9-690d-4e70-a0fe-ad079fdda070' class='xr-var-data-in' type='checkbox'><label for='data-cd5182b9-690d-4e70-a0fe-ad079fdda070' 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>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([466267.5, 466270.5, 466273.5, 466276.5, 466279.5, 466282.5, 466285.5,\n",
+       "       466288.5, 466291.5, 466294.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-12-19T10:27:29.687763 2016-...</div><input id='attrs-ec2a7d64-d96a-47ed-970e-f9f38b28d67b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec2a7d64-d96a-47ed-970e-f9f38b28d67b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce2ea0d-6c6a-43de-b19d-f194fec6c3ff' class='xr-var-data-in' type='checkbox'><label for='data-dce2ea0d-6c6a-43de-b19d-f194fec6c3ff' 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;2016-12-19T10:27:29.687763000&#x27;, &#x27;2016-12-29T12:52:42.347451000&#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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.085e+06 8.085e+06 ... 8.085e+06</div><input id='attrs-29239545-13e7-4de9-bc0d-c532a10a2a89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29239545-13e7-4de9-bc0d-c532a10a2a89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9835abfc-387c-498f-b279-6f11c20089fb' class='xr-var-data-in' type='checkbox'><label for='data-9835abfc-387c-498f-b279-6f11c20089fb' 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>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([8084698.5, 8084695.5, 8084692.5, 8084689.5, 8084686.5, 8084683.5,\n",
+       "       8084680.5, 8084677.5, 8084674.5, 8084671.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-02b28d91-2ed0-43b2-a45f-8505496bb0fd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02b28d91-2ed0-43b2-a45f-8505496bb0fd' class='xr-section-summary' >Data variables: <span>(2)</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>blue</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f9943083-d9be-48f3-af53-52d171a5bbe7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9943083-d9be-48f3-af53-52d171a5bbe7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03bc58ba-1fb7-49da-93f6-c42233ddf512' class='xr-var-data-in' type='checkbox'><label for='data-03bc58ba-1fb7-49da-93f6-c42233ddf512' 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>units :</span></dt><dd>DN</dd><dt><span>nodata :</span></dt><dd>0.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><pre>array([[[6.611017, 5.580979, 0.399607, 2.052803, 5.479985, 4.760219,\n",
+       "         5.077927, 5.574792, 0.726683, 5.170288],\n",
+       "        [4.535516, 0.088263, 4.222302, 0.289199, 3.478147, 3.227945,\n",
+       "         2.736443, 2.821799, 1.04221 , 1.099616],\n",
+       "        [0.071364, 4.393267, 0.496907, 2.311926, 1.19123 , 5.984189,\n",
+       "         5.266977, 1.146988, 3.219185, 0.982011],\n",
+       "        [5.818552, 5.176065, 4.891903, 4.557147, 4.706706, 4.670835,\n",
+       "         2.344188, 0.493237, 2.707488, 4.15662 ],\n",
+       "        [0.78458 , 3.838047, 0.803847, 1.588861, 5.002692, 2.565792,\n",
+       "         5.195116, 2.642173, 1.47148 , 6.854931],\n",
+       "        [4.407593, 6.734126, 3.702884, 4.682068, 0.498895, 2.931409,\n",
+       "         5.713952, 6.388658, 6.618634, 3.267176],\n",
+       "        [6.175152, 2.331721, 6.829246, 1.650656, 5.530157, 0.167316,\n",
+       "         6.406627, 4.559968, 0.083601, 1.231478],\n",
+       "        [2.438085, 1.593681, 5.902827, 2.124327, 1.870033, 4.519462,\n",
+       "         4.845505, 6.214475, 2.237778, 4.178488],\n",
+       "        [5.855639, 5.824333, 6.006212, 5.43411 , 3.393885, 6.183958,\n",
+       "         1.284061, 0.028555, 6.726706, 1.516993],\n",
+       "        [0.844103, 5.61329 , 6.978045, 1.183779, 2.539376, 1.268038,\n",
+       "         1.27574 , 5.101129, 2.020225, 2.081746]],\n",
+       "\n",
+       "       [[6.242907, 6.394763, 1.302492, 2.895077, 0.537664, 5.012127,\n",
+       "         4.380069, 1.624007, 5.56236 , 4.303491],\n",
+       "        [6.745937, 3.653031, 5.116965, 1.835256, 3.514732, 6.523679,\n",
+       "         0.17986 , 2.444248, 5.169099, 0.584623],\n",
+       "        [2.119518, 0.479052, 4.274714, 6.019049, 6.346329, 2.858441,\n",
+       "         3.976887, 4.218218, 4.320734, 3.941107],\n",
+       "        [2.974649, 6.67996 , 3.16875 , 3.507162, 2.909711, 1.359386,\n",
+       "         4.023015, 0.258809, 2.007625, 5.744746],\n",
+       "        [2.572982, 1.250802, 4.652006, 6.310958, 3.266477, 3.216613,\n",
+       "         3.47315 , 1.713415, 5.9575  , 2.729016],\n",
+       "        [2.743341, 4.203021, 1.306215, 2.840115, 5.351451, 2.774677,\n",
+       "         2.621753, 5.288077, 0.722618, 4.086008],\n",
+       "        [3.168672, 4.031863, 5.775087, 3.487762, 6.034522, 4.721887,\n",
+       "         5.093018, 0.386024, 2.278799, 1.536351],\n",
+       "        [4.548959, 4.797754, 6.371152, 3.69425 , 6.855343, 1.987757,\n",
+       "         4.749654, 1.750539, 1.804795, 4.966536],\n",
+       "        [1.78139 , 1.544275, 1.750026, 3.373274, 2.604254, 5.894015,\n",
+       "         3.217723, 5.637478, 2.900347, 2.097813],\n",
+       "        [1.844174, 6.994962, 2.504717, 5.292132, 0.184411, 4.870834,\n",
+       "         1.888442, 3.491315, 5.055704, 3.368395]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>green</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-99379dd8-7a4b-4bc8-abec-691062d5e6b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99379dd8-7a4b-4bc8-abec-691062d5e6b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5bbf13b-f11a-4972-a603-8355ca5a15f4' class='xr-var-data-in' type='checkbox'><label for='data-e5bbf13b-f11a-4972-a603-8355ca5a15f4' 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>units :</span></dt><dd>DN</dd><dt><span>nodata :</span></dt><dd>0.0</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><pre>array([[[ 7.920639, 66.150832, 30.096116, 30.437197, 57.794734, 11.538647,\n",
+       "         14.426782, 35.593171, 53.784858,  0.449093],\n",
+       "        [23.804111, 67.910347, 18.694533, 30.41474 , 68.117674, 44.906057,\n",
+       "         62.311842, 37.485047, 57.134336,  7.52572 ],\n",
+       "        [36.653481, 39.596833, 61.07603 , 56.883093, 29.635613, 64.114699,\n",
+       "         42.341689, 54.724789, 31.872344, 11.282554],\n",
+       "        [32.502176, 28.090549, 58.398927, 41.224019, 34.804777, 32.184565,\n",
+       "         59.392327,  9.155824, 52.967172, 67.409236],\n",
+       "        [18.79468 ,  8.543429, 35.834698,  3.596245, 30.252802, 41.549499,\n",
+       "         23.060248,  7.267762, 27.374099,  0.684024],\n",
+       "        [ 9.93227 , 44.509446, 22.01927 , 28.514121, 36.715233, 15.03939 ,\n",
+       "          2.43399 ,  0.636075, 34.43023 , 37.024545],\n",
+       "        [28.874823,  1.514255, 34.210822, 10.49793 , 54.025491, 64.294026,\n",
+       "         36.212813, 17.766628, 45.295952, 10.349576],\n",
+       "        [58.961924, 47.334638, 64.844646, 37.634131,  7.815025, 35.139303,\n",
+       "         18.501505, 35.01185 , 27.761908, 13.240655],\n",
+       "        [49.544668, 57.716538, 27.389778, 11.604377, 24.826367, 15.449456,\n",
+       "         26.482386, 42.855739, 10.4958  , 59.267182],\n",
+       "        [37.094093, 43.294246, 33.240747, 16.85513 , 54.705119, 14.633291,\n",
+       "         35.138742, 50.101683, 57.495953, 52.795405]],\n",
+       "\n",
+       "       [[26.137058, 16.448086,  4.503539, 33.351036, 20.32524 , 63.369743,\n",
+       "         11.531512, 38.629561, 59.821441, 11.547508],\n",
+       "        [ 6.438471, 28.948907,  9.949052, 23.234921, 65.539507,  9.822554,\n",
+       "         55.754023, 51.590388, 57.047098,  4.929671],\n",
+       "        [32.360472, 17.939979, 52.889505, 69.181176, 39.2923  , 56.442225,\n",
+       "          5.699603, 21.092554,  8.93472 , 23.810367],\n",
+       "        [ 3.715695, 30.653733, 44.540496, 48.578544, 24.032477, 30.339109,\n",
+       "         37.376636, 58.787274, 49.308994, 59.510765],\n",
+       "        [37.991912, 50.023013, 63.711135, 26.546118, 60.561058, 36.098302,\n",
+       "         10.725673, 40.51609 , 47.479255, 42.710909],\n",
+       "        [15.32887 , 15.878984, 30.914778, 25.902812,  3.815428, 35.530366,\n",
+       "         48.426293, 44.280075,  4.468083, 18.00032 ],\n",
+       "        [58.286993, 20.397714, 63.124   , 69.117495,  1.32436 , 29.024715,\n",
+       "         31.601531, 34.307982,  7.990292, 36.159696],\n",
+       "        [34.674335, 62.344993,  5.714717,  2.161448, 66.714977, 52.443751,\n",
+       "         12.791859, 63.707491, 13.697063,  9.394474],\n",
+       "        [16.766346, 26.260123, 40.68158 , 18.695085, 64.812126, 23.151592,\n",
+       "         50.597642, 61.308205, 31.517123, 23.469797],\n",
+       "        [44.670989, 17.533084, 39.034907, 32.676726, 53.275139, 48.731172,\n",
+       "         12.958856, 21.760335, 27.292202, 18.409063]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4c52c8d-33a6-4405-999e-665d291c190f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f4c52c8d-33a6-4405-999e-665d291c190f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
       "text/plain": [
        "<xarray.Dataset>\n",
        "Dimensions:      (time: 2, x: 10, y: 10)\n",
        "Coordinates:\n",
        "    spatial_ref  int64 ...\n",
        "  * x            (x) float64 4.663e+05 4.663e+05 ... 4.663e+05 4.663e+05\n",
-       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T12:52:42.347451\n",
+       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T...\n",
        "  * y            (y) float64 8.085e+06 8.085e+06 ... 8.085e+06 8.085e+06\n",
        "Data variables:\n",
        "    blue         (time, y, x) float64 ...\n",
@@ -72,7 +517,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x7f185c1ca278>"
+       "<matplotlib.collections.QuadMesh at 0x7f92959ad430>"
       ]
      },
      "execution_count": 4,
@@ -81,7 +526,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -114,7 +559,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "xds_lonlat = xds.rio.reproject(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")"
+    "xds_lonlat = xds.rio.reproject(\"EPSG:4326\")"
    ]
   },
   {
@@ -124,19 +569,462 @@
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".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-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",
+       "  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",
+       "  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-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-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, 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",
+       "  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.Dataset&gt;\n",
+       "Dimensions:      (time: 2, x: 10, y: 10)\n",
+       "Coordinates:\n",
+       "  * x            (x) float64 -51.32 -51.32 -51.32 ... -51.32 -51.32 -51.32\n",
+       "  * y            (y) float64 -17.32 -17.32 -17.32 ... -17.32 -17.32 -17.32\n",
+       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T...\n",
+       "    spatial_ref  int64 0\n",
+       "Data variables:\n",
+       "    blue         (time, y, x) float64 6.611 5.581 0.3996 ... 3.491 5.056 3.368\n",
+       "    green        (time, y, x) float64 7.921 66.15 30.1 ... 21.76 27.29 18.41</pre><div class='xr-wrap' hidden><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-cec6df98-c2d4-4832-aebf-7a980af8f7b2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cec6df98-c2d4-4832-aebf-7a980af8f7b2' 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</span>: 2</li><li><span class='xr-has-index'>x</span>: 10</li><li><span class='xr-has-index'>y</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-590f9d23-4368-41c0-b9cb-d265a950456a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-590f9d23-4368-41c0-b9cb-d265a950456a' 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'>-51.32 -51.32 ... -51.32 -51.32</div><input id='attrs-415fc8ab-9ddf-4792-8d9b-cf35d3cadf7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415fc8ab-9ddf-4792-8d9b-cf35d3cadf7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe8786e3-90f6-477f-9609-d92c27c92290' class='xr-var-data-in' type='checkbox'><label for='data-fe8786e3-90f6-477f-9609-d92c27c92290' 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([-51.317454, -51.317426, -51.317399, -51.317371, -51.317343, -51.317316,\n",
+       "       -51.317288, -51.31726 , -51.317233, -51.317205])</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'>-17.32 -17.32 ... -17.32 -17.32</div><input id='attrs-6378601f-e319-4d96-a20f-b7cd9155fce7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6378601f-e319-4d96-a20f-b7cd9155fce7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-507ca929-e43b-4c05-91b4-59798bbae9f7' class='xr-var-data-in' type='checkbox'><label for='data-507ca929-e43b-4c05-91b4-59798bbae9f7' 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([-17.322876, -17.322903, -17.322931, -17.322959, -17.322986, -17.323014,\n",
+       "       -17.323042, -17.323069, -17.323097, -17.323125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2016-12-19T10:27:29.687763 2016-...</div><input id='attrs-93ca70a1-6f7d-4270-8f96-2c880595ebb1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93ca70a1-6f7d-4270-8f96-2c880595ebb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-866990ca-fb27-4538-a7a3-e5ba55d033d1' class='xr-var-data-in' type='checkbox'><label for='data-866990ca-fb27-4538-a7a3-e5ba55d033d1' 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;2016-12-19T10:27:29.687763000&#x27;, &#x27;2016-12-29T12:52:42.347451000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</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'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-43ba7909-802c-4115-be2c-d6104a1cddb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43ba7909-802c-4115-be2c-d6104a1cddb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98ca88d2-0e32-4987-8cc6-1bafd1ae6d25' class='xr-var-data-in' type='checkbox'><label for='data-98ca88d2-0e32-4987-8cc6-1bafd1ae6d25' 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>GEOGCRS[&quot;WGS 84&quot;,DATUM[&quot;World Geodetic System 1984&quot;,ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],CS[ellipsoidal,2],AXIS[&quot;geodetic latitude (Lat)&quot;,north,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],AXIS[&quot;geodetic longitude (Lon)&quot;,east,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]]</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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCRS[&quot;WGS 84&quot;,DATUM[&quot;World Geodetic System 1984&quot;,ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],CS[ellipsoidal,2],AXIS[&quot;geodetic latitude (Lat)&quot;,north,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],AXIS[&quot;geodetic longitude (Lon)&quot;,east,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]]</dd><dt><span>GeoTransform :</span></dt><dd>-51.31746780720891 2.7678699822269306e-05 0.0 -17.322861663733065 0.0 -2.7678699822269306e-05</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-697643eb-5e31-41a9-8703-442ddc141d70' class='xr-section-summary-in' type='checkbox'  checked><label for='section-697643eb-5e31-41a9-8703-442ddc141d70' class='xr-section-summary' >Data variables: <span>(2)</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>blue</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.611 5.581 0.3996 ... 5.056 3.368</div><input id='attrs-9d124e0c-be45-48cc-bb29-636cdd6e9470' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d124e0c-be45-48cc-bb29-636cdd6e9470' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a72628e-327b-4e16-a1ab-f5b412971402' class='xr-var-data-in' type='checkbox'><label for='data-5a72628e-327b-4e16-a1ab-f5b412971402' 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>units :</span></dt><dd>DN</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><pre>array([[[6.61101706, 5.58097901, 0.39960727, 2.05280345, 5.47998484,\n",
+       "         4.76021916, 5.07792715, 5.57479217, 0.72668295, 5.17028805],\n",
+       "        [4.53551623, 0.08826297, 4.22230213, 0.28919903, 3.47814709,\n",
+       "         3.22794508, 2.73644333, 2.82179869, 1.04221025, 1.09961647],\n",
+       "        [0.07136352, 4.39326719, 0.49690677, 2.31192634, 1.19123023,\n",
+       "         5.98418893, 5.26697738, 1.14698827, 3.21918509, 0.98201077],\n",
+       "        [5.81855223, 5.17606488, 4.89190312, 4.55714657, 4.70670585,\n",
+       "         4.67083516, 2.34418779, 0.4932369 , 2.70748782, 4.15661977],\n",
+       "        [0.78457995, 3.83804728, 0.80384702, 1.58886148, 5.00269192,\n",
+       "         2.56579153, 5.19511563, 2.6421726 , 1.47148022, 6.85493052],\n",
+       "        [4.40759261, 6.73412648, 3.70288412, 4.68206812, 0.49889505,\n",
+       "         2.93140894, 5.71395224, 6.38865828, 6.61863439, 3.26717611],\n",
+       "        [6.17515163, 2.33172093, 6.82924574, 1.65065578, 5.53015689,\n",
+       "         0.16731611, 6.40662729, 4.55996818, 0.08360072, 1.23147801],\n",
+       "        [2.43808458, 1.59368058, 5.90282702, 2.12432736, 1.8700329 ,\n",
+       "         4.51946233, 4.84550488, 6.21447495, 2.23777817, 4.17848811],\n",
+       "        [5.85563919, 5.82433331, 6.00621159, 5.43410984, 3.39388501,\n",
+       "         6.18395763, 1.28406097, 0.02855524, 6.72670605, 1.51699291],\n",
+       "        [0.84410255, 5.61328959, 6.97804534, 1.18377926, 2.53937552,\n",
+       "         1.26803824, 1.27574049, 5.10112907, 2.02022521, 2.08174614]],\n",
+       "...\n",
+       "       [[6.24290664, 6.39476317, 1.30249235, 2.89507681, 0.5376643 ,\n",
+       "         5.01212706, 4.38006939, 1.62400749, 5.56236028, 4.30349107],\n",
+       "        [6.74593668, 3.65303136, 5.11696455, 1.83525557, 3.51473159,\n",
+       "         6.52367921, 0.17986011, 2.44424775, 5.16909939, 0.58462293],\n",
+       "        [2.11951807, 0.47905249, 4.27471358, 6.01904917, 6.34632929,\n",
+       "         2.85844128, 3.97688665, 4.21821752, 4.32073426, 3.9411069 ],\n",
+       "        [2.97464873, 6.67996018, 3.16875018, 3.50716191, 2.9097115 ,\n",
+       "         1.35938603, 4.0230148 , 0.2588095 , 2.00762528, 5.74474576],\n",
+       "        [2.57298212, 1.25080228, 4.65200582, 6.31095753, 3.26647688,\n",
+       "         3.21661254, 3.4731501 , 1.71341466, 5.95750029, 2.72901564],\n",
+       "        [2.74334064, 4.20302139, 1.30621538, 2.84011532, 5.35145147,\n",
+       "         2.77467654, 2.6217532 , 5.28807657, 0.72261773, 4.08600786],\n",
+       "        [3.1686723 , 4.0318634 , 5.77508699, 3.48776179, 6.0345218 ,\n",
+       "         4.72188719, 5.09301838, 0.38602444, 2.27879875, 1.5363515 ],\n",
+       "        [4.54895876, 4.79775447, 6.3711522 , 3.69424969, 6.85534296,\n",
+       "         1.98775739, 4.74965416, 1.75053883, 1.80479493, 4.96653593],\n",
+       "        [1.78138972, 1.54427475, 1.75002571, 3.37327355, 2.60425433,\n",
+       "         5.89401538, 3.2177233 , 5.63747771, 2.90034677, 2.09781306],\n",
+       "        [1.84417405, 6.99496234, 2.50471667, 5.29213205, 0.1844106 ,\n",
+       "         4.87083388, 1.88844217, 3.49131529, 5.05570379, 3.36839469]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>green</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.921 66.15 30.1 ... 27.29 18.41</div><input id='attrs-806ef568-6e5d-4438-b530-15853f31098a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-806ef568-6e5d-4438-b530-15853f31098a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9893d64-046a-46be-a194-ac74feec8e34' class='xr-var-data-in' type='checkbox'><label for='data-c9893d64-046a-46be-a194-ac74feec8e34' 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>units :</span></dt><dd>DN</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><pre>array([[[ 7.92063876, 66.15083163, 30.09611622, 30.43719706,\n",
+       "         57.79473407, 11.53864677, 14.42678195, 35.5931706 ,\n",
+       "         53.78485769,  0.44909335],\n",
+       "        [23.80411143, 67.91034696, 18.6945325 , 30.41473977,\n",
+       "         68.11767437, 44.90605663, 62.31184244, 37.48504719,\n",
+       "         57.13433649,  7.52571983],\n",
+       "        [36.65348061, 39.59683262, 61.07602968, 56.88309328,\n",
+       "         29.63561283, 64.11469949, 42.34168918, 54.7247894 ,\n",
+       "         31.87234425, 11.28255401],\n",
+       "        [32.50217644, 28.0905485 , 58.39892665, 41.22401876,\n",
+       "         34.80477692, 32.18456541, 59.39232697,  9.15582412,\n",
+       "         52.96717208, 67.40923645],\n",
+       "        [18.79468009,  8.54342894, 35.83469773,  3.59624497,\n",
+       "         30.25280185, 41.54949902, 23.06024792,  7.26776162,\n",
+       "         27.37409939,  0.68402392],\n",
+       "        [ 9.93226996, 44.50944555, 22.01927024, 28.5141208 ,\n",
+       "         36.71523344, 15.03939035,  2.43398964,  0.63607503,\n",
+       "         34.43022974, 37.02454468],\n",
+       "        [28.87482271,  1.51425484, 34.21082199, 10.49792965,\n",
+       "         54.02549098, 64.29402555, 36.21281265, 17.76662845,\n",
+       "...\n",
+       "         24.03247674, 30.33910879, 37.37663568, 58.78727396,\n",
+       "         49.30899357, 59.51076479],\n",
+       "        [37.99191205, 50.0230132 , 63.71113469, 26.54611832,\n",
+       "         60.5610581 , 36.09830221, 10.72567322, 40.51609048,\n",
+       "         47.47925466, 42.71090946],\n",
+       "        [15.32887012, 15.8789836 , 30.91477844, 25.90281227,\n",
+       "          3.81542846, 35.53036591, 48.42629307, 44.28007476,\n",
+       "          4.46808288, 18.00031979],\n",
+       "        [58.28699332, 20.39771424, 63.12400017, 69.11749464,\n",
+       "          1.32435965, 29.02471509, 31.60153124, 34.30798249,\n",
+       "          7.99029205, 36.15969559],\n",
+       "        [34.67433533, 62.34499312,  5.71471651,  2.16144808,\n",
+       "         66.71497747, 52.4437509 , 12.79185872, 63.70749094,\n",
+       "         13.69706259,  9.39447357],\n",
+       "        [16.76634605, 26.26012306, 40.68158023, 18.69508482,\n",
+       "         64.81212607, 23.15159177, 50.59764238, 61.30820521,\n",
+       "         31.51712269, 23.46979658],\n",
+       "        [44.67098863, 17.53308399, 39.03490717, 32.67672611,\n",
+       "         53.27513876, 48.73117231, 12.95885589, 21.760335  ,\n",
+       "         27.29220175, 18.40906318]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fcf6fb60-5394-4bfc-822e-a3123562257c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fcf6fb60-5394-4bfc-822e-a3123562257c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
       "text/plain": [
        "<xarray.Dataset>\n",
        "Dimensions:      (time: 2, x: 10, y: 10)\n",
        "Coordinates:\n",
        "  * x            (x) float64 -51.32 -51.32 -51.32 ... -51.32 -51.32 -51.32\n",
        "  * y            (y) float64 -17.32 -17.32 -17.32 ... -17.32 -17.32 -17.32\n",
-       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T12:52:42.347451\n",
+       "  * time         (time) datetime64[ns] 2016-12-19T10:27:29.687763 2016-12-29T...\n",
        "    spatial_ref  int64 0\n",
        "Data variables:\n",
        "    blue         (time, y, x) float64 6.611 5.581 0.3996 ... 3.491 5.056 3.368\n",
-       "    green        (time, y, x) float64 7.921 66.15 30.1 ... 21.76 27.29 18.41\n",
-       "Attributes:\n",
-       "    creation_date:  2019-04-12 14:35:16.846951"
+       "    green        (time, y, x) float64 7.921 66.15 30.1 ... 21.76 27.29 18.41"
       ]
      },
      "execution_count": 6,
@@ -156,7 +1044,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x7f185c0c27f0>"
+       "<matplotlib.collections.QuadMesh at 0x7f928d879fd0>"
       ]
      },
      "execution_count": 7,
@@ -165,7 +1053,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -179,6 +1067,38 @@
    "source": [
     "xds_lonlat.green.where(xds_lonlat.green!=xds_lonlat.green.rio.nodata).isel(time=1).plot()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reproject to UTM\n",
+    "\n",
+    "API Reference:\n",
+    "\n",
+    "- [rio.estimate_utm_crs()](../rioxarray.rst#rioxarray.rioxarray.XRasterBase.estimate_utm_crs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CRS.from_epsg(32722)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xds_utm = xds.rio.reproject(xds.rio.estimate_utm_crs())\n",
+    "xds_utm.rio.crs"
+   ]
   }
  ],
  "metadata": {
@@ -197,7 +1117,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/getting_started/crs_management.ipynb b/docs/getting_started/crs_management.ipynb
index d1d64d1d..a684a23a 100644
--- a/docs/getting_started/crs_management.ipynb
+++ b/docs/getting_started/crs_management.ipynb
@@ -35,7 +35,8 @@
     "#### API Documentation\n",
     "\n",
     "- [rio.write_crs()](../rioxarray.rst#rioxarray.rioxarray.XRasterBase.write_crs)\n",
-    "- [rio.crs](../rioxarray.rst#rioxarray.rioxarray.XRasterBase.crs)\n"
+    "- [rio.crs](../rioxarray.rst#rioxarray.rioxarray.XRasterBase.crs)\n",
+    "- [rio.estimate_utm_crs()](../rioxarray.rst#rioxarray.rioxarray.XRasterBase.estimate_utm_crs)"
    ]
   },
   {
@@ -327,7 +328,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,
diff --git a/docs/history.rst b/docs/history.rst
index 45c12fe7..b1f3d60f 100644
--- a/docs/history.rst
+++ b/docs/history.rst
@@ -3,7 +3,7 @@ History
 
 Latest
 ------
-
+- ENH: Added `rio.estimate_utm_crs` (issue #181)
 
 0.1.1
 ------
diff --git a/rioxarray/rioxarray.py b/rioxarray/rioxarray.py
index 648fc6ff..2b395727 100644
--- a/rioxarray/rioxarray.py
+++ b/rioxarray/rioxarray.py
@@ -496,6 +496,54 @@ class XRasterBase(object):
             grid_mapping_name=grid_mapping_name, inplace=True
         )
 
+    def estimate_utm_crs(self, datum_name="WGS 84"):
+        """Returns the estimated UTM CRS based on the bounds of the dataset.
+
+        .. versionadded:: 0.2
+
+        .. note:: Requires pyproj 3+
+
+        Parameters
+        ----------
+        datum_name : str, optional
+            The name of the datum to use in the query. Default is WGS 84.
+
+        Returns
+        -------
+        rasterio.crs.CRS
+        """
+        try:
+            from pyproj.aoi import AreaOfInterest
+            from pyproj.database import query_utm_crs_info
+        except ImportError:
+            raise RuntimeError("pyproj 3+ required for estimate_utm_crs.")
+
+        if self.crs is None:
+            raise RuntimeError("crs must be set to estimate UTM CRS.")
+
+        # ensure using geographic coordinates
+        if self.crs.is_geographic:
+            minx, miny, maxx, maxy = self.bounds(recalc=True)
+        else:
+            minx, miny, maxx, maxy = self.transform_bounds("EPSG:4326", recalc=True)
+
+        x_center = np.mean([minx, maxx])
+        y_center = np.mean([miny, maxy])
+
+        utm_crs_list = query_utm_crs_info(
+            datum_name=datum_name,
+            area_of_interest=AreaOfInterest(
+                west_lon_degree=x_center,
+                south_lat_degree=y_center,
+                east_lon_degree=x_center,
+                north_lat_degree=y_center,
+            ),
+        )
+        try:
+            return CRS.from_epsg(utm_crs_list[0].code)
+        except IndexError:
+            raise RuntimeError("Unable to determine UTM CRS")
+
     def _cached_transform(self):
         """
         Get the transform from:


Test patch:
diff --git a/test/integration/test_integration_rioxarray.py b/test/integration/test_integration_rioxarray.py
index 8492b388..f3f3cc7c 100644
--- a/test/integration/test_integration_rioxarray.py
+++ b/test/integration/test_integration_rioxarray.py
@@ -5,6 +5,7 @@ from distutils.version import LooseVersion
 from functools import partial
 
 import numpy
+import pyproj
 import pytest
 import rasterio
 import scipy
@@ -31,6 +32,8 @@ from test.conftest import (
     _assert_xarrays_equal,
 )
 
+PYPROJ_LT_3 = LooseVersion(pyproj.__version__) < LooseVersion("3")
+
 
 @pytest.fixture(params=[xarray.open_dataset, xarray.open_dataarray])
 def modis_reproject(request):
@@ -2164,3 +2167,42 @@ def test_add_spatial_ref_warning():
 def test_add_xy_grid_meta_warning():
     with pytest.raises(RuntimeError):
         add_xy_grid_meta({})
+
+
+def test_estimate_utm_crs():
+    xds = rioxarray.open_rasterio(
+        os.path.join(TEST_INPUT_DATA_DIR, "cog.tif"),
+    )
+    if PYPROJ_LT_3:
+        with pytest.raises(RuntimeError, match=r"pyproj 3\+ required"):
+            xds.rio.estimate_utm_crs()
+    else:
+        assert xds.rio.estimate_utm_crs() == CRS.from_epsg(32618)
+        assert xds.rio.reproject("EPSG:4326").rio.estimate_utm_crs() == CRS.from_epsg(
+            32618
+        )
+        assert xds.rio.estimate_utm_crs("NAD83") == CRS.from_epsg(26918)
+
+
+@pytest.mark.skipif(PYPROJ_LT_3, reason="pyproj 3+ required")
+def test_estimate_utm_crs__missing_crs():
+    with pytest.raises(RuntimeError, match=r"crs must be set to estimate UTM CRS"):
+        xarray.Dataset().rio.estimate_utm_crs("NAD83")
+
+
+def test_estimate_utm_crs__out_of_bounds():
+    xds = xarray.DataArray(
+        numpy.zeros((2, 2)),
+        dims=("latitude", "longitude"),
+        coords={
+            "latitude": [-90.0, -90.0],
+            "longitude": [-5.0, 5.0],
+        },
+    )
+    xds.rio.write_crs("EPSG:4326", inplace=True)
+    if PYPROJ_LT_3:
+        with pytest.raises(RuntimeError, match=r"pyproj 3\+ required"):
+            xds.rio.estimate_utm_crs()
+    else:
+        with pytest.raises(RuntimeError, match=r"Unable to determine UTM CRS"):
+            xds.rio.estimate_utm_crs()