From c184259179770e69b2546f446a76dcbeebf244d2 Mon Sep 17 00:00:00 2001
From: Carl Boettiger <cboettig@gmail.com>
Date: Sun, 3 Nov 2024 22:31:15 -0800
Subject: [PATCH] updated notes

---
 index.md                |   6 ++
 myst.yml                |   1 +
 reading/spatial-3.ipynb |  45 ++++-----
 reading/spatial-4.ipynb | 204 +++++++++++++++++++++-------------------
 reading/spatial-5.ipynb |   2 +-
 5 files changed, 141 insertions(+), 117 deletions(-)

diff --git a/index.md b/index.md
index 0392703..f395cbd 100644
--- a/index.md
+++ b/index.md
@@ -33,3 +33,9 @@ reproducible notebooks, databases, data visualization, geospatial analysis and m
 collaborative setting. See our [syllabus](https://espm-157.carlboettiger.info/overview/syllabus.html) and [schedule overview](https://espm-157.carlboettiger.info/overview/schedule.html)
 for details. _Please see_ [enrollment](https://espm-157.carlboettiger.info/overview/syllabus.html#enrollment) if you questions about getting into this course!
 
+## Links
+
+- [Course DataHub](https://nature.datahub.berkeley.edu) 
+- [Course Forum (Slack)](https://espm-157.slack.com/)
+- [Course GitHub](https://github.com/espm-157-f24/)
+
diff --git a/myst.yml b/myst.yml
index 0299e7f..cee8d4f 100644
--- a/myst.yml
+++ b/myst.yml
@@ -33,6 +33,7 @@ project:
         - file: reading/spatial-1.ipynb
         - file: reading/spatial-2.ipynb
         - file: reading/spatial-3.ipynb
+        - file: reading/spatial-4.ipynb
         
 site:
   template: book-theme
diff --git a/reading/spatial-3.ipynb b/reading/spatial-3.ipynb
index 3f40c8d..ad43318 100644
--- a/reading/spatial-3.ipynb
+++ b/reading/spatial-3.ipynb
@@ -21,7 +21,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7acca453f60943dfa4764ebcd1e4c3de",
+       "model_id": "5f1c24eadcaa475aa8971ee9a17c6462",
        "version_major": 2,
        "version_minor": 0
       },
@@ -47354,7 +47354,7 @@
        "</div>"
       ],
       "text/plain": [
-       "<pystac.item_collection.ItemCollection at 0x7b49693cac60>"
+       "<pystac.item_collection.ItemCollection at 0x780feb385fa0>"
       ]
      },
      "execution_count": 4,
@@ -47796,9 +47796,9 @@
        "  * time         (time) datetime64[ns] 32B 2024-06-15T15:51:53.600000 ... 202...\n",
        "Data variables:\n",
        "    nir08        (time, y, x) uint16 16MB dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;\n",
-       "    red          (time, y, x) uint16 16MB dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d910ce87-b3ae-4ce3-b3e3-13a2e1d89bd1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d910ce87-b3ae-4ce3-b3e3-13a2e1d89bd1' 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'>y</span>: 1627</li><li><span class='xr-has-index'>x</span>: 1220</li><li><span class='xr-has-index'>time</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e95bc637-867a-42b5-b777-026684b4a68c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e95bc637-867a-42b5-b777-026684b4a68c' 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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.583e+06 4.583e+06 ... 4.566e+06</div><input id='attrs-238a93f2-a829-44a9-9b73-27ceb4e1968a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-238a93f2-a829-44a9-9b73-27ceb4e1968a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12f2a81e-2a88-4a70-b400-ebc1ee42f355' class='xr-var-data-in' type='checkbox'><label for='data-12f2a81e-2a88-4a70-b400-ebc1ee42f355' 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><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([4582615., 4582605., 4582595., ..., 4566375., 4566365., 4566355.])</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'>6.678e+05 6.678e+05 ... 6.8e+05</div><input id='attrs-ad898522-340a-4718-91f4-4f5a217d1ded' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad898522-340a-4718-91f4-4f5a217d1ded' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b90d704-0e26-4b12-b926-2f57140d9ea1' class='xr-var-data-in' type='checkbox'><label for='data-5b90d704-0e26-4b12-b926-2f57140d9ea1' 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><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([667815., 667825., 667835., ..., 679985., 679995., 680005.])</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'>32618</div><input id='attrs-485e7431-2c2b-41d7-8e20-21bc97fee20a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-485e7431-2c2b-41d7-8e20-21bc97fee20a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30b5dd77-eba1-4dcd-af80-0074be8f3089' class='xr-var-data-in' type='checkbox'><label for='data-30b5dd77-eba1-4dcd-af80-0074be8f3089' 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>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</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 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 18N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-75.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>GeoTransform :</span></dt><dd>667810 10 0 4582620 0 -10</dd></dl></div><div class='xr-var-data'><pre>array(32618, dtype=int32)</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'>2024-06-15T15:51:53.600000 ... 2...</div><input id='attrs-08958b5b-fc36-47be-858c-753b3dbdd337' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08958b5b-fc36-47be-858c-753b3dbdd337' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a1a56eb-2016-4937-9bb2-53d85de89244' class='xr-var-data-in' type='checkbox'><label for='data-1a1a56eb-2016-4937-9bb2-53d85de89244' 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;2024-06-15T15:51:53.600000000&#x27;, &#x27;2024-06-25T15:51:51.156000000&#x27;,\n",
+       "    red          (time, y, x) uint16 16MB dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7c876848-8006-4a29-8901-934dc6f97d1f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7c876848-8006-4a29-8901-934dc6f97d1f' 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'>y</span>: 1627</li><li><span class='xr-has-index'>x</span>: 1220</li><li><span class='xr-has-index'>time</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e227b97f-6ec8-4cf0-9781-06c4a7c9ae6c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e227b97f-6ec8-4cf0-9781-06c4a7c9ae6c' 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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.583e+06 4.583e+06 ... 4.566e+06</div><input id='attrs-b2d965a4-988c-48d8-ac65-b2234805fba1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2d965a4-988c-48d8-ac65-b2234805fba1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3e8e895-7ba1-403f-b695-a7633ec6219b' class='xr-var-data-in' type='checkbox'><label for='data-d3e8e895-7ba1-403f-b695-a7633ec6219b' 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><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([4582615., 4582605., 4582595., ..., 4566375., 4566365., 4566355.])</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'>6.678e+05 6.678e+05 ... 6.8e+05</div><input id='attrs-7fec3b63-1609-4e32-803b-045648582e68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fec3b63-1609-4e32-803b-045648582e68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5de421e5-0d10-4182-a7cd-b355cfa5eca8' class='xr-var-data-in' type='checkbox'><label for='data-5de421e5-0d10-4182-a7cd-b355cfa5eca8' 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><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([667815., 667825., 667835., ..., 679985., 679995., 680005.])</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'>32618</div><input id='attrs-4375849e-374c-4ab4-ae22-136c5680b1f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4375849e-374c-4ab4-ae22-136c5680b1f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6faca32-026b-4ba8-9b5d-f10d0d2d6069' class='xr-var-data-in' type='checkbox'><label for='data-a6faca32-026b-4ba8-9b5d-f10d0d2d6069' 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>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</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 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 18N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-75.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>GeoTransform :</span></dt><dd>667810 10 0 4582620 0 -10</dd></dl></div><div class='xr-var-data'><pre>array(32618, dtype=int32)</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'>2024-06-15T15:51:53.600000 ... 2...</div><input id='attrs-be7b9e2d-d1af-44a7-9e2d-f772aac9e5c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be7b9e2d-d1af-44a7-9e2d-f772aac9e5c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4746fda-e100-4af1-aae2-648180d36ccd' class='xr-var-data-in' type='checkbox'><label for='data-d4746fda-e100-4af1-aae2-648180d36ccd' 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;2024-06-15T15:51:53.600000000&#x27;, &#x27;2024-06-25T15:51:51.156000000&#x27;,\n",
        "       &#x27;2024-08-14T15:51:48.959000000&#x27;, &#x27;2024-08-24T15:51:45.374000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d2c9c193-3252-449e-a027-e2eeaa33a414' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2c9c193-3252-449e-a027-e2eeaa33a414' 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>nir08</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</div><input id='attrs-fc1ac0b3-7616-4ff7-b08c-0aeae192679d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc1ac0b3-7616-4ff7-b08c-0aeae192679d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b98b698-60dd-49d2-ab61-adce3c313cd4' class='xr-var-data-in' type='checkbox'><label for='data-3b98b698-60dd-49d2-ab61-adce3c313cd4' 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>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d3b4f4e0-12cf-4b21-9e38-8ce6d5a46cb5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d3b4f4e0-12cf-4b21-9e38-8ce6d5a46cb5' 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>nir08</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</div><input id='attrs-bfb0be32-7954-4c00-ab10-d1d2679f1071' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfb0be32-7954-4c00-ab10-d1d2679f1071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb9cdc1d-4ea9-4324-9a46-89d500c98587' class='xr-var-data-in' type='checkbox'><label for='data-eb9cdc1d-4ea9-4324-9a46-89d500c98587' 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>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
        "            <table style=\"border-collapse: collapse;\">\n",
@@ -47882,7 +47882,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>red</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</div><input id='attrs-579d8527-b45b-4d35-96de-e74dc1d1b2fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-579d8527-b45b-4d35-96de-e74dc1d1b2fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57ba1f66-b9eb-43ab-80a1-832cf0b8ccdf' class='xr-var-data-in' type='checkbox'><label for='data-57ba1f66-b9eb-43ab-80a1-832cf0b8ccdf' 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>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>red</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1627, 1220), meta=np.ndarray&gt;</div><input id='attrs-5cdac1dc-2c24-4e8d-bcfe-2701a82a33fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5cdac1dc-2c24-4e8d-bcfe-2701a82a33fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24afe142-d921-480c-acdc-0c2925c49bbf' class='xr-var-data-in' type='checkbox'><label for='data-24afe142-d921-480c-acdc-0c2925c49bbf' 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>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
        "            <table style=\"border-collapse: collapse;\">\n",
@@ -47966,19 +47966,19 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ccc397d2-258d-4482-aa39-ef3600ba195b' class='xr-section-summary-in' type='checkbox'  ><label for='section-ccc397d2-258d-4482-aa39-ef3600ba195b' 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>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ee9658a4-62d2-43f7-bdb0-60824dd9a33a' class='xr-index-data-in' type='checkbox'/><label for='index-ee9658a4-62d2-43f7-bdb0-60824dd9a33a' 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(Index([4582615.0, 4582605.0, 4582595.0, 4582585.0, 4582575.0, 4582565.0,\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-855ecbe7-00ab-4640-ad6d-4c3567179fbc' class='xr-section-summary-in' type='checkbox'  ><label for='section-855ecbe7-00ab-4640-ad6d-4c3567179fbc' 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>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a85ed746-9864-4a76-910d-2feb6388a68c' class='xr-index-data-in' type='checkbox'/><label for='index-a85ed746-9864-4a76-910d-2feb6388a68c' 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(Index([4582615.0, 4582605.0, 4582595.0, 4582585.0, 4582575.0, 4582565.0,\n",
        "       4582555.0, 4582545.0, 4582535.0, 4582525.0,\n",
        "       ...\n",
        "       4566445.0, 4566435.0, 4566425.0, 4566415.0, 4566405.0, 4566395.0,\n",
        "       4566385.0, 4566375.0, 4566365.0, 4566355.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=1627))</pre></div></li><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-baad7bec-a5a7-447c-9129-f7ad24dab8ba' class='xr-index-data-in' type='checkbox'/><label for='index-baad7bec-a5a7-447c-9129-f7ad24dab8ba' 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(Index([667815.0, 667825.0, 667835.0, 667845.0, 667855.0, 667865.0, 667875.0,\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=1627))</pre></div></li><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-7902879f-0cb7-41dd-936f-af2033b6096e' class='xr-index-data-in' type='checkbox'/><label for='index-7902879f-0cb7-41dd-936f-af2033b6096e' 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(Index([667815.0, 667825.0, 667835.0, 667845.0, 667855.0, 667865.0, 667875.0,\n",
        "       667885.0, 667895.0, 667905.0,\n",
        "       ...\n",
        "       679915.0, 679925.0, 679935.0, 679945.0, 679955.0, 679965.0, 679975.0,\n",
        "       679985.0, 679995.0, 680005.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1220))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1ee2c910-4ad8-42a2-aa2c-a25d1fdc7f89' class='xr-index-data-in' type='checkbox'/><label for='index-1ee2c910-4ad8-42a2-aa2c-a25d1fdc7f89' 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(DatetimeIndex([&#x27;2024-06-15 15:51:53.600000&#x27;, &#x27;2024-06-25 15:51:51.156000&#x27;,\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1220))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6490011b-d99c-401d-a690-142abc83d564' class='xr-index-data-in' type='checkbox'/><label for='index-6490011b-d99c-401d-a690-142abc83d564' 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(DatetimeIndex([&#x27;2024-06-15 15:51:53.600000&#x27;, &#x27;2024-06-25 15:51:51.156000&#x27;,\n",
        "               &#x27;2024-08-14 15:51:48.959000&#x27;, &#x27;2024-08-24 15:51:45.374000&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f00e7dd7-766f-42ae-8885-321245b03718' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f00e7dd7-766f-42ae-8885-321245b03718' 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>"
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d4011d7f-b84f-4ff0-ab72-fc58b79512c1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4011d7f-b84f-4ff0-ab72-fc58b79512c1' 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> Size: 32MB\n",
@@ -48445,7 +48445,7 @@
        "Coordinates:\n",
        "  * y            (y) float64 13kB 4.583e+06 4.583e+06 ... 4.566e+06 4.566e+06\n",
        "  * x            (x) float64 10kB 6.678e+05 6.678e+05 ... 6.8e+05 6.8e+05\n",
-       "    spatial_ref  int32 4B 32618</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'>y</span>: 1627</li><li><span class='xr-has-index'>x</span>: 1220</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7bf966bc-5d2a-4bed-9222-f5257e6bc54d' class='xr-array-in' type='checkbox' checked><label for='section-7bf966bc-5d2a-4bed-9222-f5257e6bc54d' 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>0.8859 0.8805 0.8716 0.9001 0.8955 0.9044 ... nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[0.88591885, 0.88051675, 0.87161283, ..., 0.85875371, 0.84881165,\n",
+       "    spatial_ref  int32 4B 32618</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'>y</span>: 1627</li><li><span class='xr-has-index'>x</span>: 1220</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1c238e4c-b587-4b18-99ea-a8e67fba9241' class='xr-array-in' type='checkbox' checked><label for='section-1c238e4c-b587-4b18-99ea-a8e67fba9241' 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>0.8859 0.8805 0.8716 0.9001 0.8955 0.9044 ... nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[0.88591885, 0.88051675, 0.87161283, ..., 0.85875371, 0.84881165,\n",
        "        0.86324397],\n",
        "       [0.85873743, 0.88231669, 0.90861641, ..., 0.75906042, 0.82126435,\n",
        "        0.84697593],\n",
@@ -48457,17 +48457,17 @@
        "       [0.8458809 , 0.48283024, 0.41006737, ...,        nan,        nan,\n",
        "               nan],\n",
        "       [0.82337862, 0.4601535 , 0.44678909, ...,        nan,        nan,\n",
-       "               nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-4a5c9dc6-f663-485a-9727-1dc72df373ee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4a5c9dc6-f663-485a-9727-1dc72df373ee' class='xr-section-summary' >Coordinates: <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-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'>4.583e+06 4.583e+06 ... 4.566e+06</div><input id='attrs-cb9e12b9-b7b0-4ee5-b278-52340b82988b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb9e12b9-b7b0-4ee5-b278-52340b82988b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53d1bad0-db7a-40d0-9ec7-6eb09c2289fd' class='xr-var-data-in' type='checkbox'><label for='data-53d1bad0-db7a-40d0-9ec7-6eb09c2289fd' 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><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([4582615., 4582605., 4582595., ..., 4566375., 4566365., 4566355.])</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'>6.678e+05 6.678e+05 ... 6.8e+05</div><input id='attrs-dcb67070-6ead-45f4-b649-0cf670a8c8a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcb67070-6ead-45f4-b649-0cf670a8c8a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3250326d-e894-4402-b175-3d59d020f9bb' class='xr-var-data-in' type='checkbox'><label for='data-3250326d-e894-4402-b175-3d59d020f9bb' 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><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([667815., 667825., 667835., ..., 679985., 679995., 680005.])</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'>32618</div><input id='attrs-2af65a78-7247-42db-8b5c-167b60a5d8d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2af65a78-7247-42db-8b5c-167b60a5d8d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38af76b3-0ff4-4a5f-9408-ff39e1cdcd43' class='xr-var-data-in' type='checkbox'><label for='data-38af76b3-0ff4-4a5f-9408-ff39e1cdcd43' 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>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</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 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 18N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-75.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>GeoTransform :</span></dt><dd>667810 10 0 4582620 0 -10</dd></dl></div><div class='xr-var-data'><pre>array(32618, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b0a09e6f-0e69-464c-a66d-24600bfe8e62' class='xr-section-summary-in' type='checkbox'  ><label for='section-b0a09e6f-0e69-464c-a66d-24600bfe8e62' class='xr-section-summary' >Indexes: <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-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0aeb70df-5db4-461f-8376-06dbc38dca01' class='xr-index-data-in' type='checkbox'/><label for='index-0aeb70df-5db4-461f-8376-06dbc38dca01' 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(Index([4582615.0, 4582605.0, 4582595.0, 4582585.0, 4582575.0, 4582565.0,\n",
+       "               nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-316348ed-4423-4d9a-b3f9-398ba175d5c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-316348ed-4423-4d9a-b3f9-398ba175d5c3' class='xr-section-summary' >Coordinates: <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-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'>4.583e+06 4.583e+06 ... 4.566e+06</div><input id='attrs-3c63b160-9d4c-4955-8674-eeb885b68ce7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c63b160-9d4c-4955-8674-eeb885b68ce7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95da32b9-963b-4a72-8f17-67e100e6c187' class='xr-var-data-in' type='checkbox'><label for='data-95da32b9-963b-4a72-8f17-67e100e6c187' 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><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([4582615., 4582605., 4582595., ..., 4566375., 4566365., 4566355.])</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'>6.678e+05 6.678e+05 ... 6.8e+05</div><input id='attrs-fd3c61c6-a24a-49cb-96ce-a4008e0f673c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd3c61c6-a24a-49cb-96ce-a4008e0f673c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-befb21fd-cbb0-46ae-9ed8-1cd886adea47' class='xr-var-data-in' type='checkbox'><label for='data-befb21fd-cbb0-46ae-9ed8-1cd886adea47' 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><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32618</dd></dl></div><div class='xr-var-data'><pre>array([667815., 667825., 667835., ..., 679985., 679995., 680005.])</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'>32618</div><input id='attrs-c5161ec2-79ba-41dd-8d7d-6516c7a8c6d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5161ec2-79ba-41dd-8d7d-6516c7a8c6d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d7d914b-c932-4d82-9442-a65c635d46cd' class='xr-var-data-in' type='checkbox'><label for='data-1d7d914b-c932-4d82-9442-a65c635d46cd' 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>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;WGS 84 / UTM zone 18N&quot;,BASEGEOGCRS[&quot;WGS 84&quot;,ENSEMBLE[&quot;World Geodetic System 1984 ensemble&quot;,MEMBER[&quot;World Geodetic System 1984 (Transit)&quot;],MEMBER[&quot;World Geodetic System 1984 (G730)&quot;],MEMBER[&quot;World Geodetic System 1984 (G873)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1150)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1674)&quot;],MEMBER[&quot;World Geodetic System 1984 (G1762)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2139)&quot;],MEMBER[&quot;World Geodetic System 1984 (G2296)&quot;],ELLIPSOID[&quot;WGS 84&quot;,6378137,298.257223563,LENGTHUNIT[&quot;metre&quot;,1]],ENSEMBLEACCURACY[2.0]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;UTM zone 18N&quot;,METHOD[&quot;Transverse Mercator&quot;,ID[&quot;EPSG&quot;,9807]],PARAMETER[&quot;Latitude of natural origin&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]],PARAMETER[&quot;Longitude of natural origin&quot;,-75,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Scale factor at natural origin&quot;,0.9996,SCALEUNIT[&quot;unity&quot;,1],ID[&quot;EPSG&quot;,8805]],PARAMETER[&quot;False easting&quot;,500000,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,0,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1]],USAGE[SCOPE[&quot;Navigation and medium accuracy spatial referencing.&quot;],AREA[&quot;Between 78°W and 72°W, northern hemisphere between equator and 84°N, onshore and offshore. Bahamas. Canada - Nunavut; Ontario; Quebec. Colombia. Cuba. Ecuador. Greenland. Haiti. Jamaica. Panama. Turks and Caicos Islands. United States (USA). Venezuela.&quot;],BBOX[0,-78,84,-72]],ID[&quot;EPSG&quot;,32618]]</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 ensemble</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 18N</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-75.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>GeoTransform :</span></dt><dd>667810 10 0 4582620 0 -10</dd></dl></div><div class='xr-var-data'><pre>array(32618, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e49950f1-4f11-4076-833c-ccd27e632fd9' class='xr-section-summary-in' type='checkbox'  ><label for='section-e49950f1-4f11-4076-833c-ccd27e632fd9' class='xr-section-summary' >Indexes: <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-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c8b1aed-56d0-42ff-9a55-990221d5dbd4' class='xr-index-data-in' type='checkbox'/><label for='index-0c8b1aed-56d0-42ff-9a55-990221d5dbd4' 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(Index([4582615.0, 4582605.0, 4582595.0, 4582585.0, 4582575.0, 4582565.0,\n",
        "       4582555.0, 4582545.0, 4582535.0, 4582525.0,\n",
        "       ...\n",
        "       4566445.0, 4566435.0, 4566425.0, 4566415.0, 4566405.0, 4566395.0,\n",
        "       4566385.0, 4566375.0, 4566365.0, 4566355.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=1627))</pre></div></li><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-8f753437-eb0c-45fc-9173-b4623abea05c' class='xr-index-data-in' type='checkbox'/><label for='index-8f753437-eb0c-45fc-9173-b4623abea05c' 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(Index([667815.0, 667825.0, 667835.0, 667845.0, 667855.0, 667865.0, 667875.0,\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=1627))</pre></div></li><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-34bb77d0-a950-4f72-b882-7d3e38734600' class='xr-index-data-in' type='checkbox'/><label for='index-34bb77d0-a950-4f72-b882-7d3e38734600' 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(Index([667815.0, 667825.0, 667835.0, 667845.0, 667855.0, 667865.0, 667875.0,\n",
        "       667885.0, 667895.0, 667905.0,\n",
        "       ...\n",
        "       679915.0, 679925.0, 679935.0, 679945.0, 679955.0, 679965.0, 679975.0,\n",
        "       679985.0, 679995.0, 680005.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1220))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-026f722f-e70f-4eef-b0bb-8d46bdba6f1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-026f722f-e70f-4eef-b0bb-8d46bdba6f1c' 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>"
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=1220))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6fd0c974-1d86-4287-9afd-764f8715b644' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6fd0c974-1d86-4287-9afd-764f8715b644' 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.DataArray (y: 1627, x: 1220)> Size: 16MB\n",
@@ -48518,7 +48518,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7b494ef52810>"
+       "<matplotlib.image.AxesImage at 0x780faf5b1310>"
       ]
      },
      "execution_count": 9,
@@ -48552,7 +48552,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "66a9d71e-7fcc-4a63-abff-f62d4d9192b9",
    "metadata": {},
    "outputs": [],
@@ -48570,21 +48570,24 @@
    "id": "f9e9e67f-a4be-43d3-b3d4-0ee58a07c641",
    "metadata": {},
    "source": [
-    "We can also store a copy of our vector data:"
+    "Side note: optionally, we can also store a copy of our vector data, also setting the projection.  Common formats include geopackage, `.gpkg`, and `.parquet`.  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 15,
    "id": "89367115-c6b9-4012-918a-3292ce38a0d9",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# city.to_file(\"new_haven.shp\") # common legacy format, not ideal\n",
-    "# city.to_file(\"new_haven.gpkg\") # Good open standard\n",
+    "(city\n",
+    " .set_crs(\"EPSG:4326\")\n",
+    " .to_file(\"new_haven.gpkg\") # common open standard\n",
+    ")\n",
+    "\n",
     "\n",
     "# latest option, best performance but less widely known:\n",
-    "city.to_parquet(\"new_haven.parquet\")\n"
+    "city.set_crs(\"EPSG:4326\").to_parquet(\"new_haven.parquet\")\n"
    ]
   }
  ],
@@ -48604,7 +48607,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,
diff --git a/reading/spatial-4.ipynb b/reading/spatial-4.ipynb
index eacd28b..1b2721e 100644
--- a/reading/spatial-4.ipynb
+++ b/reading/spatial-4.ipynb
@@ -1,39 +1,120 @@
 {
  "cells": [
   {
+   "attachments": {
+    "d7b95307-317b-40c4-beb9-de3f91e5c379.png": {
+     "image/png": "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"
+    }
+   },
    "cell_type": "markdown",
    "id": "2124260a-f39e-4f6d-9469-fbac6c72a864",
    "metadata": {},
    "source": [
-    "# Zonal Statistics"
+    "# Zonal Statistics\n",
+    "\n",
+    "Having generated a Cloud-Optimized GeoTiff (COG) file containing our NDVI calculations, we are now ready to return to our redlining data and determine if indeed we still see the legacy of those racist practices more than 50 years after they were outlawed. \n",
+    "\n",
+    "The aggregation of raster pixels grouped by their containing polygons is something like the spatial equivalent of our `.group_by()` + `.aggregate()` operations in ibis, where the raster defines the values and the polygons define the groups.  \n",
+    "\n",
+    "To compute the average NDVI in each polygon, we will introduce yet another module -- `exactextract`.  This package can efficiently compute summary statistics for each polygon given a raster image.  While several different modules can perform this kind of aggregation, [`exactextract`](https://isciences.github.io/exactextract/index.html) is quite fast and scalable, using an efficient algorithm in C++, and gets it's name for an ability to account for fractional coverage of a raster cell by a polygon, like so. \n",
+    "\n",
+    "![image.png](attachment:d7b95307-317b-40c4-beb9-de3f91e5c379.png)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "63c059eb-dc3b-47f9-a544-e0f9ff3b7b75",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from exactextract import exact_extract\n"
+    "from exactextract import exact_extract\n",
+    "import ibis\n",
+    "from ibis import _\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af1b5864-d0be-43da-94eb-2fdaf7ab061e",
+   "metadata": {},
+   "source": [
+    "We begin as before by grabbing our remote city data.  Here we have added an additional filter to focus only on residental data, as non-residental sites are not graded even though they are still marked on the map. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "c21844bd-685b-4907-9396-30a8e44a85ea",
+   "execution_count": 2,
+   "id": "607ca58f-5d08-40ea-a5f1-836fe0dba47b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "exact_extract?"
+    "con = ibis.duckdb.connect(extensions=[\"spatial\"])\n",
+    "\n",
+    "redlines = (\n",
+    "    con\n",
+    "    .read_geo(\"/vsicurl/https://dsl.richmond.edu/panorama/redlining/static/mappinginequality.gpkg\")\n",
+    "    .filter(_.city == \"New Haven\", _.residential)\n",
+    "   )\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdd8adcd-63ef-4c02-a6d7-43157386404d",
+   "metadata": {},
+   "source": [
+    "Spatial operations such as overlaying polygons on the raster requires that the two datasets have **matching coordinate reference systems**.  While we have already transformed our raster data to the 'longitude, latitude' coordinates, EPSG:4326, we need to manually add this annotation to declare that our parquet data is already using this projection as well.  We do this with `.set_crs()` option on `geopandas` object:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "56c12787-459a-42f2-bd39-3c8dd63597cf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a5dd4b5535ec4ae5a7a4fa356dbe3c4b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "city =  redlines.execute().set_crs(\"EPSG:4326\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01864c30-a92d-4acd-9052-337ab209a8c8",
+   "metadata": {},
+   "source": [
+    "The `exact_extract` [documentation](https://isciences.github.io/exactextract/autoapi/exactextract/exact_extract/index.html) shows this is a flexible method able to take a raster and vector input and compute a range of summary statistics.  The method is also somewhat flexible in how it formats the output -- here we indicate we want the output formulated as a 'geopandas' object, keeping the geometry column and other useful columns from the original input data.\n",
+    "\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "id": "5e46e88c-ab93-4c36-8a48-1a777668726f",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/miniforge3/lib/python3.12/site-packages/exactextract/exact_extract.py:330: RuntimeWarning: Spatial reference system of input features does not exactly match raster.\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -71,7 +152,7 @@
        "      <td>New Haven</td>\n",
        "      <td>#76a865</td>\n",
        "      <td>0.709624</td>\n",
-       "      <td>MULTIPOLYGON (((-72.90000 41.36885, -72.90325 ...</td>\n",
+       "      <td>MULTIPOLYGON (((-72.9 41.36885, -72.90325 41.3...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -98,7 +179,7 @@
        "      <td>New Haven</td>\n",
        "      <td>#76a865</td>\n",
        "      <td>0.751388</td>\n",
-       "      <td>MULTIPOLYGON (((-72.90284 41.35795, -72.89990 ...</td>\n",
+       "      <td>MULTIPOLYGON (((-72.90284 41.35795, -72.8999 4...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -107,7 +188,7 @@
        "      <td>New Haven</td>\n",
        "      <td>#76a865</td>\n",
        "      <td>0.742981</td>\n",
-       "      <td>MULTIPOLYGON (((-72.89801 41.34930, -72.89883 ...</td>\n",
+       "      <td>MULTIPOLYGON (((-72.89801 41.3493, -72.89883 4...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -122,21 +203,21 @@
        "4    A5     A  New Haven  #76a865  0.742981   \n",
        "\n",
        "                                            geometry  \n",
-       "0  MULTIPOLYGON (((-72.90000 41.36885, -72.90325 ...  \n",
+       "0  MULTIPOLYGON (((-72.9 41.36885, -72.90325 41.3...  \n",
        "1  MULTIPOLYGON (((-72.89401 41.36331, -72.89256 ...  \n",
        "2  MULTIPOLYGON (((-72.90981 41.35949, -72.90284 ...  \n",
-       "3  MULTIPOLYGON (((-72.90284 41.35795, -72.89990 ...  \n",
-       "4  MULTIPOLYGON (((-72.89801 41.34930, -72.89883 ...  "
+       "3  MULTIPOLYGON (((-72.90284 41.35795, -72.8999 4...  \n",
+       "4  MULTIPOLYGON (((-72.89801 41.3493, -72.89883 4...  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "city_stats = exact_extract(\"ndvi.tif\", \n",
-    "                           \"new_haven.parquet\", \n",
+    "                           city, \n",
     "                           [\"mean\"], \n",
     "                           include_geom = True,\n",
     "                           include_cols=[\"label\", \"grade\", \"city\", \"fill\"],\n",
@@ -145,9 +226,17 @@
     "city_stats.head()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8b2f0e6b-f8f6-4d1a-9d8d-d9c8e70020f0",
+   "metadata": {},
+   "source": [
+    "We will write out this updated file as a parquet dataset. This provides both a mechanism to store our completed calculation and an easy way to go back from `geopandas` into `ibis`.  "
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "e9d6361b-c9a9-48e2-9b3f-818e88951d0b",
    "metadata": {},
    "outputs": [],
@@ -160,83 +249,16 @@
    "id": "e37afb42-dd1f-44ec-8180-99397dadd9ab",
    "metadata": {},
    "source": [
-    "We can bring our data back into ibis,"
+    "We can bring our data back into ibis, where we can do our familiar manipulations."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "id": "dc44e75d-c9f5-476b-8a09-b77833aafb23",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>grade</th>\n",
-       "      <th>ndvi</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>C</td>\n",
-       "      <td>0.547228</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>A</td>\n",
-       "      <td>0.730811</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>D</td>\n",
-       "      <td>0.486641</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>B</td>\n",
-       "      <td>0.609324</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  grade      ndvi\n",
-       "0     C  0.547228\n",
-       "1     A  0.730811\n",
-       "2     D  0.486641\n",
-       "3     B  0.609324"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "import ibis\n",
-    "from ibis import _\n",
-    "con = ibis.duckdb.connect(extensions=[\"spatial\"])\n",
-    "\n",
     "city = con.read_parquet(\"new_haven_stats.parquet\")"
    ]
   },
@@ -247,14 +269,6 @@
    "source": [
     " and we are finally ready to summarize the data to determine if the spectre of redlining remains: on average, are A grades still greener than D grades?  Construct the rest of the `ibis` code to compute the average NDVI by grade."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fea87402-e985-41b2-9999-e7749f28e6be",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -273,7 +287,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.10"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,
diff --git a/reading/spatial-5.ipynb b/reading/spatial-5.ipynb
index 75cf824..9c4ce48 100644
--- a/reading/spatial-5.ipynb
+++ b/reading/spatial-5.ipynb
@@ -59,7 +59,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.10"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,