diff --git a/tutorials/wetsnow-explorer.ipynb b/tutorials/wetsnow-explorer.ipynb
new file mode 100644
index 0000000..8418d9d
--- /dev/null
+++ b/tutorials/wetsnow-explorer.ipynb
@@ -0,0 +1,1557 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exploring the wetsnow dataset with stac and xarray\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "import pyproj\n",
+    "from pystac_client import Client\n",
+    "from odc.stac import stac_load\n",
+    "import xarray as xr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The pystac_client allows us to explore the data of interest with (or without) a given area and time.\n",
+    "\n",
+    "First, we select the dataset, bounding box and datetime.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "collection = \"SENTINEL1_ALPS_WETSNOW\"\n",
+    "\n",
+    "bbox = [6, 47, 7, 48]\n",
+    "\n",
+    "date = ['2021-07-28T00:00:00Z', '2021-07-29T00:00:00Z']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The client creates a connection to EODC's stac api and finds data that matches the requested extents."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<Item id=WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO>,\n",
+       " <Item id=WSM_ALPS_20210728T054318_E042N012T6_S1B_IW_SLC_027990_004296_00_ENVEO>,\n",
+       " <Item id=WSM_ALPS_20210728T054318_E042N006T6_S1B_IW_SLC_027990_004296_00_ENVEO>]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client = Client.open('https://stac.eodc.eu/api/v1')\n",
+    "results = client.search(collections=collection,\n",
+    "    max_items=10,\n",
+    "    bbox=bbox,\n",
+    "    datetime=date,\n",
+    ")\n",
+    "result_items = list(results.items())\n",
+    "result_items"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The stac items contain all the metadata provided, as shown in the example in the next cell:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "\n",
+       "<style>\n",
+       ".pystac-summary {\n",
+       "    cursor: pointer;\n",
+       "    display: list-item;\n",
+       "    list-style: revert;\n",
+       "    margin-bottom: 0 !important;\n",
+       "\n",
+       "    .pystac-l {\n",
+       "        padding-left: 0.5em;\n",
+       "        color: rgb(64, 128, 128);\n",
+       "        font-style: italic;\n",
+       "    }\n",
+       "}\n",
+       ".pystac-row {\n",
+       "    overflow-wrap: break-word;\n",
+       "    padding-left: .825em;\n",
+       "\n",
+       "    .pystac-k {\n",
+       "        display: inline-block;\n",
+       "        margin: 0px 0.5em 0px 0px;\n",
+       "    }\n",
+       "    .pystac-v {\n",
+       "        color: rgb(186, 33, 33);\n",
+       "    }\n",
+       "}\n",
+       ".pystac-k {\n",
+       "    color: rgb(0, 128, 0);\n",
+       "    font-weight: 700;\n",
+       "}\n",
+       "</style>\n",
+       "<div class=\"jp-RenderedJSON jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div class=\"container\" style=\"line-height: normal;\">\n",
+       "        <ul style=\"padding: 0px; margin: 0px; list-style: none; display: block;\">\n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"Feature\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">stac_version</span>\n",
+       "            <span class=\"pystac-v\">\"1.0.0\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">id</span>\n",
+       "            <span class=\"pystac-v\">\"WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">properties</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">gsd</span>\n",
+       "            <span class=\"pystac-v\">100</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">datetime</span>\n",
+       "            <span class=\"pystac-v\">\"2021-07-28T05:43:18Z\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">platform</span>\n",
+       "            <span class=\"pystac-v\">\"SENTINEL-1B\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">constellation</span>\n",
+       "            <span class=\"pystac-v\">\"sentinel-1\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sat:orbit_state</span>\n",
+       "            <span class=\"pystac-v\">\"descending\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:product_type</span>\n",
+       "            <span class=\"pystac-v\">\"SLC\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">sar:polarizations</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">\"VV\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">\"VH\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:frequency_band</span>\n",
+       "            <span class=\"pystac-v\">\"C\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sat:relative_orbit</span>\n",
+       "            <span class=\"pystac-v\">139</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:instrument_mode</span>\n",
+       "            <span class=\"pystac-v\">\"IW\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:center_frequency</span>\n",
+       "            <span class=\"pystac-v\">5.40500045433435</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:pixel_spacing_range</span>\n",
+       "            <span class=\"pystac-v\">2.329562</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:observation_direction</span>\n",
+       "            <span class=\"pystac-v\">\"right\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sar:pixel_spacing_azimuth</span>\n",
+       "            <span class=\"pystac-v\">13.93271</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">sat:platform_international_designator</span>\n",
+       "            <span class=\"pystac-v\">\"2016-025A\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">geometry</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"Polygon\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">coordinates</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span><span class=\"pystac-l\">[] 5 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">4.069</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">43.003</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">1</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">5.395</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">48.997</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">2</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">8.881</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">49</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">3</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">7.207</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">43.006</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">4</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">4.069</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">43.003</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">links</span><span class=\"pystac-l\">[] 4 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">rel</span>\n",
+       "            <span class=\"pystac-v\">\"collection\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac.eodc.eu/api/v1/collections/SENTINEL1_ALPS_WETSNOW\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">1</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">rel</span>\n",
+       "            <span class=\"pystac-v\">\"parent\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac.eodc.eu/api/v1/collections/SENTINEL1_ALPS_WETSNOW\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">2</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">rel</span>\n",
+       "            <span class=\"pystac-v\">\"root\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac.eodc.eu/api/v1\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">title</span>\n",
+       "            <span class=\"pystac-v\">\"EODC Data Catalogue\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">3</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">rel</span>\n",
+       "            <span class=\"pystac-v\">\"self\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac.eodc.eu/api/v1/collections/SENTINEL1_ALPS_WETSNOW/items/WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"application/geo+json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">assets</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">WSM</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://data.eodc.eu/collections/s1-alps-wetsnow/track139/20210728/WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO.tif\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"image/tiff; application=geotiff\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-k\">thumbnail</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">href</span>\n",
+       "            <span class=\"pystac-v\">\"https://data.eodc.eu/collections/s1-alps-wetsnow/track139/20210728/WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO.png\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">type</span>\n",
+       "            <span class=\"pystac-v\">\"image/png\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">bbox</span><span class=\"pystac-l\">[] 4 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">4.069</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">43.003</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">2</span>\n",
+       "            <span class=\"pystac-v\">8.881</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">3</span>\n",
+       "            <span class=\"pystac-v\">49.0</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\"><span class=\"pystac-k\">stac_extensions</span><span class=\"pystac-l\">[] 3 items</span></summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">0</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac-extensions.github.io/sat/v1.0.0/schema.json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">1</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac-extensions.github.io/sar/v1.0.0/schema.json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">2</span>\n",
+       "            <span class=\"pystac-v\">\"https://stac-extensions.github.io/projection/v1.0.0/schema.json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li class=\"pystac-row\">\n",
+       "            <span class=\"pystac-k\">collection</span>\n",
+       "            <span class=\"pystac-v\">\"SENTINEL1_ALPS_WETSNOW\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "        </ul>\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Item id=WSM_ALPS_20210728T054318_E042N018T6_S1B_IW_SLC_027990_004296_00_ENVEO>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result_items[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We utilize odc's stac_load functionality to load the data as an xarray.DataArray. \n",
+    "\n",
+    "We need to define the coordinate reference system as well as the resolution. As the data is provided in the European Equi7 CRS, we define this accordingly. \n",
+    "\n",
+    "We then select a subset of the data by setting the x and y coordinates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "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",
+       "html[data-theme=dark],\n",
+       "body[data-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 !important;\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-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;WSM&#x27; (y: 2291, x: 3942)&gt; Size: 36MB\n",
+       "dask.array&lt;getitem, shape=(2291, 3942), dtype=float32, chunksize=(1000, 1000), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * y            (y) float64 18kB 8.596e+06 8.596e+06 ... 8.138e+06 8.138e+06\n",
+       "  * x            (x) float64 32kB -1.309e+06 -1.308e+06 ... -5.205e+05\n",
+       "    spatial_ref  int32 4B 0\n",
+       "    time         datetime64[ns] 8B 2021-07-28T05:43:18</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'>'WSM'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 2291</li><li><span class='xr-has-index'>x</span>: 3942</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-87f9722c-1ffe-40bc-a36c-4a7cb3ca035c' class='xr-array-in' type='checkbox' checked><label for='section-87f9722c-1ffe-40bc-a36c-4a7cb3ca035c' 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>dask.array&lt;chunksize=(1000, 1000), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 34.45 MiB </td>\n",
+       "                        <td> 3.81 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2291, 3942) </td>\n",
+       "                        <td> (1000, 1000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 12 chunks in 4 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"119\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"30\" x2=\"120\" y2=\"30\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" />\n",
+       "  <line x1=\"0\" y1=\"69\" x2=\"120\" y2=\"69\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"69\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"69\" />\n",
+       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"69\" />\n",
+       "  <line x1=\"91\" y1=\"0\" x2=\"91\" y2=\"69\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"69\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,69.74124809741248 0.0,69.74124809741248\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"89.741248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3942</text>\n",
+       "  <text x=\"140.000000\" y=\"34.870624\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,34.870624)\">2291</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-b46d57bb-2094-457a-884b-3b0c32fe4e17' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b46d57bb-2094-457a-884b-3b0c32fe4e17' 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'>8.596e+06 8.596e+06 ... 8.138e+06</div><input id='attrs-3d644b0c-f652-43de-b1ae-09585df10a50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d644b0c-f652-43de-b1ae-09585df10a50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b55d5985-edff-4a59-bcec-828906da3322' class='xr-var-data-in' type='checkbox'><label for='data-b55d5985-edff-4a59-bcec-828906da3322' 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>-200.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;Azimuthal_Equidistant&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],UNIT[&quot;degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Azimuthal_Equidistant&quot;],PARAMETER[&quot;false_easting&quot;,4340913.84808],PARAMETER[&quot;false_northing&quot;,4812712.92347],PARAMETER[&quot;longitude_of_center&quot;,94.0],PARAMETER[&quot;latitude_of_center&quot;,47.0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]]]</dd></dl></div><div class='xr-var-data'><pre>array([8596300., 8596100., 8595900., ..., 8138700., 8138500., 8138300.])</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'>-1.309e+06 ... -5.205e+05</div><input id='attrs-e47d5a7c-607c-4a9a-9ba6-f189d0fa6cb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e47d5a7c-607c-4a9a-9ba6-f189d0fa6cb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51703a7b-aecd-4bc7-88dc-797597c3f099' class='xr-var-data-in' type='checkbox'><label for='data-51703a7b-aecd-4bc7-88dc-797597c3f099' 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>200.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;Azimuthal_Equidistant&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],UNIT[&quot;degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Azimuthal_Equidistant&quot;],PARAMETER[&quot;false_easting&quot;,4340913.84808],PARAMETER[&quot;false_northing&quot;,4812712.92347],PARAMETER[&quot;longitude_of_center&quot;,94.0],PARAMETER[&quot;latitude_of_center&quot;,47.0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]]]</dd></dl></div><div class='xr-var-data'><pre>array([-1308700., -1308500., -1308300., ...,  -520900.,  -520700.,  -520500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-45fe56e7-08ba-45b1-a363-2a0ecca7aef5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45fe56e7-08ba-45b1-a363-2a0ecca7aef5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcdbe22b-25aa-4fa4-8579-4fe4796928e0' class='xr-var-data-in' type='checkbox'><label for='data-bcdbe22b-25aa-4fa4-8579-4fe4796928e0' 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;Azimuthal_Equidistant&quot;,BASEGEOGCRS[&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]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;unnamed&quot;,METHOD[&quot;Modified Azimuthal Equidistant&quot;,ID[&quot;EPSG&quot;,9832]],PARAMETER[&quot;False easting&quot;,4340913.84808,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,4812712.92347,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]],PARAMETER[&quot;Longitude of natural origin&quot;,94,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Latitude of natural origin&quot;,47,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]]</dd><dt><span>crs_wkt :</span></dt><dd>PROJCRS[&quot;Azimuthal_Equidistant&quot;,BASEGEOGCRS[&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]],ID[&quot;EPSG&quot;,4326]],CONVERSION[&quot;unnamed&quot;,METHOD[&quot;Modified Azimuthal Equidistant&quot;,ID[&quot;EPSG&quot;,9832]],PARAMETER[&quot;False easting&quot;,4340913.84808,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8806]],PARAMETER[&quot;False northing&quot;,4812712.92347,LENGTHUNIT[&quot;metre&quot;,1],ID[&quot;EPSG&quot;,8807]],PARAMETER[&quot;Longitude of natural origin&quot;,94,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8802]],PARAMETER[&quot;Latitude of natural origin&quot;,47,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8801]]],CS[Cartesian,2],AXIS[&quot;(E)&quot;,east,ORDER[1],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]],AXIS[&quot;(N)&quot;,north,ORDER[2],LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>projected_crs_name :</span></dt><dd>Azimuthal_Equidistant</dd><dt><span>grid_mapping_name :</span></dt><dd>azimuthal_equidistant</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>47.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>94.0</dd><dt><span>false_easting :</span></dt><dd>4340913.84808</dd><dt><span>false_northing :</span></dt><dd>4812712.92347</dd><dt><span>GeoTransform :</span></dt><dd>-1308800 200 0 8596400 0 -200</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-07-28T05:43:18</div><input id='attrs-76ac6d09-bae3-4535-932f-4468c5650023' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76ac6d09-bae3-4535-932f-4468c5650023' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22c9f983-2828-4f75-b8e0-d0cbb8750dc2' class='xr-var-data-in' type='checkbox'><label for='data-22c9f983-2828-4f75-b8e0-d0cbb8750dc2' 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;2021-07-28T05:43:18.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-68cd07c6-cc7c-4d03-bf38-2835da297837' class='xr-section-summary-in' type='checkbox'  ><label for='section-68cd07c6-cc7c-4d03-bf38-2835da297837' 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-e39a8f3c-43e9-4384-a858-890a7b554b6d' class='xr-index-data-in' type='checkbox'/><label for='index-e39a8f3c-43e9-4384-a858-890a7b554b6d' 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([8596300.0, 8596100.0, 8595900.0, 8595700.0, 8595500.0, 8595300.0,\n",
+       "       8595100.0, 8594900.0, 8594700.0, 8594500.0,\n",
+       "       ...\n",
+       "       8140100.0, 8139900.0, 8139700.0, 8139500.0, 8139300.0, 8139100.0,\n",
+       "       8138900.0, 8138700.0, 8138500.0, 8138300.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=2291))</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-a0dce495-9963-48e1-8d3e-56287ca634ce' class='xr-index-data-in' type='checkbox'/><label for='index-a0dce495-9963-48e1-8d3e-56287ca634ce' 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([-1308700.0, -1308500.0, -1308300.0, -1308100.0, -1307900.0, -1307700.0,\n",
+       "       -1307500.0, -1307300.0, -1307100.0, -1306900.0,\n",
+       "       ...\n",
+       "        -522300.0,  -522100.0,  -521900.0,  -521700.0,  -521500.0,  -521300.0,\n",
+       "        -521100.0,  -520900.0,  -520700.0,  -520500.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=3942))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ded07733-bc4a-4641-86fd-45b652233377' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ded07733-bc4a-4641-86fd-45b652233377' 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 'WSM' (y: 2291, x: 3942)> Size: 36MB\n",
+       "dask.array<getitem, shape=(2291, 3942), dtype=float32, chunksize=(1000, 1000), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * y            (y) float64 18kB 8.596e+06 8.596e+06 ... 8.138e+06 8.138e+06\n",
+       "  * x            (x) float64 32kB -1.309e+06 -1.308e+06 ... -5.205e+05\n",
+       "    spatial_ref  int32 4B 0\n",
+       "    time         datetime64[ns] 8B 2021-07-28T05:43:18"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "crs = pyproj.CRS.from_wkt(\"PROJCS[\\\"Azimuthal_Equidistant\\\",GEOGCS[\\\"WGS 84\\\",DATUM[\\\"WGS_1984\\\",SPHEROID[\\\"WGS 84\\\",6378137,298.257223563,AUTHORITY[\\\"EPSG\\\",\\\"7030\\\"]],AUTHORITY[\\\"EPSG\\\",\\\"6326\\\"]],PRIMEM[\\\"Greenwich\\\",0],UNIT[\\\"degree\\\",0.0174532925199433],AUTHORITY[\\\"EPSG\\\",\\\"4326\\\"]],PROJECTION[\\\"Azimuthal_Equidistant\\\"],PARAMETER[\\\"false_easting\\\",4340913.84808],PARAMETER[\\\"false_northing\\\",4812712.92347],PARAMETER[\\\"longitude_of_center\\\",94.0],PARAMETER[\\\"latitude_of_center\\\",47.0],UNIT[\\\"metre\\\",1,AUTHORITY[\\\"EPSG\\\",\\\"9001\\\"]]]\")\n",
+    "resolution = 200\n",
+    "# crs = pyproj.CRS(\"epsg:4326\")\n",
+    "# resolution = 0.0009\n",
+    "\n",
+    "data = stac_load(\n",
+    "    result_items, \n",
+    "    chunks={\"x\": 1000, \"y\": 1000}, \n",
+    "    bands=[\"WSM\"],\n",
+    "    crs=crs,\n",
+    "    resolution=resolution,\n",
+    "    resampling=\"nearest\",\n",
+    "    )\n",
+    "\n",
+    "wsm = data.WSM\n",
+    "\n",
+    "wsm_data = wsm.isel(time=0).sel(x=slice(-1308700, -508900), y=slice(8605500, 8135700))\n",
+    "\n",
+    "wsm_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The dataset contains certain discrete values. We use the numpy.unique functionality to list these values: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[110. 125. 200. 210. 220.  nan]\n"
+     ]
+    }
+   ],
+   "source": [
+    "unique, counts = np.unique(wsm_data, return_counts=True)\n",
+    "\n",
+    "print(unique)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The colormap for the dataset was create as defined in the metadata of the files. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wetsnow_default_color = \"0,0,0,255\"\n",
+    "wetsow_colors = {\n",
+    "  110: \"255,0,255,255\",\n",
+    "  115: \"246,246,246,255\",\n",
+    "  120: \"225,230,90,255\",\n",
+    "  125: \"241,243,109,255\",\n",
+    "  200: \"40,40,40,255\",\n",
+    "  210: \"100,100,215,255\",\n",
+    "  215: \"93,241,244,255\",\n",
+    "  220: \"25,160,35,255\",\n",
+    "  230: \"255,190,100,255\",\n",
+    "  240: \"60,60,60,255\",\n",
+    "  255: \"0,0,0,0\",\n",
+    "}\n",
+    "\n",
+    "mpl_colors = []\n",
+    "for cidx in range(0, 256):\n",
+    "    color = wetsow_colors[cidx] if cidx in wetsow_colors else wetsnow_default_color\n",
+    "    r,g,b,t = [int(x.strip())/255.0 for x in color.split(\",\")]\n",
+    "    mpl_colors.append([r, g, b, t])\n",
+    "\n",
+    "wetsnow_cmap = matplotlib.colors.ListedColormap(mpl_colors, name=\"wetsnow\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, we create a plot of the example dataset on the 28 July, 2021."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1600x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "collection_name = collection.replace(\"_\", \" \")\n",
+    "time = 0\n",
+    "day = np.datetime64(wsm['time'].values[time], \"D\")\n",
+    "\n",
+    "plt.figure(figsize=(16,10))\n",
+    "plt.imshow(wsm_data, cmap=wetsnow_cmap, vmin=0, vmax=255, interpolation=\"nearest\")\n",
+    "plt.title(f\"{collection_name} {day}\")\n",
+    "plt.axis(\"off\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}