gis/vegetation_index.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "57a212ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cubo\n",
    "import xarray as xr\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26c47140",
   "metadata": {},
   "source": [
    "# 1. Get data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2ad6dfc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/federico/.pyenv/versions/3.8.8/envs/pg8/lib/python3.8/site-packages/stackstac/prepare.py:363: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
      "  times = pd.to_datetime(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[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;landsat-c2-l2&#x27; (time: 102, band: 4, y: 2500, x: 2500)&gt;\n",
       "dask.array&lt;fetch_raster_window, shape=(102, 4, 2500, 2500), dtype=float64, chunksize=(1, 1, 1024, 1024), chunktype=numpy.ndarray&gt;\n",
       "Coordinates: (12/30)\n",
       "  * time                         (time) datetime64[ns] 2015-01-08T03:13:29.98...\n",
       "    id                           (time) &lt;U31 &#x27;LC08_L2SP_125051_20150108_02_T1...\n",
       "  * band                         (band) &lt;U5 &#x27;blue&#x27; &#x27;green&#x27; &#x27;red&#x27; &#x27;nir08&#x27;\n",
       "  * x                            (x) float64 5.114e+05 5.114e+05 ... 5.864e+05\n",
       "  * y                            (y) float64 1.46e+06 1.46e+06 ... 1.385e+06\n",
       "    landsat:correction           &lt;U4 &#x27;L2SP&#x27;\n",
       "    ...                           ...\n",
       "    title                        (band) &lt;U22 &#x27;Blue Band&#x27; ... &#x27;Near Infrared B...\n",
       "    raster:bands                 object {&#x27;scale&#x27;: 2.75e-05, &#x27;nodata&#x27;: 0, &#x27;off...\n",
       "    common_name                  (band) &lt;U5 &#x27;blue&#x27; &#x27;green&#x27; &#x27;red&#x27; &#x27;nir08&#x27;\n",
       "    center_wavelength            (band) float64 0.48 0.56 0.65 0.87\n",
       "    full_width_half_max          (band) float64 0.06 0.06 0.04 0.03\n",
       "    epsg                         &lt;U10 &#x27;EPSG:32648&#x27;\n",
       "Attributes:\n",
       "    collection:           landsat-c2-l2\n",
       "    stac:                 https://planetarycomputer.microsoft.com/api/stac/v1\n",
       "    epsg:                 EPSG:32648\n",
       "    resolution:           30\n",
       "    edge_size:            2500\n",
       "    central_lat:          12.8681\n",
       "    central_lon:          105.4509\n",
       "    central_y:            1422592.3438612917\n",
       "    central_x:            548922.3612959113\n",
       "    time_coverage_start:  2015-01-01\n",
       "    time_coverage_end:    2044-06-30</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'>'landsat-c2-l2'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 102</li><li><span class='xr-has-index'>band</span>: 4</li><li><span class='xr-has-index'>y</span>: 2500</li><li><span class='xr-has-index'>x</span>: 2500</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7e34f440-a9d5-4763-8af9-966f995ec2e4' class='xr-array-in' type='checkbox' checked><label for='section-7e34f440-a9d5-4763-8af9-966f995ec2e4' 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=(1, 1, 1024, 1024), 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> 19.00 GiB </td>\n",
       "                        <td> 8.00 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (102, 4, 2500, 2500) </td>\n",
       "                        <td> (1, 1, 1024, 1024) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 3672 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"390\" height=\"184\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"33\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"33\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" />\n",
       "  <line x1=\"1\" y1=\"0\" x2=\"1\" y2=\"25\" />\n",
       "  <line x1=\"2\" y1=\"0\" x2=\"2\" y2=\"25\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"4\" y1=\"0\" x2=\"4\" y2=\"25\" />\n",
       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"8\" y1=\"0\" x2=\"8\" y2=\"25\" />\n",
       "  <line x1=\"9\" y1=\"0\" x2=\"9\" y2=\"25\" />\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
       "  <line x1=\"13\" y1=\"0\" x2=\"13\" y2=\"25\" />\n",
       "  <line x1=\"14\" y1=\"0\" x2=\"14\" y2=\"25\" />\n",
       "  <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n",
       "  <line x1=\"16\" y1=\"0\" x2=\"16\" y2=\"25\" />\n",
       "  <line x1=\"17\" y1=\"0\" x2=\"17\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"19\" y1=\"0\" x2=\"19\" y2=\"25\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"25\" />\n",
       "  <line x1=\"21\" y1=\"0\" x2=\"21\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"23\" y1=\"0\" x2=\"23\" y2=\"25\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"25\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"28\" y1=\"0\" x2=\"28\" y2=\"25\" />\n",
       "  <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"25\" />\n",
       "  <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 33.255025095924935,0.0 33.255025095924935,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"16.627513\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >102</text>\n",
       "  <text x=\"53.255025\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,53.255025,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"103\" y1=\"0\" x2=\"117\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"103\" y1=\"49\" x2=\"117\" y2=\"64\" />\n",
       "  <line x1=\"103\" y1=\"98\" x2=\"117\" y2=\"113\" />\n",
       "  <line x1=\"103\" y1=\"120\" x2=\"117\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"103\" y1=\"0\" x2=\"103\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"106\" y1=\"3\" x2=\"106\" y2=\"123\" />\n",
       "  <line x1=\"110\" y1=\"7\" x2=\"110\" y2=\"127\" />\n",
       "  <line x1=\"114\" y1=\"11\" x2=\"114\" y2=\"131\" />\n",
       "  <line x1=\"117\" y1=\"14\" x2=\"117\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"103.0,0.0 117.9485979497544,14.948597949754403 117.9485979497544,134.9485979497544 103.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"103\" y1=\"0\" x2=\"223\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"106\" y1=\"3\" x2=\"226\" y2=\"3\" />\n",
       "  <line x1=\"110\" y1=\"7\" x2=\"230\" y2=\"7\" />\n",
       "  <line x1=\"114\" y1=\"11\" x2=\"234\" y2=\"11\" />\n",
       "  <line x1=\"117\" y1=\"14\" x2=\"237\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"103\" y1=\"0\" x2=\"117\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"152\" y1=\"0\" x2=\"167\" y2=\"14\" />\n",
       "  <line x1=\"201\" y1=\"0\" x2=\"216\" y2=\"14\" />\n",
       "  <line x1=\"223\" y1=\"0\" x2=\"237\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"103.0,0.0 223.0,0.0 237.9485979497544,14.948597949754403 117.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"117\" y1=\"14\" x2=\"237\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"117\" y1=\"64\" x2=\"237\" y2=\"64\" />\n",
       "  <line x1=\"117\" y1=\"113\" x2=\"237\" y2=\"113\" />\n",
       "  <line x1=\"117\" y1=\"134\" x2=\"237\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"117\" y1=\"14\" x2=\"117\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"167\" y1=\"14\" x2=\"167\" y2=\"134\" />\n",
       "  <line x1=\"216\" y1=\"14\" x2=\"216\" y2=\"134\" />\n",
       "  <line x1=\"237\" y1=\"14\" x2=\"237\" y2=\"134\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"117.9485979497544,14.948597949754403 237.9485979497544,14.948597949754403 237.9485979497544,134.9485979497544 117.9485979497544,134.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"177.948598\" y=\"154.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2500</text>\n",
       "  <text x=\"257.948598\" y=\"74.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,257.948598,74.948598)\">2500</text>\n",
       "  <text x=\"100.474299\" y=\"147.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,100.474299,147.474299)\">4</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-1d042e89-1dc6-46df-9e01-73077fca9b61' class='xr-section-summary-in' type='checkbox'  ><label for='section-1d042e89-1dc6-46df-9e01-73077fca9b61' class='xr-section-summary' >Coordinates: <span>(30)</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'>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'>2015-01-08T03:13:29.982468 ... 2...</div><input id='attrs-3b8784d8-e4e6-4b58-a908-4b4e4d2c5e84' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b8784d8-e4e6-4b58-a908-4b4e4d2c5e84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-febbce9c-cade-4851-9f3d-433d55bf8b33' class='xr-var-data-in' type='checkbox'><label for='data-febbce9c-cade-4851-9f3d-433d55bf8b33' 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;2015-01-08T03:13:29.982468000&#x27;, &#x27;2015-01-08T03:13:53.894685000&#x27;,\n",
       "       &#x27;2015-01-15T03:19:39.382766000&#x27;, &#x27;2015-01-24T03:13:23.531457000&#x27;,\n",
       "       &#x27;2015-01-24T03:13:47.430966000&#x27;, &#x27;2015-01-31T03:19:34.830432000&#x27;,\n",
       "       &#x27;2015-02-09T03:13:19.704636000&#x27;, &#x27;2015-02-09T03:13:43.608381000&#x27;,\n",
       "       &#x27;2015-02-16T03:19:26.145922000&#x27;, &#x27;2015-03-13T03:13:02.707654000&#x27;,\n",
       "       &#x27;2015-03-29T03:12:54.851466000&#x27;, &#x27;2015-03-29T03:13:18.759447000&#x27;,\n",
       "       &#x27;2015-04-14T03:12:49.874425000&#x27;, &#x27;2015-04-14T03:13:13.778170000&#x27;,\n",
       "       &#x27;2015-04-21T03:18:59.524650000&#x27;, &#x27;2015-06-08T03:18:50.724091000&#x27;,\n",
       "       &#x27;2015-10-30T03:19:44.058978000&#x27;, &#x27;2015-12-01T03:19:46.574861000&#x27;,\n",
       "       &#x27;2016-01-02T03:19:43.637647000&#x27;, &#x27;2016-01-11T03:13:55.076387000&#x27;,\n",
       "       &#x27;2016-02-19T03:19:30.848775000&#x27;, &#x27;2016-02-28T03:13:20.550865000&#x27;,\n",
       "       &#x27;2016-02-28T03:13:44.454611000&#x27;, &#x27;2016-03-06T03:19:30.619047000&#x27;,\n",
       "       &#x27;2016-03-31T03:13:06.338286000&#x27;, &#x27;2016-03-31T03:13:30.242032000&#x27;,\n",
       "       &#x27;2016-04-07T03:19:15.543638000&#x27;, &#x27;2016-11-10T03:13:46.324285000&#x27;,\n",
       "       &#x27;2017-01-04T03:19:49.833936000&#x27;, &#x27;2017-01-13T03:13:36.994349000&#x27;,\n",
       "       &#x27;2017-01-13T03:14:00.898095000&#x27;, &#x27;2017-01-29T03:13:30.908147000&#x27;,\n",
       "       &#x27;2017-01-29T03:13:54.816129000&#x27;, &#x27;2017-02-05T03:19:37.962610000&#x27;,\n",
       "       &#x27;2017-02-14T03:13:23.409057000&#x27;, &#x27;2017-02-14T03:13:47.308566000&#x27;,\n",
       "       &#x27;2017-03-02T03:13:17.695177000&#x27;, &#x27;2017-10-28T03:13:44.989931000&#x27;,\n",
       "       &#x27;2017-12-06T03:19:46.450403000&#x27;, &#x27;2018-01-16T03:13:29.484403000&#x27;,\n",
       "       &#x27;2018-02-01T03:13:19.623973000&#x27;, &#x27;2018-02-08T03:19:28.388754000&#x27;,\n",
       "       &#x27;2018-03-12T03:19:13.492882000&#x27;, &#x27;2018-10-31T03:13:21.498402000&#x27;,\n",
       "       &#x27;2018-10-31T03:13:45.402149000&#x27;, &#x27;2018-11-16T03:13:23.032770000&#x27;,\n",
       "       &#x27;2018-12-02T03:13:21.593729000&#x27;, &#x27;2018-12-02T03:13:45.497476000&#x27;,\n",
       "       &#x27;2018-12-18T03:13:19.185441000&#x27;, &#x27;2018-12-25T03:19:30.309284000&#x27;,\n",
       "       &#x27;2019-01-26T03:19:24.951395000&#x27;, &#x27;2019-02-04T03:13:12.734248000&#x27;,\n",
       "       &#x27;2019-02-04T03:13:36.637995000&#x27;, &#x27;2019-02-11T03:19:22.800138000&#x27;,\n",
       "       &#x27;2019-02-27T03:19:19.231836000&#x27;, &#x27;2019-04-16T03:19:05.033901000&#x27;,\n",
       "       &#x27;2019-10-25T03:20:01.460261000&#x27;, &#x27;2019-11-19T03:13:46.570936000&#x27;,\n",
       "       &#x27;2019-11-19T03:14:10.478919000&#x27;, &#x27;2019-11-26T03:19:56.829298000&#x27;,\n",
       "       &#x27;2019-12-05T03:13:45.794081000&#x27;, &#x27;2019-12-05T03:14:09.697829000&#x27;,\n",
       "       &#x27;2019-12-12T03:19:55.878939000&#x27;, &#x27;2019-12-28T03:19:52.160815000&#x27;,\n",
       "       &#x27;2020-01-06T03:13:39.004177000&#x27;, &#x27;2020-01-06T03:14:02.907923000&#x27;,\n",
       "       &#x27;2020-01-13T03:19:48.635803000&#x27;, &#x27;2020-01-22T03:13:35.504675000&#x27;,\n",
       "       &#x27;2020-01-22T03:13:59.408422000&#x27;, &#x27;2020-02-07T03:13:30.227052000&#x27;,\n",
       "       &#x27;2020-02-07T03:13:54.139272000&#x27;, &#x27;2020-02-23T03:13:26.817603000&#x27;,\n",
       "       &#x27;2020-02-23T03:13:50.721351000&#x27;, &#x27;2020-03-26T03:13:12.319739000&#x27;,\n",
       "       &#x27;2020-03-26T03:13:36.227724000&#x27;, &#x27;2020-11-21T03:13:45.792619000&#x27;,\n",
       "       &#x27;2020-12-30T03:19:55.118484000&#x27;, &#x27;2021-01-08T03:13:40.750169000&#x27;,\n",
       "       &#x27;2021-01-08T03:14:04.653916000&#x27;, &#x27;2021-01-15T03:19:48.153029000&#x27;,\n",
       "       &#x27;2021-01-31T03:19:45.579618000&#x27;, &#x27;2021-03-04T03:19:35.262993000&#x27;,\n",
       "       &#x27;2021-03-13T03:13:19.214301000&#x27;, &#x27;2021-03-13T03:13:43.118049000&#x27;,\n",
       "       &#x27;2021-12-10T03:13:48.214587000&#x27;, &#x27;2021-12-10T03:14:12.126807000&#x27;,\n",
       "       &#x27;2022-01-11T03:14:04.825171000&#x27;, &#x27;2022-01-18T03:19:50.106658000&#x27;,\n",
       "       &#x27;2022-01-27T03:13:35.312364000&#x27;, &#x27;2022-04-08T03:19:25.334767000&#x27;,\n",
       "       &#x27;2022-06-20T03:13:39.396245000&#x27;, &#x27;2022-11-02T03:20:16.401626000&#x27;,\n",
       "       &#x27;2022-12-13T03:13:57.297286000&#x27;, &#x27;2022-12-13T03:14:21.205269000&#x27;,\n",
       "       &#x27;2022-12-20T03:20:02.551373000&#x27;, &#x27;2023-01-30T03:13:49.792150000&#x27;,\n",
       "       &#x27;2023-02-06T03:19:59.828665000&#x27;, &#x27;2023-03-10T03:19:36.398519000&#x27;,\n",
       "       &#x27;2023-03-19T03:13:21.687104000&#x27;, &#x27;2023-03-19T03:13:45.590852000&#x27;,\n",
       "       &#x27;2023-03-26T03:19:27.417316000&#x27;, &#x27;2023-05-22T03:12:44.346558000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U31</div><div class='xr-var-preview xr-preview'>&#x27;LC08_L2SP_125051_20150108_02_T1...</div><input id='attrs-2214c65d-708c-4923-8485-0818b78f3352' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2214c65d-708c-4923-8485-0818b78f3352' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1eb56ecd-fb73-417a-9f97-4d58aff4c8fb' class='xr-var-data-in' type='checkbox'><label for='data-1eb56ecd-fb73-417a-9f97-4d58aff4c8fb' 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;LC08_L2SP_125051_20150108_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20150108_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20150115_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20150124_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20150124_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20150131_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20150209_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20150209_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20150216_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20150313_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20150329_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20150329_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20150414_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20150414_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20150421_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20150608_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20151030_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20151201_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20160102_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20160111_02_T1&#x27;,\n",
       "...\n",
       "       &#x27;LC08_L2SP_125051_20210313_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20210313_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20211210_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20211210_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20220111_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20220118_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20220127_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20220408_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20220620_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20221102_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20221213_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20221213_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20221220_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20230130_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20230206_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20230310_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20230319_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125052_20230319_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_126051_20230326_02_T1&#x27;,\n",
       "       &#x27;LC08_L2SP_125051_20230522_02_T1&#x27;], dtype=&#x27;&lt;U31&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;blue&#x27; &#x27;green&#x27; &#x27;red&#x27; &#x27;nir08&#x27;</div><input id='attrs-25554e3d-4e98-4f2d-a917-800ceed88e28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25554e3d-4e98-4f2d-a917-800ceed88e28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71c1772f-80e1-4aef-9aeb-5eb68cba9c86' class='xr-var-data-in' type='checkbox'><label for='data-71c1772f-80e1-4aef-9aeb-5eb68cba9c86' 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;blue&#x27;, &#x27;green&#x27;, &#x27;red&#x27;, &#x27;nir08&#x27;], dtype=&#x27;&lt;U5&#x27;)</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'>5.114e+05 5.114e+05 ... 5.864e+05</div><input id='attrs-ee69f04f-ccf2-442b-8c03-3012dcb4bfad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee69f04f-ccf2-442b-8c03-3012dcb4bfad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7ba18da-5271-4e90-b40c-749d019be317' class='xr-var-data-in' type='checkbox'><label for='data-b7ba18da-5271-4e90-b40c-749d019be317' 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([511410., 511440., 511470., ..., 586320., 586350., 586380.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46e+06 1.46e+06 ... 1.385e+06</div><input id='attrs-fbbdd2ab-c4d7-49eb-b20b-fefac275c31e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbbdd2ab-c4d7-49eb-b20b-fefac275c31e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e60ae89-9d5a-481d-a2ef-ca04ddee9fa0' class='xr-var-data-in' type='checkbox'><label for='data-4e60ae89-9d5a-481d-a2ef-ca04ddee9fa0' 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([1460100., 1460070., 1460040., ..., 1385190., 1385160., 1385130.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:correction</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;L2SP&#x27;</div><input id='attrs-ec9c9445-a988-4fd6-86d8-425d97a591bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec9c9445-a988-4fd6-86d8-425d97a591bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26fffd9f-db23-478f-b1a4-8c8455f48f39' class='xr-var-data-in' type='checkbox'><label for='data-26fffd9f-db23-478f-b1a4-8c8455f48f39' 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;L2SP&#x27;, dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.56 3.72 0.0 ... 0.63 4.61 4.48</div><input id='attrs-3098d234-a35c-46da-96bc-c15f7bcee141' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3098d234-a35c-46da-96bc-c15f7bcee141' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82c34cce-7403-494c-b137-e80b30c722c8' class='xr-var-data-in' type='checkbox'><label for='data-82c34cce-7403-494c-b137-e80b30c722c8' 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([4.56, 3.72, 0.  , 0.6 , 0.56, 0.12, 5.4 , 0.09, 0.61, 8.61, 1.45,\n",
       "       1.42, 0.46, 8.27, 0.23, 0.32, 0.11, 5.67, 0.  , 6.66, 0.23, 1.98,\n",
       "       2.14, 5.81, 1.47, 6.92, 2.93, 1.31, 4.2 , 8.86, 7.53, 6.8 , 2.57,\n",
       "       3.76, 2.06, 0.52, 1.34, 3.45, 1.64, 1.74, 0.04, 4.11, 0.21, 0.01,\n",
       "       5.5 , 6.7 , 2.64, 5.42, 4.55, 5.76, 8.23, 2.01, 8.03, 0.  , 0.3 ,\n",
       "       8.86, 1.67, 3.46, 1.9 , 0.28, 8.69, 5.83, 4.31, 0.07, 0.16, 0.65,\n",
       "       0.  , 0.11, 0.98, 8.88, 2.03, 1.14, 0.23, 7.32, 5.76, 7.59, 1.15,\n",
       "       7.  , 3.19, 2.35, 6.41, 8.22, 0.04, 1.04, 1.  , 0.09, 8.5 , 0.04,\n",
       "       0.83, 8.77, 3.48, 0.16, 3.19, 8.22, 0.01, 5.85, 8.98, 0.35, 0.41,\n",
       "       0.63, 4.61, 4.48])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>description</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U71</div><div class='xr-var-preview xr-preview'>&#x27;Collection 2 Level-2 Blue Band ...</div><input id='attrs-6d70d1b4-879d-4409-9cab-07468e6c3974' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d70d1b4-879d-4409-9cab-07468e6c3974' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd6bad07-37ef-48b1-a133-9e8840981e82' class='xr-var-data-in' type='checkbox'><label for='data-cd6bad07-37ef-48b1-a133-9e8840981e82' 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;Collection 2 Level-2 Blue Band (SR_B2) Surface Reflectance&#x27;,\n",
       "       &#x27;Collection 2 Level-2 Green Band (SR_B3) Surface Reflectance&#x27;,\n",
       "       &#x27;Collection 2 Level-2 Red Band (SR_B4) Surface Reflectance&#x27;,\n",
       "       &#x27;Collection 2 Level-2 Near Infrared Band 0.8 (SR_B5) Surface Reflectance&#x27;],\n",
       "      dtype=&#x27;&lt;U71&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:scene_id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;LC81250512015008LGN01&#x27; ... &#x27;LC8...</div><input id='attrs-ede0b7ba-43f4-4826-afc3-9e1f6a6054c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ede0b7ba-43f4-4826-afc3-9e1f6a6054c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-501634a7-1fa8-42ad-aa57-fc114d1e5f74' class='xr-var-data-in' type='checkbox'><label for='data-501634a7-1fa8-42ad-aa57-fc114d1e5f74' 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;LC81250512015008LGN01&#x27;, &#x27;LC81250522015008LGN01&#x27;,\n",
       "       &#x27;LC81260512015015LGN01&#x27;, &#x27;LC81250512015024LGN01&#x27;,\n",
       "       &#x27;LC81250522015024LGN01&#x27;, &#x27;LC81260512015031LGN02&#x27;,\n",
       "       &#x27;LC81250512015040LGN02&#x27;, &#x27;LC81250522015040LGN02&#x27;,\n",
       "       &#x27;LC81260512015047LGN01&#x27;, &#x27;LC81250512015072LGN01&#x27;,\n",
       "       &#x27;LC81250512015088LGN01&#x27;, &#x27;LC81250522015088LGN01&#x27;,\n",
       "       &#x27;LC81250512015104LGN01&#x27;, &#x27;LC81250522015104LGN01&#x27;,\n",
       "       &#x27;LC81260512015111LGN02&#x27;, &#x27;LC81260512015159LGN01&#x27;,\n",
       "       &#x27;LC81260512015303LGN02&#x27;, &#x27;LC81260512015335LGN01&#x27;,\n",
       "       &#x27;LC81260512016002LGN02&#x27;, &#x27;LC81250522016011LGN02&#x27;,\n",
       "       &#x27;LC81260512016050LGN01&#x27;, &#x27;LC81250512016059LGN02&#x27;,\n",
       "       &#x27;LC81250522016059LGN02&#x27;, &#x27;LC81260512016066LGN01&#x27;,\n",
       "       &#x27;LC81250512016091LGN02&#x27;, &#x27;LC81250522016091LGN02&#x27;,\n",
       "       &#x27;LC81260512016098LGN02&#x27;, &#x27;LC81250512016315LGN01&#x27;,\n",
       "       &#x27;LC81260512017004LGN01&#x27;, &#x27;LC81250512017013LGN01&#x27;,\n",
       "       &#x27;LC81250522017013LGN01&#x27;, &#x27;LC81250512017029LGN00&#x27;,\n",
       "       &#x27;LC81250522017029LGN00&#x27;, &#x27;LC81260512017036LGN00&#x27;,\n",
       "       &#x27;LC81250512017045LGN00&#x27;, &#x27;LC81250522017045LGN00&#x27;,\n",
       "       &#x27;LC81250512017061LGN00&#x27;, &#x27;LC81250512017301LGN00&#x27;,\n",
       "       &#x27;LC81260512017340LGN00&#x27;, &#x27;LC81250512018016LGN00&#x27;,\n",
       "...\n",
       "       &#x27;LC81260512019346LGN00&#x27;, &#x27;LC81260512019362LGN00&#x27;,\n",
       "       &#x27;LC81250512020006LGN00&#x27;, &#x27;LC81250522020006LGN00&#x27;,\n",
       "       &#x27;LC81260512020013LGN00&#x27;, &#x27;LC81250512020022LGN00&#x27;,\n",
       "       &#x27;LC81250522020022LGN00&#x27;, &#x27;LC81250512020038LGN00&#x27;,\n",
       "       &#x27;LC81250522020038LGN00&#x27;, &#x27;LC81250512020054LGN00&#x27;,\n",
       "       &#x27;LC81250522020054LGN00&#x27;, &#x27;LC81250512020086LGN00&#x27;,\n",
       "       &#x27;LC81250522020086LGN00&#x27;, &#x27;LC81250512020326LGN00&#x27;,\n",
       "       &#x27;LC81260512020365LGN00&#x27;, &#x27;LC81250512021008LGN00&#x27;,\n",
       "       &#x27;LC81250522021008LGN00&#x27;, &#x27;LC81260512021015LGN00&#x27;,\n",
       "       &#x27;LC81260512021031LGN00&#x27;, &#x27;LC81260512021063LGN00&#x27;,\n",
       "       &#x27;LC81250512021072LGN00&#x27;, &#x27;LC81250522021072LGN00&#x27;,\n",
       "       &#x27;LC81250512021344LGN00&#x27;, &#x27;LC81250522021344LGN00&#x27;,\n",
       "       &#x27;LC81250522022011LGN00&#x27;, &#x27;LC81260512022018LGN00&#x27;,\n",
       "       &#x27;LC81250512022027LGN00&#x27;, &#x27;LC81260512022098LGN00&#x27;,\n",
       "       &#x27;LC81250512022171LGN00&#x27;, &#x27;LC81260512022306LGN00&#x27;,\n",
       "       &#x27;LC81250512022347LGN00&#x27;, &#x27;LC81250522022347LGN00&#x27;,\n",
       "       &#x27;LC81260512022354LGN00&#x27;, &#x27;LC81250512023030LGN00&#x27;,\n",
       "       &#x27;LC81260512023037LGN00&#x27;, &#x27;LC81260512023069LGN00&#x27;,\n",
       "       &#x27;LC81250512023078LGN00&#x27;, &#x27;LC81250522023078LGN00&#x27;,\n",
       "       &#x27;LC81260512023085LGN00&#x27;, &#x27;LC81250512023142LGN00&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:collection_category</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;T1&#x27;</div><input id='attrs-dc3e7efb-2d76-4568-8f76-c891acaecb2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc3e7efb-2d76-4568-8f76-c891acaecb2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-533fbd4f-ae9d-4ded-9995-634d7312e559' class='xr-var-data-in' type='checkbox'><label for='data-533fbd4f-ae9d-4ded-9995-634d7312e559' 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;T1&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>created</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U27</div><div class='xr-var-preview xr-preview'>&#x27;2022-05-06T17:48:57.778376Z&#x27; .....</div><input id='attrs-36061b9c-23a3-4169-856f-832138d1ec25' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36061b9c-23a3-4169-856f-832138d1ec25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3c39a35-68ca-42e5-bc44-0d4e26c5b26e' class='xr-var-data-in' type='checkbox'><label for='data-d3c39a35-68ca-42e5-bc44-0d4e26c5b26e' 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;2022-05-06T17:48:57.778376Z&#x27;, &#x27;2022-05-06T17:49:01.560940Z&#x27;,\n",
       "       &#x27;2022-05-06T18:01:03.737320Z&#x27;, &#x27;2022-05-06T17:48:57.935455Z&#x27;,\n",
       "       &#x27;2022-05-06T17:49:01.705714Z&#x27;, &#x27;2022-05-06T18:01:03.894038Z&#x27;,\n",
       "       &#x27;2022-05-06T17:48:58.115638Z&#x27;, &#x27;2022-05-06T17:49:01.844285Z&#x27;,\n",
       "       &#x27;2022-05-06T18:01:04.232460Z&#x27;, &#x27;2022-05-06T17:48:58.460087Z&#x27;,\n",
       "       &#x27;2022-05-06T17:48:58.628214Z&#x27;, &#x27;2022-05-06T17:49:02.345564Z&#x27;,\n",
       "       &#x27;2022-05-06T17:48:58.788797Z&#x27;, &#x27;2022-05-06T17:49:02.496635Z&#x27;,\n",
       "       &#x27;2022-05-06T18:01:04.726512Z&#x27;, &#x27;2022-05-06T18:01:05.280998Z&#x27;,\n",
       "       &#x27;2022-05-06T18:01:06.738600Z&#x27;, &#x27;2022-05-06T18:01:07.074241Z&#x27;,\n",
       "       &#x27;2022-05-06T17:37:56.044594Z&#x27;, &#x27;2022-05-06T18:05:48.145448Z&#x27;,\n",
       "       &#x27;2022-05-06T17:37:56.723675Z&#x27;, &#x27;2022-05-06T18:05:45.161239Z&#x27;,\n",
       "       &#x27;2022-05-06T18:05:48.444870Z&#x27;, &#x27;2022-05-06T17:37:56.915694Z&#x27;,\n",
       "       &#x27;2022-05-06T18:05:45.423722Z&#x27;, &#x27;2022-05-06T18:05:48.793814Z&#x27;,\n",
       "       &#x27;2022-05-06T17:37:57.376840Z&#x27;, &#x27;2022-05-06T18:05:47.468782Z&#x27;,\n",
       "       &#x27;2022-05-06T17:19:23.934554Z&#x27;, &#x27;2022-05-06T17:33:50.084128Z&#x27;,\n",
       "       &#x27;2022-05-06T17:33:53.621772Z&#x27;, &#x27;2022-05-06T17:33:50.294451Z&#x27;,\n",
       "       &#x27;2022-05-06T17:33:53.767995Z&#x27;, &#x27;2022-05-06T17:19:24.210497Z&#x27;,\n",
       "       &#x27;2022-05-06T17:33:50.439863Z&#x27;, &#x27;2022-05-06T17:33:53.945270Z&#x27;,\n",
       "       &#x27;2022-05-06T17:33:50.570209Z&#x27;, &#x27;2022-05-06T17:33:52.831896Z&#x27;,\n",
       "       &#x27;2022-05-06T17:19:27.206240Z&#x27;, &#x27;2022-05-06T16:57:40.819926Z&#x27;,\n",
       "...\n",
       "       &#x27;2022-05-06T17:13:15.692156Z&#x27;, &#x27;2022-05-06T17:13:19.866924Z&#x27;,\n",
       "       &#x27;2022-05-06T17:14:35.601267Z&#x27;, &#x27;2022-05-06T17:13:15.852465Z&#x27;,\n",
       "       &#x27;2022-05-06T17:13:20.026116Z&#x27;, &#x27;2022-05-06T17:13:15.997212Z&#x27;,\n",
       "       &#x27;2022-05-06T17:13:20.174052Z&#x27;, &#x27;2022-05-06T17:13:16.153483Z&#x27;,\n",
       "       &#x27;2022-05-06T17:13:20.337980Z&#x27;, &#x27;2022-05-06T17:13:16.599372Z&#x27;,\n",
       "       &#x27;2022-05-06T17:13:20.703780Z&#x27;, &#x27;2022-05-06T17:13:19.386319Z&#x27;,\n",
       "       &#x27;2022-05-06T17:14:40.403202Z&#x27;, &#x27;2022-05-06T18:05:19.486565Z&#x27;,\n",
       "       &#x27;2022-05-06T18:05:33.437092Z&#x27;, &#x27;2022-05-06T17:48:14.300777Z&#x27;,\n",
       "       &#x27;2022-05-06T17:48:14.823497Z&#x27;, &#x27;2022-05-06T17:48:16.848377Z&#x27;,\n",
       "       &#x27;2022-05-06T18:05:21.479595Z&#x27;, &#x27;2022-05-06T18:05:36.677896Z&#x27;,\n",
       "       &#x27;2022-05-06T18:05:30.794557Z&#x27;, &#x27;2022-05-06T18:05:47.511081Z&#x27;,\n",
       "       &#x27;2022-05-06T17:47:26.164585Z&#x27;, &#x27;2022-05-06T17:29:45.613927Z&#x27;,\n",
       "       &#x27;2022-05-06T17:47:17.009764Z&#x27;, &#x27;2022-05-06T17:29:50.154568Z&#x27;,\n",
       "       &#x27;2022-07-15T09:16:01.132564Z&#x27;, &#x27;2022-11-24T05:30:15.167806Z&#x27;,\n",
       "       &#x27;2023-01-06T05:39:20.534913Z&#x27;, &#x27;2023-01-06T05:39:21.101951Z&#x27;,\n",
       "       &#x27;2023-01-03T05:25:27.387763Z&#x27;, &#x27;2023-02-18T05:41:07.793470Z&#x27;,\n",
       "       &#x27;2023-02-21T05:32:22.952097Z&#x27;, &#x27;2023-03-28T20:41:01.330024Z&#x27;,\n",
       "       &#x27;2023-03-28T20:40:46.829520Z&#x27;, &#x27;2023-03-28T20:40:47.566152Z&#x27;,\n",
       "       &#x27;2023-04-08T09:14:14.316831Z&#x27;, &#x27;2023-06-04T09:26:25.717075Z&#x27;],\n",
       "      dtype=&#x27;&lt;U27&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>instruments</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;tirs&#x27;, &#x27;oli&#x27;}</div><input id='attrs-b1efa0c9-f86e-4151-a5ea-c170efd0060e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b1efa0c9-f86e-4151-a5ea-c170efd0060e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08952e7e-55cb-4406-9a2c-afc5a446fb65' class='xr-var-data-in' type='checkbox'><label for='data-08952e7e-55cb-4406-9a2c-afc5a446fb65' 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;tirs&#x27;, &#x27;oli&#x27;}, dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gsd</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>30</div><input id='attrs-bd372290-e2a3-4be1-8ec8-d61011e18d19' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd372290-e2a3-4be1-8ec8-d61011e18d19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ee2d61a-dad1-4de4-919f-32e00929ef01' class='xr-var-data-in' type='checkbox'><label for='data-6ee2d61a-dad1-4de4-919f-32e00929ef01' 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(30)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:sun_azimuth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>143.3 142.2 141.6 ... 110.4 69.32</div><input id='attrs-0c4d91c6-023d-4db3-8052-9624c2d26cda' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c4d91c6-023d-4db3-8052-9624c2d26cda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d32f31b7-13df-466e-ab60-d9712e39b2e3' class='xr-var-data-in' type='checkbox'><label for='data-d32f31b7-13df-466e-ab60-d9712e39b2e3' 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([143.30653334, 142.15532914, 141.56963468, 139.0051761 ,\n",
       "       137.71730949, 136.7682899 , 133.57962018, 132.06043465,\n",
       "       130.82955611, 118.63795992, 108.295698  , 105.50409595,\n",
       "        95.977964  ,  92.82648998,  90.28126969,  64.01568698,\n",
       "       141.39270501, 147.7061173 , 144.65846674, 141.49227159,\n",
       "       129.7117322 , 125.65691607, 123.72900621, 122.13275496,\n",
       "       106.34473798, 103.4680853 , 100.99900684, 145.15246107,\n",
       "       144.10840217, 141.98808943, 140.79967156, 137.29630354,\n",
       "       135.93906014, 134.88907934, 131.47076816, 129.84721508,\n",
       "       124.30222621, 140.83453216, 147.73591769, 141.233402  ,\n",
       "       136.34847744, 133.85813998, 119.06711396, 141.80141589,\n",
       "       140.13821206, 146.16902754, 147.67425514, 146.50780639,\n",
       "       146.89316559, 145.97304243, 138.35771404, 135.37043064,\n",
       "       133.93395925, 132.79013759, 125.96148538,  94.33413664,\n",
       "       139.3836037 , 146.77176508, 145.46849418, 147.53324604,\n",
       "       147.81380356, 146.66662695, 147.55679021, 145.62966901,\n",
       "       143.86240547, 142.72369726, 142.20157703, 139.73165983,\n",
       "       138.4674006 , 134.45818003, 132.97542413, 127.98213012,\n",
       "       126.1767359 , 109.91152073, 107.17865707, 147.11781752,\n",
       "       145.13616402, 143.24175922, 142.08754772, 141.48532422,\n",
       "       136.65603473, 123.31809788, 118.3981548 , 116.07589339,\n",
       "       147.6444617 , 146.52467512, 141.40908044, 140.74030495,\n",
       "       138.05421518, 100.57050049,  62.93795321, 142.76292673,\n",
       "       147.50650152, 146.39638713, 146.81091637, 137.17536732,\n",
       "       134.75421002, 120.38542068, 115.06162932, 112.56776729,\n",
       "       110.42775123,  69.32356732])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>proj:epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-f2138677-c94a-4b4b-81e1-83c9a2540979' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f2138677-c94a-4b4b-81e1-83c9a2540979' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-321e7ba1-967e-4486-bdfc-b1515c6be7ff' class='xr-var-data-in' type='checkbox'><label for='data-321e7ba1-967e-4486-bdfc-b1515c6be7ff' 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(32648)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;2&#x27;</div><input id='attrs-d503e11b-bdb9-4e01-bbe5-ce446dd1ffe3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d503e11b-bdb9-4e01-bbe5-ce446dd1ffe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda64c59-cd39-44a2-8e25-dcde34f953a9' class='xr-var-data-in' type='checkbox'><label for='data-dda64c59-cd39-44a2-8e25-dcde34f953a9' 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;2&#x27;, dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>platform</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;landsat-8&#x27;</div><input id='attrs-26b0306c-060e-45a1-93ab-f3350221f9c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26b0306c-060e-45a1-93ab-f3350221f9c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e622d0a4-dd4e-4c2f-ba89-b061969c74a5' class='xr-var-data-in' type='checkbox'><label for='data-e622d0a4-dd4e-4c2f-ba89-b061969c74a5' 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;landsat-8&#x27;, dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:sun_elevation</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.11 47.13 46.54 ... 61.57 65.58</div><input id='attrs-1a6bd084-e4b3-4552-88c7-1354104a7c7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a6bd084-e4b3-4552-88c7-1354104a7c7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13332536-60e5-4bbd-b880-30d1455e26a9' class='xr-var-data-in' type='checkbox'><label for='data-13332536-60e5-4bbd-b880-30d1455e26a9' 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([46.11242919, 47.1342578 , 46.54275521, 47.52395237, 48.46289101,\n",
       "       48.59917876, 50.327049  , 51.15388366, 51.89468552, 58.29327027,\n",
       "       62.14032686, 62.35799927, 64.91166068, 64.81160817, 65.63705932,\n",
       "       64.383405  , 56.24125109, 49.00888651, 45.99220225, 47.26273795,\n",
       "       52.58068578, 54.85776614, 55.50608495, 56.69947419, 62.77479963,\n",
       "       62.94199458, 64.06524167, 53.37681705, 46.02795545, 46.44424641,\n",
       "       47.44104831, 48.37118376, 49.27597107, 49.63841593, 51.57272006,\n",
       "       52.35343235, 55.57168489, 56.62588899, 48.09614033, 46.65478224,\n",
       "       48.82510971, 50.18058312, 58.11482085, 55.89473953, 56.88337769,\n",
       "       52.02167683, 48.75931718, 49.85695143, 46.62531522, 46.14577213,\n",
       "       47.79547846, 49.31706114, 50.18174439, 50.75472077, 54.63808764,\n",
       "       65.19091648, 57.5141482 , 51.46748395, 52.54888795, 49.98432031,\n",
       "       48.35458724, 49.45476044, 47.35289861, 46.09073758, 46.0693627 ,\n",
       "       47.10096489, 46.4061736 , 47.27512888, 48.22838782, 49.90915438,\n",
       "       50.75490756, 53.59682467, 54.29911449, 61.7183078 , 61.97734583,\n",
       "       50.8559833 , 46.03004601, 46.16697902, 47.18715365, 46.62149898,\n",
       "       48.73585443, 56.13928271, 58.50138737, 58.97453707, 47.54269631,\n",
       "       48.64065388, 47.3186018 , 46.88538379, 48.04101727, 64.16220079,\n",
       "       63.81174492, 55.48516556, 47.21478678, 48.31041156, 46.52738723,\n",
       "       48.49316652, 49.78113388, 57.59627878, 59.90345586, 60.2934085 ,\n",
       "       61.56721364, 65.58349693])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>view:off_nadir</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-10a4e2db-21a7-42a6-8687-7b0ed5d59d60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10a4e2db-21a7-42a6-8687-7b0ed5d59d60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6df02a4b-237c-4606-b301-d92386eb4bd3' class='xr-var-data-in' type='checkbox'><label for='data-6df02a4b-237c-4606-b301-d92386eb4bd3' 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(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_path</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;125&#x27; &#x27;125&#x27; &#x27;126&#x27; ... &#x27;126&#x27; &#x27;125&#x27;</div><input id='attrs-064dccbb-6ed5-4850-aa78-e1a47482b73f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-064dccbb-6ed5-4850-aa78-e1a47482b73f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c30db38-69c6-4666-8a8f-ff3eff13b04c' class='xr-var-data-in' type='checkbox'><label for='data-6c30db38-69c6-4666-8a8f-ff3eff13b04c' 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;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;126&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;126&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;126&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;, &#x27;126&#x27;, &#x27;126&#x27;, &#x27;125&#x27;,\n",
       "       &#x27;125&#x27;, &#x27;126&#x27;, &#x27;125&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:wrs_row</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;051&#x27; &#x27;052&#x27; &#x27;051&#x27; ... &#x27;051&#x27; &#x27;051&#x27;</div><input id='attrs-718c44a9-7d56-4320-86aa-cb80501a77e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-718c44a9-7d56-4320-86aa-cb80501a77e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efc23bb9-4e0a-4736-89ac-94d9430547a0' class='xr-var-data-in' type='checkbox'><label for='data-efc23bb9-4e0a-4736-89ac-94d9430547a0' 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;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;052&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;, &#x27;051&#x27;,\n",
       "       &#x27;052&#x27;, &#x27;051&#x27;, &#x27;051&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:collection_number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;02&#x27;</div><input id='attrs-46b7f71d-6fc1-41af-b60b-a145274673fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46b7f71d-6fc1-41af-b60b-a145274673fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc606650-8a56-47c2-99a4-7ba455a24e6e' class='xr-var-data-in' type='checkbox'><label for='data-cc606650-8a56-47c2-99a4-7ba455a24e6e' 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;02&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>landsat:cloud_cover_land</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.56 3.72 0.0 ... 0.63 4.61 4.48</div><input id='attrs-60973aee-2611-4cae-8c22-4ce0b0c2e112' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60973aee-2611-4cae-8c22-4ce0b0c2e112' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b516dc0-bed1-407e-b761-55bf867c0a34' class='xr-var-data-in' type='checkbox'><label for='data-2b516dc0-bed1-407e-b761-55bf867c0a34' 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([4.56, 3.72, 0.  , 0.6 , 0.56, 0.12, 5.4 , 0.09, 0.61, 8.61, 1.45,\n",
       "       1.42, 0.46, 8.26, 0.23, 0.32, 0.11, 5.67, 0.  , 6.66, 0.23, 1.98,\n",
       "       2.14, 5.81, 1.47, 6.92, 2.93, 1.31, 4.2 , 8.86, 7.53, 6.8 , 2.57,\n",
       "       3.76, 2.06, 0.52, 1.34, 3.45, 1.64, 1.74, 0.04, 4.11, 0.21, 0.01,\n",
       "       5.5 , 6.7 , 2.64, 5.42, 4.55, 5.76, 8.23, 2.01, 8.03, 0.  , 0.3 ,\n",
       "       8.86, 1.67, 3.46, 1.9 , 0.28, 8.69, 5.83, 4.31, 0.07, 0.16, 0.65,\n",
       "       0.  , 0.11, 0.98, 8.88, 2.03, 1.14, 0.23, 7.32, 5.75, 7.59, 1.15,\n",
       "       7.  , 3.19, 2.35, 6.41, 8.22, 0.04, 1.04, 1.  , 0.09, 8.5 , 0.04,\n",
       "       0.83, 8.77, 3.48, 0.16, 3.19, 8.22, 0.01, 5.85, 8.98, 0.35, 0.41,\n",
       "       0.63, 4.61, 4.48])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sci:doi</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U16</div><div class='xr-var-preview xr-preview'>&#x27;10.5066/P9OGBGM6&#x27;</div><input id='attrs-472e24ee-d3fd-43c1-9028-b9df7c8c93a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-472e24ee-d3fd-43c1-9028-b9df7c8c93a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd9ec2fc-4bc6-46ad-8b8a-67223723b6f1' class='xr-var-data-in' type='checkbox'><label for='data-cd9ec2fc-4bc6-46ad-8b8a-67223723b6f1' 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;10.5066/P9OGBGM6&#x27;, dtype=&#x27;&lt;U16&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>title</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U22</div><div class='xr-var-preview xr-preview'>&#x27;Blue Band&#x27; ... &#x27;Near Infrared B...</div><input id='attrs-54081de2-1d9d-471f-a4c0-0322b5751f15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54081de2-1d9d-471f-a4c0-0322b5751f15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42d63981-7c53-479c-8739-3b7af716c28f' class='xr-var-data-in' type='checkbox'><label for='data-42d63981-7c53-479c-8739-3b7af716c28f' 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;Blue Band&#x27;, &#x27;Green Band&#x27;, &#x27;Red Band&#x27;, &#x27;Near Infrared Band 0.8&#x27;],\n",
       "      dtype=&#x27;&lt;U22&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raster:bands</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>{&#x27;scale&#x27;: 2.75e-05, &#x27;nodata&#x27;: 0,...</div><input id='attrs-690d56be-89bc-4174-930e-f5c4af725b53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-690d56be-89bc-4174-930e-f5c4af725b53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af8122da-ac60-4596-83af-8614c2c086b7' class='xr-var-data-in' type='checkbox'><label for='data-af8122da-ac60-4596-83af-8614c2c086b7' 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;scale&#x27;: 2.75e-05, &#x27;nodata&#x27;: 0, &#x27;offset&#x27;: -0.2, &#x27;data_type&#x27;: &#x27;uint16&#x27;, &#x27;spatial_resolution&#x27;: 30},\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>common_name</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>&lt;U5</div><div class='xr-var-preview xr-preview'>&#x27;blue&#x27; &#x27;green&#x27; &#x27;red&#x27; &#x27;nir08&#x27;</div><input id='attrs-73a01caf-b9d6-4802-8d57-7dc22ad94589' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73a01caf-b9d6-4802-8d57-7dc22ad94589' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e90fcf4-50ee-48e1-be06-49f1616db022' class='xr-var-data-in' type='checkbox'><label for='data-2e90fcf4-50ee-48e1-be06-49f1616db022' 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;blue&#x27;, &#x27;green&#x27;, &#x27;red&#x27;, &#x27;nir08&#x27;], dtype=&#x27;&lt;U5&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>center_wavelength</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.48 0.56 0.65 0.87</div><input id='attrs-3fc62859-7053-41c5-9f0e-f07367ec167a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fc62859-7053-41c5-9f0e-f07367ec167a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28e6e78d-9c9d-4510-a9d8-c4fba1473a33' class='xr-var-data-in' type='checkbox'><label for='data-28e6e78d-9c9d-4510-a9d8-c4fba1473a33' 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([0.48, 0.56, 0.65, 0.87])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>full_width_half_max</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.06 0.06 0.04 0.03</div><input id='attrs-dcbd7fff-c282-4453-88c1-3e180c099cfe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dcbd7fff-c282-4453-88c1-3e180c099cfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b1432d1-ec16-4c93-90af-eb0bee6cb2e6' class='xr-var-data-in' type='checkbox'><label for='data-4b1432d1-ec16-4c93-90af-eb0bee6cb2e6' 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([0.06, 0.06, 0.04, 0.03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;EPSG:32648&#x27;</div><input id='attrs-3a984f4f-52fe-40bb-a1a9-12e61dd80281' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a984f4f-52fe-40bb-a1a9-12e61dd80281' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b264e26-7ede-447c-ac5c-99dddceea49f' class='xr-var-data-in' type='checkbox'><label for='data-2b264e26-7ede-447c-ac5c-99dddceea49f' 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;EPSG:32648&#x27;, dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c7592c34-f258-4980-8d5d-11f4180e6937' class='xr-section-summary-in' type='checkbox'  ><label for='section-c7592c34-f258-4980-8d5d-11f4180e6937' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4303b577-e5f7-4946-98a2-df71a64aab4a' class='xr-index-data-in' type='checkbox'/><label for='index-4303b577-e5f7-4946-98a2-df71a64aab4a' 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;2015-01-08 03:13:29.982468&#x27;, &#x27;2015-01-08 03:13:53.894685&#x27;,\n",
       "               &#x27;2015-01-15 03:19:39.382766&#x27;, &#x27;2015-01-24 03:13:23.531457&#x27;,\n",
       "               &#x27;2015-01-24 03:13:47.430966&#x27;, &#x27;2015-01-31 03:19:34.830432&#x27;,\n",
       "               &#x27;2015-02-09 03:13:19.704636&#x27;, &#x27;2015-02-09 03:13:43.608381&#x27;,\n",
       "               &#x27;2015-02-16 03:19:26.145922&#x27;, &#x27;2015-03-13 03:13:02.707654&#x27;,\n",
       "               ...\n",
       "               &#x27;2022-12-13 03:13:57.297286&#x27;, &#x27;2022-12-13 03:14:21.205269&#x27;,\n",
       "               &#x27;2022-12-20 03:20:02.551373&#x27;, &#x27;2023-01-30 03:13:49.792150&#x27;,\n",
       "               &#x27;2023-02-06 03:19:59.828665&#x27;, &#x27;2023-03-10 03:19:36.398519&#x27;,\n",
       "               &#x27;2023-03-19 03:13:21.687104&#x27;, &#x27;2023-03-19 03:13:45.590852&#x27;,\n",
       "               &#x27;2023-03-26 03:19:27.417316&#x27;, &#x27;2023-05-22 03:12:44.346558&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=102, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>band</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-25377af6-7b12-40fd-95dc-2827d33a7c06' class='xr-index-data-in' type='checkbox'/><label for='index-25377af6-7b12-40fd-95dc-2827d33a7c06' 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([&#x27;blue&#x27;, &#x27;green&#x27;, &#x27;red&#x27;, &#x27;nir08&#x27;], dtype=&#x27;object&#x27;, name=&#x27;band&#x27;))</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-765c98f0-bdd9-4e71-9cc1-40bafbfb62fa' class='xr-index-data-in' type='checkbox'/><label for='index-765c98f0-bdd9-4e71-9cc1-40bafbfb62fa' 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([511410.0, 511440.0, 511470.0, 511500.0, 511530.0, 511560.0, 511590.0,\n",
       "       511620.0, 511650.0, 511680.0,\n",
       "       ...\n",
       "       586110.0, 586140.0, 586170.0, 586200.0, 586230.0, 586260.0, 586290.0,\n",
       "       586320.0, 586350.0, 586380.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=2500))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f99cf65-01b4-4d2e-87dc-0b405c8298e1' class='xr-index-data-in' type='checkbox'/><label for='index-3f99cf65-01b4-4d2e-87dc-0b405c8298e1' 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([1460100.0, 1460070.0, 1460040.0, 1460010.0, 1459980.0, 1459950.0,\n",
       "       1459920.0, 1459890.0, 1459860.0, 1459830.0,\n",
       "       ...\n",
       "       1385400.0, 1385370.0, 1385340.0, 1385310.0, 1385280.0, 1385250.0,\n",
       "       1385220.0, 1385190.0, 1385160.0, 1385130.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=2500))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d00c4dac-6ca5-4aeb-8dcb-18dd1765b64c' class='xr-section-summary-in' type='checkbox'  ><label for='section-d00c4dac-6ca5-4aeb-8dcb-18dd1765b64c' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>collection :</span></dt><dd>landsat-c2-l2</dd><dt><span>stac :</span></dt><dd>https://planetarycomputer.microsoft.com/api/stac/v1</dd><dt><span>epsg :</span></dt><dd>EPSG:32648</dd><dt><span>resolution :</span></dt><dd>30</dd><dt><span>edge_size :</span></dt><dd>2500</dd><dt><span>central_lat :</span></dt><dd>12.8681</dd><dt><span>central_lon :</span></dt><dd>105.4509</dd><dt><span>central_y :</span></dt><dd>1422592.3438612917</dd><dt><span>central_x :</span></dt><dd>548922.3612959113</dd><dt><span>time_coverage_start :</span></dt><dd>2015-01-01</dd><dt><span>time_coverage_end :</span></dt><dd>2044-06-30</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'landsat-c2-l2' (time: 102, band: 4, y: 2500, x: 2500)>\n",
       "dask.array<fetch_raster_window, shape=(102, 4, 2500, 2500), dtype=float64, chunksize=(1, 1, 1024, 1024), chunktype=numpy.ndarray>\n",
       "Coordinates: (12/30)\n",
       "  * time                         (time) datetime64[ns] 2015-01-08T03:13:29.98...\n",
       "    id                           (time) <U31 'LC08_L2SP_125051_20150108_02_T1...\n",
       "  * band                         (band) <U5 'blue' 'green' 'red' 'nir08'\n",
       "  * x                            (x) float64 5.114e+05 5.114e+05 ... 5.864e+05\n",
       "  * y                            (y) float64 1.46e+06 1.46e+06 ... 1.385e+06\n",
       "    landsat:correction           <U4 'L2SP'\n",
       "    ...                           ...\n",
       "    title                        (band) <U22 'Blue Band' ... 'Near Infrared B...\n",
       "    raster:bands                 object {'scale': 2.75e-05, 'nodata': 0, 'off...\n",
       "    common_name                  (band) <U5 'blue' 'green' 'red' 'nir08'\n",
       "    center_wavelength            (band) float64 0.48 0.56 0.65 0.87\n",
       "    full_width_half_max          (band) float64 0.06 0.06 0.04 0.03\n",
       "    epsg                         <U10 'EPSG:32648'\n",
       "Attributes:\n",
       "    collection:           landsat-c2-l2\n",
       "    stac:                 https://planetarycomputer.microsoft.com/api/stac/v1\n",
       "    epsg:                 EPSG:32648\n",
       "    resolution:           30\n",
       "    edge_size:            2500\n",
       "    central_lat:          12.8681\n",
       "    central_lon:          105.4509\n",
       "    central_y:            1422592.3438612917\n",
       "    central_x:            548922.3612959113\n",
       "    time_coverage_start:  2015-01-01\n",
       "    time_coverage_end:    2044-06-30"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da = cubo.create(\n",
    "    lat=12.8681,\n",
    "    lon=105.4509,\n",
    "    collection=\"landsat-c2-l2\",\n",
    "    bands=[\"blue\",\"green\",\"red\", \"nir08\"],\n",
    "    start_date=\"2015-01-01\", # start project date \n",
    "    end_date=\"2044-06-30\", # end date\n",
    "    edge_size=2500,\n",
    "    resolution=30,\n",
    "    query={\n",
    "        \"eo:cloud_cover\": {\"lt\": 9},\n",
    "        \"platform\": {\"eq\": \"landsat-8\"}\n",
    "    }\n",
    ")\n",
    "\n",
    "# crs 32648\n",
    "da\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a316e3ad",
   "metadata": {},
   "source": [
    "# 2. Remove captures with NAN in ROI, and save rasters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3849f9bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0   2015-01-08T03:13:29.982468000\n",
      "1   2015-01-08T03:13:53.894685000\n",
      "2   2015-01-15T03:19:39.382766000\n",
      "3   2015-01-24T03:13:23.531457000\n",
      "4   2015-01-24T03:13:47.430966000\n",
      "5   2015-01-31T03:19:34.830432000\n",
      "6   2015-02-09T03:13:19.704636000\n",
      "7   2015-02-09T03:13:43.608381000\n",
      "8   2015-02-16T03:19:26.145922000\n",
      "9   2015-03-13T03:13:02.707654000\n",
      "10   2015-03-29T03:12:54.851466000\n",
      "11   2015-03-29T03:13:18.759447000\n",
      "12   2015-04-14T03:12:49.874425000\n",
      "13   2015-04-14T03:13:13.778170000\n",
      "14   2015-04-21T03:18:59.524650000\n",
      "15   2015-06-08T03:18:50.724091000\n",
      "16   2015-10-30T03:19:44.058978000\n",
      "17   2015-12-01T03:19:46.574861000\n",
      "18   2016-01-02T03:19:43.637647000\n",
      "19   2016-01-11T03:13:55.076387000\n",
      "20   2016-02-19T03:19:30.848775000\n",
      "21   2016-02-28T03:13:20.550865000\n",
      "22   2016-02-28T03:13:44.454611000\n",
      "23   2016-03-06T03:19:30.619047000\n",
      "24   2016-03-31T03:13:06.338286000\n",
      "25   2016-03-31T03:13:30.242032000\n",
      "26   2016-04-07T03:19:15.543638000\n",
      "27   2016-11-10T03:13:46.324285000\n",
      "28   2017-01-04T03:19:49.833936000\n",
      "29   2017-01-13T03:13:36.994349000\n",
      "30   2017-01-13T03:14:00.898095000\n",
      "31   2017-01-29T03:13:30.908147000\n",
      "32   2017-01-29T03:13:54.816129000\n",
      "33   2017-02-05T03:19:37.962610000\n",
      "34   2017-02-14T03:13:23.409057000\n",
      "35   2017-02-14T03:13:47.308566000\n",
      "36   2017-03-02T03:13:17.695177000\n",
      "37   2017-10-28T03:13:44.989931000\n",
      "38   2017-12-06T03:19:46.450403000\n",
      "39   2018-01-16T03:13:29.484403000\n",
      "40   2018-02-01T03:13:19.623973000\n",
      "41   2018-02-08T03:19:28.388754000\n",
      "42   2018-03-12T03:19:13.492882000\n",
      "43   2018-10-31T03:13:21.498402000\n",
      "44   2018-10-31T03:13:45.402149000\n",
      "45   2018-11-16T03:13:23.032770000\n",
      "46   2018-12-02T03:13:21.593729000\n",
      "47   2018-12-02T03:13:45.497476000\n",
      "48   2018-12-18T03:13:19.185441000\n",
      "49   2018-12-25T03:19:30.309284000\n",
      "50   2019-01-26T03:19:24.951395000\n",
      "51   2019-02-04T03:13:12.734248000\n",
      "52   2019-02-04T03:13:36.637995000\n",
      "53   2019-02-11T03:19:22.800138000\n",
      "54   2019-02-27T03:19:19.231836000\n",
      "55   2019-04-16T03:19:05.033901000\n",
      "56   2019-10-25T03:20:01.460261000\n",
      "57   2019-11-19T03:13:46.570936000\n",
      "58   2019-11-19T03:14:10.478919000\n",
      "59   2019-11-26T03:19:56.829298000\n",
      "60   2019-12-05T03:13:45.794081000\n",
      "61   2019-12-05T03:14:09.697829000\n",
      "62   2019-12-12T03:19:55.878939000\n",
      "63   2019-12-28T03:19:52.160815000\n",
      "64   2020-01-06T03:13:39.004177000\n",
      "65   2020-01-06T03:14:02.907923000\n",
      "66   2020-01-13T03:19:48.635803000\n",
      "67   2020-01-22T03:13:35.504675000\n",
      "68   2020-01-22T03:13:59.408422000\n",
      "69   2020-02-07T03:13:30.227052000\n",
      "70   2020-02-07T03:13:54.139272000\n",
      "71   2020-02-23T03:13:26.817603000\n",
      "72   2020-02-23T03:13:50.721351000\n",
      "73   2020-03-26T03:13:12.319739000\n",
      "74   2020-03-26T03:13:36.227724000\n",
      "75   2020-11-21T03:13:45.792619000\n",
      "76   2020-12-30T03:19:55.118484000\n",
      "77   2021-01-08T03:13:40.750169000\n",
      "78   2021-01-08T03:14:04.653916000\n",
      "79   2021-01-15T03:19:48.153029000\n",
      "80   2021-01-31T03:19:45.579618000\n",
      "81   2021-03-04T03:19:35.262993000\n",
      "82   2021-03-13T03:13:19.214301000\n",
      "83   2021-03-13T03:13:43.118049000\n",
      "84   2021-12-10T03:13:48.214587000\n",
      "85   2021-12-10T03:14:12.126807000\n",
      "86   2022-01-11T03:14:04.825171000\n",
      "87   2022-01-18T03:19:50.106658000\n",
      "88   2022-01-27T03:13:35.312364000\n",
      "89   2022-04-08T03:19:25.334767000\n",
      "90   2022-06-20T03:13:39.396245000\n",
      "91   2022-11-02T03:20:16.401626000\n",
      "92   2022-12-13T03:13:57.297286000\n",
      "93   2022-12-13T03:14:21.205269000\n",
      "94   2022-12-20T03:20:02.551373000\n",
      "95   2023-01-30T03:13:49.792150000\n",
      "96   2023-02-06T03:19:59.828665000\n",
      "97   2023-03-10T03:19:36.398519000\n",
      "98   2023-03-19T03:13:21.687104000\n",
      "99   2023-03-19T03:13:45.590852000\n",
      "100   2023-03-26T03:19:27.417316000\n",
      "101   2023-05-22T03:12:44.346558000\n",
      "extracted and saved 21 out of 102 captures\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "da = (da * 0.0000275) - 0.2\n",
    "ds = da.to_dataset()\n",
    "\n",
    "\"\"\"\n",
    "import geopandas as gpd\n",
    "import rioxarray\n",
    "import numpy \n",
    "\n",
    "gpd = gpd.read_file('./data/TUMRING/TUMRING.geojson')\n",
    "gpd = gpd.to_crs(\"32648\")\n",
    "da = da.rio.write_crs(\"32648\")\n",
    "\n",
    "\n",
    "ds = da.to_dataset()\n",
    "\n",
    "path_data = 'data/TUMRING/satellite_images/'\n",
    "dates_extracted = []\n",
    "days_total = len(da['time'])\n",
    "\n",
    "for day_idx in range(len(da['time'])):\n",
    "    print(str(day_idx) + \"   \"+ str(da['time'][day_idx].data))\n",
    "    ds = da.to_dataset()\n",
    "    ds = ds.isel(time=(day_idx))\n",
    "    ds = ds.squeeze()  # remove dimensions with size 1\n",
    "    ds = ds.rio.write_crs(\"32648\")\n",
    "\n",
    "    try:\n",
    "        if not numpy.isnan(numpy.min(ds['landsat-c2-l2'].to_numpy())):\n",
    "            ds = ds.rio.clip(gpd.geometry, all_touched=True)\n",
    "            ds['landsat-c2-l2'].rio.to_raster(path_data + str(da['time'][day_idx].data)[:10] + '.tif')\n",
    "            dates_extracted.append(str(da['time'][day_idx].data)[:10])\n",
    "    except:\n",
    "        pass\n",
    "print(f\"extracted and saved {len(dates_extracted)} out of {len(da['time'])} captures\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca28905f",
   "metadata": {},
   "source": [
    "# 3. Compute average NDVI for each capture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a2112873",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/TUMRING/satellite_images/2015-01-15.tif\n",
      "data/TUMRING/satellite_images/2015-01-31.tif\n",
      "data/TUMRING/satellite_images/2015-02-16.tif\n",
      "data/TUMRING/satellite_images/2015-04-21.tif\n",
      "data/TUMRING/satellite_images/2015-06-08.tif\n",
      "data/TUMRING/satellite_images/2016-01-02.tif\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_110690/951576558.py:21: RuntimeWarning: divide by zero encountered in divide\n",
      "  EVI = 2.5 * ((NIR - R) / (NIR + 6 * R - 7.5 * B + 1))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/TUMRING/satellite_images/2016-02-19.tif\n",
      "data/TUMRING/satellite_images/2016-04-07.tif\n",
      "data/TUMRING/satellite_images/2017-01-04.tif\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_110690/951576558.py:21: RuntimeWarning: divide by zero encountered in divide\n",
      "  EVI = 2.5 * ((NIR - R) / (NIR + 6 * R - 7.5 * B + 1))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/TUMRING/satellite_images/2018-02-08.tif\n",
      "data/TUMRING/satellite_images/2018-03-12.tif\n",
      "data/TUMRING/satellite_images/2018-12-25.tif\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_110690/951576558.py:21: RuntimeWarning: divide by zero encountered in divide\n",
      "  EVI = 2.5 * ((NIR - R) / (NIR + 6 * R - 7.5 * B + 1))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/TUMRING/satellite_images/2019-01-26.tif\n",
      "data/TUMRING/satellite_images/2019-02-11.tif\n",
      "data/TUMRING/satellite_images/2019-02-27.tif\n",
      "data/TUMRING/satellite_images/2019-10-25.tif\n",
      "data/TUMRING/satellite_images/2019-11-26.tif\n",
      "data/TUMRING/satellite_images/2021-01-15.tif\n",
      "data/TUMRING/satellite_images/2022-04-08.tif\n",
      "data/TUMRING/satellite_images/2022-12-20.tif\n",
      "data/TUMRING/satellite_images/2023-03-10.tif\n"
     ]
    }
   ],
   "source": [
    "import glob\n",
    "import numpy as np\n",
    "import rioxarray\n",
    "import os\n",
    "\n",
    "stats_NDVI = []\n",
    "stats_LAI = []\n",
    "stats_EVI = []\n",
    "\n",
    "dates = []\n",
    "for file in sorted(glob.glob('data/TUMRING/satellite_images/*')):\n",
    "    print(file)\n",
    "    \n",
    "    # open raster and get bands\n",
    "    da = rioxarray.open_rasterio(file, masked=True)\n",
    "    B = da.sel(band=[1]).to_numpy()\n",
    "    R = da.sel(band=[3]).to_numpy()\n",
    "    NIR = da.sel(band=[4]).to_numpy()\n",
    "    \n",
    "    # compute indices\n",
    "    EVI = 2.5 * ((NIR - R) / (NIR + 6 * R - 7.5 * B + 1))\n",
    "    LAI = (3.618*EVI - 0.118) \n",
    "    NDVI = ( NIR - R ) / ( NIR + R ) \n",
    "\n",
    "\n",
    "    EVI = EVI[~np.isnan(EVI)]\n",
    "    NDVI = NDVI[~np.isnan(NDVI)]\n",
    "    LAI = LAI[~np.isnan(LAI)]\n",
    "\n",
    "    if LAI.mean() != np.inf and NDVI.mean() != np.inf:\n",
    "        stats_LAI.append({\n",
    "        'min': LAI.min(),\n",
    "        'mean': LAI.mean(),\n",
    "        'median': np.median(LAI),\n",
    "        'max': LAI.max()})\n",
    "        \n",
    "        stats_NDVI.append({\n",
    "    'min': NDVI.min(),\n",
    "    'mean': NDVI.mean(),\n",
    "    'median': np.median(NDVI),\n",
    "    'max': NDVI.max()})\n",
    "        \n",
    "   # print(os.path.basename(file).split('.')[0])\n",
    "        dates.append(os.path.basename(file).split('.')[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "03457b23",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "means_NDVI = [stat['mean'] for stat in stats_NDVI]\n",
    "means_LAI = [stat['mean'] for stat in stats_LAI]\n",
    "\n",
    "d = {'NDVI': means_NDVI, \"LAI\": means_LAI}\n",
    "df = pd.DataFrame(data=d)\n",
    "# ambient air temperature\n",
    "# the simple moving average \n",
    "df['NDVI_SMA_15'] = df.NDVI.rolling(15, min_periods=1, center=True).mean()\n",
    "df['LAI_SMA_15'] = df.LAI.rolling(15, min_periods=1, center=True).mean()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe0c48c",
   "metadata": {},
   "source": [
    "# Add regression line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a7daf02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NDVI coefficient:\n",
      "[[-9.65828718e-20]]\n",
      "LAI coefficient:\n",
      "[[-9.95002647e-18]]\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn import linear_model\n",
    "\n",
    "data_time = np.asarray(dates)\n",
    "data_count = np.asarray(means_NDVI)\n",
    "\n",
    "dfr = pd.DataFrame({'time': data_time, 'count': data_count})\n",
    "dfr.time = pd.to_datetime(dfr.time)\n",
    "\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(dfr.time.values.reshape(-1, 1), dfr['count'].values.reshape(-1, 1))\n",
    "\n",
    "# Make predictions using the testing set\n",
    "y_pred = regr.predict(dfr.time.values.astype(float).reshape(-1, 1))\n",
    "\n",
    "df['REG_NDVI'] = y_pred\n",
    "print(\"NDVI coefficient:\")\n",
    "print(regr.coef_)\n",
    "\n",
    "\n",
    "data_time = np.asarray(dates)\n",
    "data_count = np.asarray(means_LAI)\n",
    "\n",
    "dfr = pd.DataFrame({'time': data_time, 'count': data_count})\n",
    "dfr.time = pd.to_datetime(dfr.time)\n",
    "\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(dfr.time.values.reshape(-1, 1), dfr['count'].values.reshape(-1, 1))\n",
    "print(\"LAI coefficient:\")\n",
    "print(regr.coef_)\n",
    "# Make predictions using the testing set\n",
    "y_pred = regr.predict(dfr.time.values.astype(float).reshape(-1, 1))\n",
    "\n",
    "df['REG_LAI'] = y_pred\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "126bcba4",
   "metadata": {},
   "source": [
    "# Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d82de8ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_110690/1805376702.py:12: UserWarning: When passing multiple axes, sharex and sharey are ignored. These settings must be specified when creating axes.\n",
      "  df[['LAI','LAI_SMA_15', 'REG_LAI']].plot(subplots=True, ax=target1, legend=True, sharex=True, sharey=False, color=colors)\n",
      "/tmp/ipykernel_110690/1805376702.py:16: UserWarning: When passing multiple axes, sharex and sharey are ignored. These settings must be specified when creating axes.\n",
      "  df[['NDVI','NDVI_SMA_15', 'REG_NDVI']].plot(subplots=True, ax=target2, legend=True, sharex=True, sharey=False, color=colors)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17]),\n",
       " [Text(0, 0, '2015-01-15'),\n",
       "  Text(1, 0, '2015-01-31'),\n",
       "  Text(2, 0, '2015-02-16'),\n",
       "  Text(3, 0, '2015-06-08'),\n",
       "  Text(4, 0, '2016-01-02'),\n",
       "  Text(5, 0, '2016-02-19'),\n",
       "  Text(6, 0, '2017-01-04'),\n",
       "  Text(7, 0, '2018-02-08'),\n",
       "  Text(8, 0, '2018-12-25'),\n",
       "  Text(9, 0, '2019-01-26'),\n",
       "  Text(10, 0, '2019-02-11'),\n",
       "  Text(11, 0, '2019-02-27'),\n",
       "  Text(12, 0, '2019-10-25'),\n",
       "  Text(13, 0, '2019-11-26'),\n",
       "  Text(14, 0, '2021-01-15'),\n",
       "  Text(15, 0, '2022-04-08'),\n",
       "  Text(16, 0, '2022-12-20'),\n",
       "  Text(17, 0, '2023-03-10')])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, axes = plt.subplots(2, 1, figsize=(9, 5))\n",
    "plt.subplots_adjust(wspace=0.5, hspace=0.5)\n",
    "\n",
    "target1 = [axes[0], axes[0], axes[0]]\n",
    "\n",
    "target2 = [axes[1], axes[1], axes[1]]\n",
    "\n",
    "axes[0].set_title(\"LAI\");\n",
    "colors = ['purple', 'red', 'orange']\n",
    "df[['LAI','LAI_SMA_15', 'REG_LAI']].plot(subplots=True, ax=target1, legend=True, sharex=True, sharey=False, color=colors)\n",
    "\n",
    "axes[1].set_title(\"NDVI\");\n",
    "colors = ['purple', 'red', 'orange']\n",
    "df[['NDVI','NDVI_SMA_15', 'REG_NDVI']].plot(subplots=True, ax=target2, legend=True, sharex=True, sharey=False, color=colors)\n",
    "plt.xticks(range(0,len(dates)), dates)\n",
    "plt.xticks(rotation = 90) # Rotates X-Axis Ticks by 45-degrees\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "72340159",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.009396179486095122"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def pct_change(nparray):\n",
    "    pct=np.zeros_like(nparray)\n",
    "    pct[1:]=np.diff(nparray) / np.abs(nparray[:-1])\n",
    "    #TODO zero divisionerror\n",
    "    return pct\n",
    "\n",
    "values = df[['LAI_SMA_15']].to_numpy().flatten().tolist()\n",
    "np.mean(pct_change(values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0debb699",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0019576240766316535"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values = df[['NDVI_SMA_15']].to_numpy().flatten().tolist()\n",
    "np.mean(pct_change(values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86cdd49d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}