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   "source": [
    "# **Forest Clear-Cut Detection using Sentinel-2 Time Series**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/kenoz/SITS_utils/blob/main/docs/source/tutorials/colab_sits_ex05.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "K2FIkbDYrq9l"
   },
   "source": [
    "---\n",
    "We aim to detect tree cover loss by identifying rapid drops in univariate time-series data (e.g. Sentinel-2 indices). This notebook uses an adapted version of the [ClearCutsDetection](https://gitlab.irstea.fr/remi.cresson/ClearCutsDetection) OTB (Orfeo ToolBox) application developed by R. Cresson (INRAE-UMR TETIS), now available as a built-in feature of the `sits` package.\n",
    "\n",
    "---\n",
    "## 1. Installation of SITS package and its depedencies\n",
    "\n",
    "First, install `sits` package with [pip](https://pypi.org/project/SITS/). We also need some other packages for displaying data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#!pip install -q --upgrade sits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can import `sits` modules and some other libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from sits import sits, analysis\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import box\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also create a directory to store the output files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_dir = 'test_data'\n",
    "if not os.path.exists(out_dir):\n",
    "    os.makedirs(out_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 2. Study area\n",
    "\n",
    "We have selected a study site in the **Morvan Regional Natural Park**, France. The workflow requires two spatial definitions: a bounding box in WGS84 (lat/lon) for querying the STAC catalog, and a projected version in EPSG:3035 to define the output CRS for analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bbox in EPSG:4326: [4.0, 47.0, 4.1, 47.05]\n",
      "bbox in EPSG:3035: [3864842.734478761, 2671911.2763597923, 3872853.778674381, 2678061.0457251826]\n"
     ]
    }
   ],
   "source": [
    "# area of study\n",
    "bbox_4326 = [4.000000, 47.000000, 4.100000, 47.050000]\n",
    "\n",
    "print(f\"bbox in EPSG:4326: {bbox_4326}\")\n",
    "geom = box(*bbox_4326)\n",
    "# Load into a GeoDataFrame and set the original CRS (WGS84)\n",
    "gdf = gpd.GeoDataFrame({'geometry': [geom]}, crs=\"EPSG:4326\")\n",
    "\n",
    "# Transform to EPSG:3035\n",
    "gdf_3035 = gdf.to_crs(\"EPSG:3035\")\n",
    "# Extract the bounds as a list: [minx, miny, maxx, maxy]\n",
    "bbox_3035 = list(gdf_3035.total_bounds)\n",
    "print(f\"bbox in EPSG:3035: {bbox_3035}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "# open an interactive map directly in the notebook\n",
    "gdf.explore()"
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   "source": [
    "```\n",
    "<div style=\"text-align: center;\">\n",
    "  <img src=\"img/cc_area.png\" alt=\"clear-cut method\" width=\"500\">\n",
    "</div>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 3. Pre-processing: STAC Queries and Forest Masking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1. Sentinel-2 time series\n",
    "\n",
    "The retrieval process involves collecting Sentinel-2 (Level-2A) imagery acquired between January 1, 2019, and January 1, 2025, filtered for a cloud cover of less than 20%. We then construct a four-band geospatial data cube, consisting of B04 (Red), B08 (NIR), B11 (SWIR), and SCL (Scene Classification Layer), reprojected to EPSG:3035 at a 10m spatial resolution. During this process, radiometric offsets are corrected. Finally, the SCL layer is utilized to mask invalid pixels, such as clouds and cloud shadows (refer to [tutorial 01](https://github.com/kenoz/SITS_utils/blob/186dbf13de0289707a8a2d9c7f3706fc96591d51/docs/source/tutorials/colab_sits_ex01.ipynb) for additional details)."
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   "execution_count": 6,
   "metadata": {
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       "  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 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\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:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\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",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\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",
       "  border-color: var(--xr-background-color-row-even);\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",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\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-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\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",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
       "Dimensions:      (time: 201, y: 616, x: 802)\n",
       "Coordinates:\n",
       "  * y            (y) float64 5kB 2.678e+06 2.678e+06 ... 2.672e+06 2.672e+06\n",
       "  * x            (x) float64 6kB 3.865e+06 3.865e+06 ... 3.873e+06 3.873e+06\n",
       "  * time         (time) datetime64[ns] 2kB 2019-02-05T10:52:31.024000 ... 202...\n",
       "    spatial_ref  int64 8B 0\n",
       "Data variables:\n",
       "    B04          (time, y, x) float32 397MB dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;\n",
       "    B08          (time, y, x) float32 397MB dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;\n",
       "    B11          (time, y, x) float32 397MB dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;\n",
       "    SCL          (time, y, x) float32 397MB dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-35eea25d-44b9-4a7c-92c9-17138271d7ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-35eea25d-44b9-4a7c-92c9-17138271d7ca' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 201</li><li><span class='xr-has-index'>y</span>: 616</li><li><span class='xr-has-index'>x</span>: 802</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6e722e6b-47fe-46ea-a375-d6bee51f7f3b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e722e6b-47fe-46ea-a375-d6bee51f7f3b' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.678e+06 2.678e+06 ... 2.672e+06</div><input id='attrs-8315ad7a-bff9-451a-9529-42646b383486' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8315ad7a-bff9-451a-9529-42646b383486' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45b2a737-e240-45f4-81dc-1d015e0f4fc4' class='xr-var-data-in' type='checkbox'><label for='data-45b2a737-e240-45f4-81dc-1d015e0f4fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([2678065., 2678055., 2678045., ..., 2671935., 2671925., 2671915.])</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'>3.865e+06 3.865e+06 ... 3.873e+06</div><input id='attrs-d7cb3e89-ec6c-4899-9f5e-70839eef00d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7cb3e89-ec6c-4899-9f5e-70839eef00d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d51efc04-daa7-4860-94fc-eb74f0f79f1d' class='xr-var-data-in' type='checkbox'><label for='data-d51efc04-daa7-4860-94fc-eb74f0f79f1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([3864845., 3864855., 3864865., ..., 3872835., 3872845., 3872855.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-02-05T10:52:31.024000 ... 2...</div><input id='attrs-59d494f5-6e16-4c60-a7b7-b136b54ee51d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59d494f5-6e16-4c60-a7b7-b136b54ee51d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2feafe81-4690-4b16-8e8b-49e1d51c2935' class='xr-var-data-in' type='checkbox'><label for='data-2feafe81-4690-4b16-8e8b-49e1d51c2935' 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;2019-02-05T10:52:31.024000000&#x27;, &#x27;2019-02-15T10:51:31.024000000&#x27;,\n",
       "       &#x27;2019-02-17T10:41:19.024000000&#x27;, ..., &#x27;2024-10-23T10:41:11.024000000&#x27;,\n",
       "       &#x27;2024-10-28T10:40:49.024000000&#x27;, &#x27;2024-11-05T10:52:31.025000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a2306919-6b8e-4e80-ade3-4b5ea7a2f47a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2306919-6b8e-4e80-ade3-4b5ea7a2f47a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ded39fe2-6e54-4187-b46b-4a191a0db2f1' class='xr-var-data-in' type='checkbox'><label for='data-ded39fe2-6e54-4187-b46b-4a191a0db2f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>ETRS89</dd><dt><span>horizontal_datum_name :</span></dt><dd>European Terrestrial Reference System 1989</dd><dt><span>projected_crs_name :</span></dt><dd>ETRS89-extended / LAEA Europe</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>52.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>4321000.0</dd><dt><span>false_northing :</span></dt><dd>3210000.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>3864840.0 10.0 0.0 2678070.0 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c7a5c41-cfeb-4343-9553-e79cada5f0ad' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4c7a5c41-cfeb-4343-9553-e79cada5f0ad' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>B04</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;</div><input id='attrs-3957c7d3-2351-4e5a-a4de-9af4ee78fbb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3957c7d3-2351-4e5a-a4de-9af4ee78fbb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5227ae30-3a47-4a11-a0d0-0e088a717a8c' class='xr-var-data-in' type='checkbox'><label for='data-5227ae30-3a47-4a11-a0d0-0e088a717a8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <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> 378.80 MiB </td>\n",
       "                        <td> 1.43 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (201, 616, 802) </td>\n",
       "                        <td> (1, 612, 612) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 804 chunks in 15 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B08</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;</div><input id='attrs-9cd66348-c37e-4c2f-b0cc-b5e4c65a87d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd66348-c37e-4c2f-b0cc-b5e4c65a87d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bf7ed98-893d-48bf-9d9b-a90ae24e651a' class='xr-var-data-in' type='checkbox'><label for='data-7bf7ed98-893d-48bf-9d9b-a90ae24e651a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 378.80 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 612, 612) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B11</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;</div><input id='attrs-61a5b157-a8db-48d5-9ffe-03d80f8700a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61a5b157-a8db-48d5-9ffe-03d80f8700a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a23d1833-9b19-4fc9-8985-f9a0ce66536c' class='xr-var-data-in' type='checkbox'><label for='data-a23d1833-9b19-4fc9-8985-f9a0ce66536c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <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> 378.80 MiB </td>\n",
       "                        <td> 1.43 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (201, 616, 802) </td>\n",
       "                        <td> (1, 612, 612) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 804 chunks in 15 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SCL</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 612, 612), meta=np.ndarray&gt;</div><input id='attrs-8d71f869-77a6-4b73-b681-6a46f982568c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d71f869-77a6-4b73-b681-6a46f982568c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ea7990e-69e8-4008-9e28-231b4beec0ab' class='xr-var-data-in' type='checkbox'><label for='data-0ea7990e-69e8-4008-9e28-231b4beec0ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>nodata :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <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> 378.80 MiB </td>\n",
       "                        <td> 1.43 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (201, 616, 802) </td>\n",
       "                        <td> (1, 612, 612) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 804 chunks in 11 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f697d6a-cf23-4f35-ab04-98ec9c98bf96' class='xr-section-summary-in' type='checkbox'  ><label for='section-7f697d6a-cf23-4f35-ab04-98ec9c98bf96' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4f3d91d2-b99e-40a1-b623-88b0568173c1' class='xr-index-data-in' type='checkbox'/><label for='index-4f3d91d2-b99e-40a1-b623-88b0568173c1' 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([2678065.0, 2678055.0, 2678045.0, 2678035.0, 2678025.0, 2678015.0,\n",
       "       2678005.0, 2677995.0, 2677985.0, 2677975.0,\n",
       "       ...\n",
       "       2672005.0, 2671995.0, 2671985.0, 2671975.0, 2671965.0, 2671955.0,\n",
       "       2671945.0, 2671935.0, 2671925.0, 2671915.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=616))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1899fe23-22ff-4faa-85af-7ef6aa56c592' class='xr-index-data-in' type='checkbox'/><label for='index-1899fe23-22ff-4faa-85af-7ef6aa56c592' 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([3864845.0, 3864855.0, 3864865.0, 3864875.0, 3864885.0, 3864895.0,\n",
       "       3864905.0, 3864915.0, 3864925.0, 3864935.0,\n",
       "       ...\n",
       "       3872765.0, 3872775.0, 3872785.0, 3872795.0, 3872805.0, 3872815.0,\n",
       "       3872825.0, 3872835.0, 3872845.0, 3872855.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=802))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2809d11e-c768-402c-8935-8477b3500da4' class='xr-index-data-in' type='checkbox'/><label for='index-2809d11e-c768-402c-8935-8477b3500da4' 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;2019-02-05 10:52:31.024000&#x27;, &#x27;2019-02-15 10:51:31.024000&#x27;,\n",
       "               &#x27;2019-02-17 10:41:19.024000&#x27;, &#x27;2019-02-20 10:50:59.024000&#x27;,\n",
       "               &#x27;2019-02-22 10:40:41.024000&#x27;, &#x27;2019-02-25 10:50:21.024000&#x27;,\n",
       "               &#x27;2019-02-27 10:40:19.024000&#x27;, &#x27;2019-03-19 10:40:19.025000&#x27;,\n",
       "               &#x27;2019-03-22 10:50:29.024000&#x27;, &#x27;2019-03-27 10:50:31.025000&#x27;,\n",
       "               ...\n",
       "               &#x27;2024-07-30 10:36:29.024000&#x27;, &#x27;2024-08-12 10:46:29.024000&#x27;,\n",
       "               &#x27;2024-08-19 10:36:29.024000&#x27;, &#x27;2024-08-22 10:46:19.024000&#x27;,\n",
       "               &#x27;2024-08-24 10:40:21.024000&#x27;, &#x27;2024-08-29 10:36:29.024000&#x27;,\n",
       "               &#x27;2024-10-21 10:50:09.024000&#x27;, &#x27;2024-10-23 10:41:11.024000&#x27;,\n",
       "               &#x27;2024-10-28 10:40:49.024000&#x27;, &#x27;2024-11-05 10:52:31.025000&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=201, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d91b263-b4dc-48b7-af00-b828dba73b4c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7d91b263-b4dc-48b7-af00-b828dba73b4c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2GB\n",
       "Dimensions:      (time: 201, y: 616, x: 802)\n",
       "Coordinates:\n",
       "  * y            (y) float64 5kB 2.678e+06 2.678e+06 ... 2.672e+06 2.672e+06\n",
       "  * x            (x) float64 6kB 3.865e+06 3.865e+06 ... 3.873e+06 3.873e+06\n",
       "  * time         (time) datetime64[ns] 2kB 2019-02-05T10:52:31.024000 ... 202...\n",
       "    spatial_ref  int64 8B 0\n",
       "Data variables:\n",
       "    B04          (time, y, x) float32 397MB dask.array<chunksize=(1, 612, 612), meta=np.ndarray>\n",
       "    B08          (time, y, x) float32 397MB dask.array<chunksize=(1, 612, 612), meta=np.ndarray>\n",
       "    B11          (time, y, x) float32 397MB dask.array<chunksize=(1, 612, 612), meta=np.ndarray>\n",
       "    SCL          (time, y, x) float32 397MB dask.array<chunksize=(1, 612, 612), meta=np.ndarray>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bands = ['B04', 'B08', 'B11', 'SCL']\n",
    "cloud_cover = 20\n",
    "\n",
    "ts_S2 = sits.StacAttack(provider='mpc',\n",
    "                        collection='sentinel-2-l2a',\n",
    "                        bands=bands)\n",
    "\n",
    "# search of items based on bbox coordinates and time interval criteria\n",
    "ts_S2.searchItems(bbox_4326,\n",
    "                  date_start=datetime(2019, 1, 1),\n",
    "                  date_end=datetime(2025, 1, 1),\n",
    "                  query={\"eo:cloud_cover\": {\"lt\": cloud_cover}})\n",
    "\n",
    "# load of the time series in a lazy way\n",
    "ts_S2.loadCube(bbox_3035, resolution=10, crs_out=3035)\n",
    "ts_S2.fixS2shift()\n",
    "\n",
    "ts_S2.mask_conf(mask_values=[0, 1, 3, 6, 8, 9, 10, 11])\n",
    "ts_S2.mask_apply()\n",
    "\n",
    "ts_S2.cube"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2. Forest mask\n",
    "\n",
    "The algorithm detects abrupt signal drops regardless of land cover type. Therefore, a forest mask is required to focus the detection exclusively on forested regions and avoid false positives in other areas. For this example, we use the [ESRI 10 meter land cover](https://planetarycomputer.microsoft.com/dataset/io-lulc#overview) product. This dataset provides a global estimates of 10-class land use/land cover (LULC) for 2020, derived from ESA Sentinel-2 imagery at 10m resolution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datetime parsing failed: time data '2020-06-01T00:00:00Z' does not match format '%Y-%m-%dT%H:%M:%S.%fZ'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/osekenj/.local/lib/python3.11/site-packages/rasterio/warp.py:387: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix will be returned.\n",
      "  dest = _reproject(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lulc = sits.StacAttack(provider='mpc',\n",
    "                       collection='io-lulc',\n",
    "                       bands=['data'])\n",
    "lulc.searchItems(bbox_4326,\n",
    "                 date_start=datetime(2019, 1, 1),\n",
    "                 date_end=datetime(2020, 12, 31))\n",
    "lulc.loadCube(bbox_3035, resolution=10, crs_out=3035)\n",
    "\n",
    "lulc.cube.data.plot()\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Like most land-cover classifications, this dataset uses integers to represent different classes. We need to determine the specific code used for forest pixels to isolate them for our analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class index: 0, Value: nodata\n",
      "Class index: 1, Value: water\n",
      "Class index: 2, Value: trees\n",
      "Class index: 3, Value: grass\n",
      "Class index: 4, Value: flooded veg\n",
      "Class index: 5, Value: crops\n",
      "Class index: 6, Value: scrub\n",
      "Class index: 7, Value: built area\n",
      "Class index: 8, Value: bare\n",
      "Class index: 9, Value: snow/ice\n",
      "Class index: 10, Value: clouds\n"
     ]
    }
   ],
   "source": [
    "for index, value in enumerate(lulc.items_prop[\"label:classes\"][0][0][\"classes\"]):\n",
    "    print(f\"Class index: {index}, Value: {value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Following the ESRI 10m LULC scheme, the **value 2** corresponds to the **Forest class**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "forest_mask = (lulc.cube.data != 2).squeeze(drop=True)\n",
    "\n",
    "forest_mask.plot()\n",
    "plt.axis('scaled')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To constrain the satellite data using the forest mask, we utilize again the `StacAttack.mask_conf()` method by passing our boolean array to the `mask_array` parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "ts_S2.mask_conf(mask_array=forest_mask)\n",
    "ts_S2.mask_apply()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 4. Clear-cut mapping\n",
    "\n",
    "### 4.1. A few words about the method\n",
    "This detection method exploits vegetation index time series to map forest clear-cuts by identifying abrupt temporal declines. The algorithm uses a convolution-based approach to calculate a value $d$, which quantifies the transition of a pixel's index value from a high, stable forest signal to a low post-harvest signal. A clear-cut is detected whenever $d$ exceeds a configurable threshold $d_{THRES}$ at a specific date $t_i$. The intensity of the drop is categorized into \"strong\" or \"very strong\" magnitudes, and metadata, such as the number of samples used for detection, are recorded to validate the result. The algorithm processes each unmasked pixel independently as a temporal stack. Originally implemented via the Orfeo ToolBox ([OTB](https://www.orfeo-toolbox.org/)), this approach is now available in `sits` package.\n",
    "\n",
    "<div style=\"text-align: center;\">\n",
    "  <img src=\"img/clearcut.png\" alt=\"clear-cut method\" width=\"400\">\n",
    "</div>\n",
    "<div style=\"text-align: center;\">\n",
    "  <sup>Clear-cut detection in one pixel of Sentinel-2 time series. <i>Only valid pixel values are shown. The top chart presents the NDVI time series, the bottom chart presents the “NDVI drop” time series. Maximum drop greater than the specified threshold $d_{THRES}$ is labeled as clear-cut.</i></sup>\n",
    "</div>\n",
    "\n",
    "source:\n",
    "\n",
    "> K. Ose and R. Cresson, \"Clear-Cuts Detection Services for The Monitoring Needs of the French Ministry of Agriculture,\" *IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium*, Yokohama, Japan, 2019, pp. 4284-4287, [doi: 10.1109/IGARSS.2019.8897825](https://ieeexplore.ieee.org/document/8897825).\n",
    "\n",
    "### 4.2. Time series of Vegetation Index\n",
    "As explained in [tutorial 03](https://github.com/kenoz/SITS_utils/blob/main/docs/source/tutorials/colab_sits_ex03.ipynb), `sits` utilizes the `spyndex` package to calculate spectral indices. In this step, we generate a time series of NDMI.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "band_mapping = {'B': 'B02', 'G': 'B03', 'R': 'B04', 'N': 'B08', 'S1': 'B11'}\n",
    "index = 'NDMI'\n",
    "\n",
    "ts_S2.spectral_index(index, band_mapping)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3. Clear-cuts detection\n",
    "\n",
    "The clear-cut detection logic is implemented within the `ClearCut` class of the `sits.analysis` module. This class is designed to detect abrupt changes in univariate time series (e.g., spectral indices like NDVI) by comparing observations within two sliding temporal windows:\n",
    "\n",
    "- Backward Window: summarizes past observations to establish a baseline.\n",
    "- Forward Window: summarizes upcoming observations to detect potential drops.\n",
    "\n",
    "A change is flagged when the forward window shows a significant decline relative to the backward window, exceeding a user-defined threshold. The detection process follows two mandatory stages:\n",
    "\n",
    "1. `ClearCut.season_of_interest()`: this method filters the data cube to retain only observations within a specific yearly range. By default, we use start=\"06-01\" and end=\"08-31\" to focus on the summer season. This is crucial for studying deciduous broadleaf forests; during winter, the natural loss of leaves significantly impacts vegetation index values, which frequently leads to false detections.\n",
    "2. `ClearCut.detect_anomalies()`: this core method identifies anomalies by calculating the magnitude of change (the absolute difference between the means of the backward and forward windows). An anomaly is recorded if this magnitude exceeds the primary threshold.\n",
    "\n",
    "Key Parameters:\n",
    "> - thresholds (list, default [0.2, 0.3, 0.4]): Values used to classify the severity of the anomaly.\n",
    "> - window_backward / window_forward (int): The temporal extent (in days) for the past (720d) and future (60d) baselines.\n",
    "> - min_obs_backward / min_obs_forward (int): The minimum required valid pixels within those windows. If these are not met, the algorithm searches beyond the window limits, and the inrange flag is set to False.\n",
    "> - out_crs: The target CRS for the output (default \"EPSG:3035\").\n",
    "\n",
    "Output Dataset: the resulting `Clearcut.detection` is an `xarray.Dataset` containing:\n",
    "> - magnitude_first / max / last: The intensity of the first, strongest, and most recent anomalies.\n",
    "> - date_first / max / last: The corresponding dates (Unix epoch) of these events.\n",
    "> - mask: A binary layer indicating where an anomaly was detected.\n",
    "> - inrange: A flag indicating if the detection stayed within the defined temporal window constraints.\n",
    "> - classif: A categorical layer classifying the event based on the provided thresholds (low, medium and high confidence).\n",
    "\n",
    "Optionally, you can export the result to a NetCDF file using `ClearCut.detection.to_netcdf()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_detect = analysis.ClearCut(ts_S2.indices.NDMI)\n",
    "cc_detect.season_of_interest()\n",
    "cc_detect.detect_anomalies(thresholds=[0.25, 0.35, 0.45],\n",
    "                           min_obs_backward=5,\n",
    "                           min_obs_forward=5)\n",
    "\n",
    "cc_detect.detection.to_netcdf(os.path.join(out_dir, f\"clearcut_example.nc\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output `xarray.Dataarray` includes 9 variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 17MB\n",
       "Dimensions:          (y: 616, x: 802)\n",
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       "    mask             (y, x) bool 494kB True True True True ... False False False\n",
       "    inrange          (y, x) bool 494kB True True True True ... True True True\n",
       "    classif          (y, x) int64 4MB 1 1 3 2 3 3 3 3 0 0 ... 0 0 0 0 0 0 0 0 0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-10c538ba-851e-4aaa-8fd6-ef1c15ffa420' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-10c538ba-851e-4aaa-8fd6-ef1c15ffa420' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 616</li><li><span class='xr-has-index'>x</span>: 802</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-70c25e0a-fe6c-4543-a2d0-59e4c3e3d36a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-70c25e0a-fe6c-4543-a2d0-59e4c3e3d36a' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.678e+06 2.678e+06 ... 2.672e+06</div><input id='attrs-12e76f14-7e35-4f63-87fd-ed087e41f40b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12e76f14-7e35-4f63-87fd-ed087e41f40b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60dd674c-a41a-4937-9874-6bc9ceb32dee' class='xr-var-data-in' type='checkbox'><label for='data-60dd674c-a41a-4937-9874-6bc9ceb32dee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([2678065., 2678055., 2678045., ..., 2671935., 2671925., 2671915.])</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'>3.865e+06 3.865e+06 ... 3.873e+06</div><input id='attrs-1e7c62d5-5200-4b74-b9c7-b9a3ca76e383' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e7c62d5-5200-4b74-b9c7-b9a3ca76e383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97008872-7b4d-4c5c-9af2-a06fa82b24a6' class='xr-var-data-in' type='checkbox'><label for='data-97008872-7b4d-4c5c-9af2-a06fa82b24a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([3864845., 3864855., 3864865., ..., 3872835., 3872845., 3872855.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-06-02T10:40:31.024000</div><input id='attrs-b9be74ed-20fb-49f7-b120-11ca3169c5b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b9be74ed-20fb-49f7-b120-11ca3169c5b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85acd0dc-df97-4e53-b3fc-dee6f831913d' class='xr-var-data-in' type='checkbox'><label for='data-85acd0dc-df97-4e53-b3fc-dee6f831913d' 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;2019-06-02T10:40:31.024000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-c0563bc7-5c43-4027-9a72-898092ff08fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0563bc7-5c43-4027-9a72-898092ff08fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7c85f1d-0424-4cce-aa35-e816b90f1b9b' class='xr-var-data-in' type='checkbox'><label for='data-c7c85f1d-0424-4cce-aa35-e816b90f1b9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314140356</dd><dt><span>inverse_flattening :</span></dt><dd>298.257222101</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>GRS 1980</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>ETRS89</dd><dt><span>horizontal_datum_name :</span></dt><dd>European Terrestrial Reference System 1989</dd><dt><span>projected_crs_name :</span></dt><dd>ETRS89-extended / LAEA Europe</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>52.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>10.0</dd><dt><span>false_easting :</span></dt><dd>4321000.0</dd><dt><span>false_northing :</span></dt><dd>3210000.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;ETRS89-extended / LAEA Europe&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4258&quot;]],PROJECTION[&quot;Lambert_Azimuthal_Equal_Area&quot;],PARAMETER[&quot;latitude_of_center&quot;,52],PARAMETER[&quot;longitude_of_center&quot;,10],PARAMETER[&quot;false_easting&quot;,4321000],PARAMETER[&quot;false_northing&quot;,3210000],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Northing&quot;,NORTH],AXIS[&quot;Easting&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>3864840.0 10.0 0.0 2678070.0 0.0 -10.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-83ec01c9-cb43-43eb-9561-e1a531f68395' class='xr-section-summary-in' type='checkbox'  checked><label for='section-83ec01c9-cb43-43eb-9561-e1a531f68395' class='xr-section-summary' >Data variables: <span>(9)</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>magnitude_first</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3028 -0.3303 -0.5003 ... nan nan</div><input id='attrs-55ee26f7-2bfb-4d66-b8ad-5746712674e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55ee26f7-2bfb-4d66-b8ad-5746712674e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-681643bd-575e-45e9-bbd8-206e0a103c9a' class='xr-var-data-in' type='checkbox'><label for='data-681643bd-575e-45e9-bbd8-206e0a103c9a' 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([[-0.30284378, -0.33034608, -0.50025326, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan, -0.31732804, -0.49788946, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan, -0.42456904, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>date_first</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.878e+04 1.878e+04 ... nan nan</div><input id='attrs-52f3030e-4b70-4255-a91e-f1637b5a7eaf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52f3030e-4b70-4255-a91e-f1637b5a7eaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f60024df-d17f-48b5-a43e-2b1d33065088' class='xr-var-data-in' type='checkbox'><label for='data-f60024df-d17f-48b5-a43e-2b1d33065088' 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([[18779., 18779., 18779., ...,    nan,    nan,    nan],\n",
       "       [   nan, 18779., 18779., ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan, 18779., ...,    nan,    nan,    nan],\n",
       "       ...,\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnitude_max</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3028 -0.3303 -0.5003 ... nan nan</div><input id='attrs-f45cb6d3-5da0-4323-8d48-c25a402e1467' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f45cb6d3-5da0-4323-8d48-c25a402e1467' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47dcfadc-462a-45a3-a56c-7b9c968feb10' class='xr-var-data-in' type='checkbox'><label for='data-47dcfadc-462a-45a3-a56c-7b9c968feb10' 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([[-0.30284378, -0.33034608, -0.50025326, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan, -0.31732804, -0.49788946, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan, -0.42456904, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>date_max</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.878e+04 1.878e+04 ... nan nan</div><input id='attrs-91f85ee7-e2c4-4d7f-bbb3-2fe24b1bf93f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-91f85ee7-e2c4-4d7f-bbb3-2fe24b1bf93f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a61c51f-4677-4df6-8eff-0856535eec09' class='xr-var-data-in' type='checkbox'><label for='data-1a61c51f-4677-4df6-8eff-0856535eec09' 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([[18779., 18779., 18779., ...,    nan,    nan,    nan],\n",
       "       [   nan, 18779., 18779., ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan, 18779., ...,    nan,    nan,    nan],\n",
       "       ...,\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnitude_last</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2884 -0.2538 -0.304 ... nan nan</div><input id='attrs-8bcaa71e-0958-490c-ab4f-45dc80dd486e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8bcaa71e-0958-490c-ab4f-45dc80dd486e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfa7bcf7-0a44-4c7f-99f0-193f825b159a' class='xr-var-data-in' type='checkbox'><label for='data-bfa7bcf7-0a44-4c7f-99f0-193f825b159a' 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([[-0.28841224, -0.25377288, -0.3040022 , ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan, -0.30150932, -0.2852101 , ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan, -0.2751347 , ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>date_last</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.879e+04 1.879e+04 ... nan nan</div><input id='attrs-fe27c19c-1a17-4aea-aa16-fe01c67e7227' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe27c19c-1a17-4aea-aa16-fe01c67e7227' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6b61bf2-dd9f-48dc-b9dc-ee8003481461' class='xr-var-data-in' type='checkbox'><label for='data-c6b61bf2-dd9f-48dc-b9dc-ee8003481461' 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([[18789., 18792., 18794., ...,    nan,    nan,    nan],\n",
       "       [   nan, 18789., 18794., ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan, 18794., ...,    nan,    nan,    nan],\n",
       "       ...,\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... False False</div><input id='attrs-96cb3e08-ad2d-4700-9c5a-f246e6ce7ab4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96cb3e08-ad2d-4700-9c5a-f246e6ce7ab4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3861c056-9b45-4681-9cba-91d847276129' class='xr-var-data-in' type='checkbox'><label for='data-3861c056-9b45-4681-9cba-91d847276129' 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([[ True,  True,  True, ..., False, False, False],\n",
       "       [False,  True,  True, ..., False, False, False],\n",
       "       [False, False,  True, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>inrange</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... True True True</div><input id='attrs-07b723d1-564b-44df-b428-63a50120212d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07b723d1-564b-44df-b428-63a50120212d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69cf7721-22c8-46a0-a668-df8f6ff68c85' class='xr-var-data-in' type='checkbox'><label for='data-69cf7721-22c8-46a0-a668-df8f6ff68c85' 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([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       ...,\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>classif</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 3 2 3 3 3 3 ... 0 0 0 0 0 0 0 0</div><input id='attrs-804cd61d-204d-4135-942d-f051e574f9d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-804cd61d-204d-4135-942d-f051e574f9d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-359c8982-5448-4665-8d88-d63b40c19826' class='xr-var-data-in' type='checkbox'><label for='data-359c8982-5448-4665-8d88-d63b40c19826' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>thresholds :</span></dt><dd>[0.25, 0.35, 0.45]</dd></dl></div><div class='xr-var-data'><pre>array([[1, 1, 3, ..., 0, 0, 0],\n",
       "       [0, 1, 3, ..., 0, 0, 0],\n",
       "       [0, 0, 2, ..., 0, 0, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 0, 0]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-20b22e89-9a68-4c6f-b465-d2d8529f3cd1' class='xr-section-summary-in' type='checkbox'  ><label for='section-20b22e89-9a68-4c6f-b465-d2d8529f3cd1' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-087e83af-361f-4ed0-a7c6-6c199895b615' class='xr-index-data-in' type='checkbox'/><label for='index-087e83af-361f-4ed0-a7c6-6c199895b615' 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([2678065.0, 2678055.0, 2678045.0, 2678035.0, 2678025.0, 2678015.0,\n",
       "       2678005.0, 2677995.0, 2677985.0, 2677975.0,\n",
       "       ...\n",
       "       2672005.0, 2671995.0, 2671985.0, 2671975.0, 2671965.0, 2671955.0,\n",
       "       2671945.0, 2671935.0, 2671925.0, 2671915.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=616))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c636d5fb-d215-4c38-a19e-ce679cd47eb8' class='xr-index-data-in' type='checkbox'/><label for='index-c636d5fb-d215-4c38-a19e-ce679cd47eb8' 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([3864845.0, 3864855.0, 3864865.0, 3864875.0, 3864885.0, 3864895.0,\n",
       "       3864905.0, 3864915.0, 3864925.0, 3864935.0,\n",
       "       ...\n",
       "       3872765.0, 3872775.0, 3872785.0, 3872795.0, 3872805.0, 3872815.0,\n",
       "       3872825.0, 3872835.0, 3872845.0, 3872855.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=802))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0294356c-ec67-4b12-9e2c-71baff59b8de' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0294356c-ec67-4b12-9e2c-71baff59b8de' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 17MB\n",
       "Dimensions:          (y: 616, x: 802)\n",
       "Coordinates:\n",
       "  * y                (y) float64 5kB 2.678e+06 2.678e+06 ... 2.672e+06 2.672e+06\n",
       "  * x                (x) float64 6kB 3.865e+06 3.865e+06 ... 3.873e+06 3.873e+06\n",
       "    time             datetime64[ns] 8B 2019-06-02T10:40:31.024000\n",
       "    spatial_ref      int64 8B 0\n",
       "Data variables:\n",
       "    magnitude_first  (y, x) float32 2MB -0.3028 -0.3303 -0.5003 ... nan nan nan\n",
       "    date_first       (y, x) float32 2MB 1.878e+04 1.878e+04 ... nan nan\n",
       "    magnitude_max    (y, x) float32 2MB -0.3028 -0.3303 -0.5003 ... nan nan nan\n",
       "    date_max         (y, x) float32 2MB 1.878e+04 1.878e+04 ... nan nan\n",
       "    magnitude_last   (y, x) float32 2MB -0.2884 -0.2538 -0.304 ... nan nan nan\n",
       "    date_last        (y, x) float32 2MB 1.879e+04 1.879e+04 ... nan nan\n",
       "    mask             (y, x) bool 494kB True True True True ... False False False\n",
       "    inrange          (y, x) bool 494kB True True True True ... True True True\n",
       "    classif          (y, x) int64 4MB 1 1 3 2 3 3 3 3 0 0 ... 0 0 0 0 0 0 0 0 0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc_detect.detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can visualize the results using an interactive Folium map. The following variables are displayed:\n",
    "- `date_max`: The image acquisition date on which the maximum magnitude drop was detected within the time series.\n",
    "- `classif`: A classification result where 1 represents low magnitude, 2 medium magnitude, and 3 high magnitude. These classes can be interpreted as the level of detection confidence.\n",
    "- `magnitude_max`: The maximum recorded value of the magnitude drop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "            var image_overlay_b1b1b41b623b205482f4ab37a7ee1dd2 = L.imageOverlay(\n",
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&quot;,\n",
       "                [[46.99455872067707, 3.994260477590751], [47.05555465776594, 4.105644362709546]],\n",
       "                {&quot;opacity&quot;: 0.9}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            image_overlay_b1b1b41b623b205482f4ab37a7ee1dd2.addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "        \n",
       "    \n",
       "            var image_overlay_c794667315383773f25ad8aaedd88b8b = L.imageOverlay(\n",
       "                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&quot;,\n",
       "                [[46.99455872067707, 3.994260477590751], [47.05555465776594, 4.105644362709546]],\n",
       "                {&quot;opacity&quot;: 0.9}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            image_overlay_c794667315383773f25ad8aaedd88b8b.addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "        \n",
       "    \n",
       "            var image_overlay_33cad93cfbdad41a92a32e2a8ce33ce8 = L.imageOverlay(\n",
       "                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&quot;,\n",
       "                [[46.99455872067707, 3.994260477590751], [47.05555465776594, 4.105644362709546]],\n",
       "                {&quot;opacity&quot;: 0.9}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            image_overlay_33cad93cfbdad41a92a32e2a8ce33ce8.addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "        \n",
       "    \n",
       "            var marker_68b7dd86fd00cae6536c23080df6c018 = L.marker(\n",
       "                [47.01649, 4.0569],\n",
       "                {}\n",
       "            ).addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "        \n",
       "    \n",
       "            var icon_c0a0f8b35f390be7e96d3f0e7e3d145b = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;leaf&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_68b7dd86fd00cae6536c23080df6c018.setIcon(icon_c0a0f8b35f390be7e96d3f0e7e3d145b);\n",
       "        \n",
       "    \n",
       "        var popup_6ee1668d9ba1c02bd026a8e8d5160956 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_5f8fcdc8ee2f9c645e3e79b162d24718 = $(`&lt;div id=&quot;html_5f8fcdc8ee2f9c645e3e79b162d24718&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;A&lt;/div&gt;`)[0];\n",
       "                popup_6ee1668d9ba1c02bd026a8e8d5160956.setContent(html_5f8fcdc8ee2f9c645e3e79b162d24718);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_68b7dd86fd00cae6536c23080df6c018.bindPopup(popup_6ee1668d9ba1c02bd026a8e8d5160956)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_ab37f7187394bd32a9df40f6cf9a1cde = L.marker(\n",
       "                [47.0298, 4.05275],\n",
       "                {}\n",
       "            ).addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "        \n",
       "    \n",
       "            var icon_577ea3be38c07f98ebb98e763a11efc4 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;leaf&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_ab37f7187394bd32a9df40f6cf9a1cde.setIcon(icon_577ea3be38c07f98ebb98e763a11efc4);\n",
       "        \n",
       "    \n",
       "        var popup_11f5931c3be48fcc12b41e2fe4ee0ef3 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_52c000bf0866b926a4f7b23f48449bc6 = $(`&lt;div id=&quot;html_52c000bf0866b926a4f7b23f48449bc6&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;B&lt;/div&gt;`)[0];\n",
       "                popup_11f5931c3be48fcc12b41e2fe4ee0ef3.setContent(html_52c000bf0866b926a4f7b23f48449bc6);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_ab37f7187394bd32a9df40f6cf9a1cde.bindPopup(popup_11f5931c3be48fcc12b41e2fe4ee0ef3)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            map_ec6fb9af3e01ed9dcdd75745391771cd.fitBounds(\n",
       "                [[46.99455872067707, 3.994260477590751], [47.05555465776594, 4.105644362709546]],\n",
       "                {}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            var layer_control_0aaac9682650092bd66bcaf6de5a6dfb_layers = {\n",
       "                base_layers : {\n",
       "                    &quot;Google Satellite&quot; : tile_layer_af28c9ede3a7b3a8ba04478e61adec03,\n",
       "                },\n",
       "                overlays :  {\n",
       "                    &quot;Change Date&quot; : image_overlay_b1b1b41b623b205482f4ab37a7ee1dd2,\n",
       "                    &quot;Change Classif&quot; : image_overlay_c794667315383773f25ad8aaedd88b8b,\n",
       "                    &quot;Change Magnitude&quot; : image_overlay_33cad93cfbdad41a92a32e2a8ce33ce8,\n",
       "                },\n",
       "            };\n",
       "            let layer_control_0aaac9682650092bd66bcaf6de5a6dfb = L.control.layers(\n",
       "                layer_control_0aaac9682650092bd66bcaf6de5a6dfb_layers.base_layers,\n",
       "                layer_control_0aaac9682650092bd66bcaf6de5a6dfb_layers.overlays,\n",
       "                {&quot;autoZIndex&quot;: true, &quot;collapsed&quot;: true, &quot;position&quot;: &quot;topright&quot;}\n",
       "            ).addTo(map_ec6fb9af3e01ed9dcdd75745391771cd);\n",
       "\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fcfcc11f190>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "from shapely.geometry import Point\n",
    "import numpy as np\n",
    "from rasterio.enums import Resampling\n",
    "\n",
    "def add_xarray_to_map(m, da, name, cmap_name='magma', vmin=None, vmax=None, opacity=0.9):\n",
    "    \"\"\"\n",
    "    Reprojects an xarray DataArray, colorizes it, and adds it to a folium map.\n",
    "    \"\"\"\n",
    "    # 1. Reproject to WGS84\n",
    "    # Note: Using astype('float32') avoids the 'bool' KeyError\n",
    "    da_4326 = (da.astype('float32')\n",
    "               .rio.write_crs(\"EPSG:3035\", inplace=True)\n",
    "               .rio.reproject(\"EPSG:4326\", resampling=Resampling.nearest))\n",
    "\n",
    "    # 2. Get Bounds for Folium: [[min_lat, min_lon], [max_lat, max_lon]]\n",
    "    b = da_4326.rio.bounds()\n",
    "    bounds = [[b[1], b[0]], [b[3], b[2]]]\n",
    "\n",
    "    # 3. Colorize the data\n",
    "    data = da_4326.values\n",
    "    v_min = vmin if vmin is not None else np.nanmin(data)\n",
    "    v_max = vmax if vmax is not None else np.nanmax(data)\n",
    "\n",
    "    norm = plt.Normalize(vmin=v_min, vmax=v_max)\n",
    "    cmap = plt.get_cmap(cmap_name)\n",
    "    rgba_data = cmap(norm(data))\n",
    "\n",
    "    # 4. Add to map\n",
    "    folium.raster_layers.ImageOverlay(\n",
    "        image=rgba_data,\n",
    "        bounds=bounds,\n",
    "        opacity=opacity,\n",
    "        name=name\n",
    "    ).add_to(m)\n",
    "\n",
    "    return bounds\n",
    "\n",
    "# --- Main Logic ---\n",
    "\n",
    "# Initialize Map\n",
    "m = folium.Map(tiles=None)\n",
    "\n",
    "# Add Satellite Basemap\n",
    "folium.TileLayer(\n",
    "    tiles='https://mt1.google.com/vt/lyrs=s&x={x}&y={y}&z={z}',\n",
    "    attr='Google',\n",
    "    name='Google Satellite',\n",
    "    overlay=False\n",
    ").add_to(m)\n",
    "\n",
    "# Process layers using the function\n",
    "classif_filtered = cc_detect.detection.classif.where(\n",
    "    cc_detect.detection.classif.isin([1, 2, 3])\n",
    ")\n",
    "\n",
    "layers = [\n",
    "    (cc_detect.detection.date_max,      \"Change Date\",      'viridis', None, None),\n",
    "    (classif_filtered,                  \"Change Classif\",   'YlOrRd',  None, None),\n",
    "    (cc_detect.detection.magnitude_max, \"Change Magnitude\", 'magma',   None, None),\n",
    "]\n",
    "\n",
    "last_bounds = None\n",
    "for da, name, cmap, vmin, vmax in layers:\n",
    "    last_bounds = add_xarray_to_map(m, da, name, cmap_name=cmap, vmin=vmin, vmax=vmax)\n",
    "\n",
    "# Add 2 reference points\n",
    "point_A = {\"coord_3035\":[3869300, 2674000], \"coord_4326\":[47.01649, 4.05690]}\n",
    "point_B = {\"coord_3035\":[3869100, 2675500], \"coord_4326\":[47.0298, 4.05275]}\n",
    "\n",
    "folium.Marker(\n",
    "    location=point_A[\"coord_4326\"],\n",
    "    popup=\"A\",\n",
    "    icon=folium.Icon(color=\"green\", icon=\"leaf\")\n",
    ").add_to(m)\n",
    "\n",
    "folium.Marker(\n",
    "    location=point_B[\"coord_4326\"],\n",
    "    popup=\"B\",\n",
    "    icon=folium.Icon(color=\"red\", icon=\"leaf\")\n",
    ").add_to(m)\n",
    "\n",
    "# Center the map automatically based on the last layer\n",
    "if last_bounds:\n",
    "    m.fit_bounds(last_bounds)\n",
    "\n",
    "folium.LayerControl().add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "<div style=\"text-align: center;\">\n",
    "  <img src=\"img/cc_map.png\" alt=\"clear-cut method\" width=\"500\">\n",
    "</div>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.4. Plotting the reference points\n",
    "\n",
    "In the figure above, we have represented two points that illustrate different forest dynamics:\n",
    "\n",
    "- **Point A (Green)**: Represents a stable forest area unaffected by changes.\n",
    "- **Point B (Red)**: Corresponds to a clear-cut area.\n",
    "\n",
    "We will now perform a detailed time-series analysis of the NDMI for both points to better understand the behavior of the `sits.analysis.ClearCut` method. We utilize the `sits.analysis.SitsPlotter` class to visualize the index time series and execute the change detection algorithm. This class handles extraction, outlier filtering, and plotting of temporal data for a specific spatial coordinate. It segments the time series into 'fitting' and 'monitoring' windows relative to a break date and supports statistical outlier removal (Sigma or IQR).\n",
    "\n",
    "**Reference site A**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 6.31387562e-01, -2.60446376e-05,  5.13758415e-02, -2.37047788e-02,\n",
       "        1.38931659e-02,  6.14276945e-03, -8.39480969e-03,  1.23986521e-02])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d1 = datetime(2019, 1, 1)\n",
    "d2 = datetime(2025, 1, 1)\n",
    "daterange = [d1, d2]\n",
    "\n",
    "plot_A = analysis.SitsPlotter(ts_S2.indices, \"NDMI\",\n",
    "                              daterange,\n",
    "                              break_date=datetime(2021, 1, 1),\n",
    "                              coords=point_A[\"coord_3035\"],\n",
    "                              ylim=[-0.25, 0.80],\n",
    "                              filter_method=\"sigma\",\n",
    "                              filter_value=1.5)\n",
    "\n",
    "plot_A.plot_model(degree=3, include_trend=True, envelope_quantiles=(0.05, 0.95))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reference point B**\n",
    "\n",
    "Since Point B represents a clear-cut site, we execute the `run_detection()` method of `analysis.SitsPlotter` to visualize the change detection results. This allows us to examine the temporal anomalies and identify the break date corresponding to the maximum magnitude detected by the `analysis.ClearCut` algorithm. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_B = analysis.SitsPlotter(ts_S2.indices, \"NDMI\",\n",
    "                              daterange,\n",
    "                              break_date=datetime(2021, 1, 1),\n",
    "                              coords=point_B[\"coord_3035\"],\n",
    "                              ylim=[-0.25, 0.80],\n",
    "                              filter_method=\"sigma\",\n",
    "                              filter_value=1.5)\n",
    "\n",
    "plot_B.plot_model(degree=3, include_trend=True, envelope_quantiles=(0.05, 0.95))\n",
    "plot_B.run_detection(thresholds=[0.25, 0.35, 0.45])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The class also supports exporting plots directly to PNG files if needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'test_data/sits_NDMI.png'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_B.save_plot(out_dir)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": [
    {
     "file_id": "https://github.com/kenoz/SITS_utils/blob/main/examples/colab_sits_ex02.ipynb",
     "timestamp": 1738147041012
    }
   ]
  },
  "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": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}