adjust_retrieve_data.ipynb

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   "id": "67fe1f80-db9e-4b5f-be1b-5ab3dea1f6f6",
   "metadata": {
    "tags": []
   },
   "source": [
    "# ATMOS 2022 - Adjust and Retrieve Datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd626f62-ddbe-4db9-b0dc-ae5e4a6fbca2",
   "metadata": {},
   "source": [
    "-----------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2855e138-02ec-4e29-94bf-41ed6b827cb8",
   "metadata": {},
   "source": [
    "## 0. Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "38a775d7-3957-40fa-b583-1ea6c0782a4c",
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   "outputs": [],
   "source": [
    "from utils.data import *\n",
    "from utils.utils import *\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%reload_ext autoreload"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b269ee0-eb47-486a-9809-26bc8e4215a7",
   "metadata": {},
   "source": [
    "## 1. Dmsp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "48d10d9d-511d-4336-851e-880bccc021ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'izmir'\n",
    "dt = retrieve_dmsp(province)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "383c5d7c-e24c-4629-b955-cf63711058e8",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 22, y: 189, x: 273)&gt;\n",
       "array([[[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
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       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
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       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)\n",
       "Coordinates:\n",
       "  * y            (y) float64 39.39 39.38 39.38 39.37 ... 37.85 37.84 37.83 37.83\n",
       "  * x            (x) float64 26.23 26.24 26.25 26.26 ... 28.47 28.48 28.49 28.5\n",
       "    band         int64 1\n",
       "  * time         (time) int64 1992 1993 1994 1995 1996 ... 2010 2011 2012 2013\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  1.0\n",
       "    add_offset:    0.0\n",
       "    data-source:   dmsp\n",
       "    province:      izmir</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 22</li><li><span class='xr-has-index'>y</span>: 189</li><li><span class='xr-has-index'>x</span>: 273</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5f0054ae-37d0-481a-9efe-b0f44c16d630' class='xr-array-in' type='checkbox' checked><label for='section-5f0054ae-37d0-481a-9efe-b0f44c16d630' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0</span></div><div class='xr-array-data'><pre>array([[[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
       "...\n",
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       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)</pre></div></div></li><li class='xr-section-item'><input id='section-a9634eb2-d99a-4c41-bf1f-1487bb848fc8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9634eb2-d99a-4c41-bf1f-1487bb848fc8' class='xr-section-summary' >Coordinates: <span>(5)</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'>39.39 39.38 39.38 ... 37.83 37.83</div><input id='attrs-d08d04ae-5e7f-4bc1-94f0-b4cecdda4d00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d08d04ae-5e7f-4bc1-94f0-b4cecdda4d00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34787dcd-16cd-454d-bb9b-28325993ea7f' class='xr-var-data-in' type='checkbox'><label for='data-34787dcd-16cd-454d-bb9b-28325993ea7f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([39.391667, 39.383333, 39.375   , 39.366667, 39.358333, 39.35    ,\n",
       "       39.341667, 39.333333, 39.325   , 39.316667, 39.308333, 39.3     ,\n",
       "       39.291667, 39.283333, 39.275   , 39.266667, 39.258333, 39.25    ,\n",
       "       39.241667, 39.233333, 39.225   , 39.216667, 39.208333, 39.2     ,\n",
       "       39.191667, 39.183333, 39.175   , 39.166667, 39.158333, 39.15    ,\n",
       "       39.141667, 39.133333, 39.125   , 39.116667, 39.108333, 39.1     ,\n",
       "       39.091667, 39.083333, 39.075   , 39.066667, 39.058333, 39.05    ,\n",
       "       39.041667, 39.033333, 39.025   , 39.016667, 39.008333, 39.      ,\n",
       "       38.991667, 38.983333, 38.975   , 38.966667, 38.958333, 38.95    ,\n",
       "       38.941667, 38.933333, 38.925   , 38.916667, 38.908333, 38.9     ,\n",
       "       38.891667, 38.883333, 38.875   , 38.866667, 38.858333, 38.85    ,\n",
       "       38.841667, 38.833333, 38.825   , 38.816667, 38.808333, 38.8     ,\n",
       "       38.791667, 38.783333, 38.775   , 38.766667, 38.758333, 38.75    ,\n",
       "       38.741667, 38.733333, 38.725   , 38.716667, 38.708333, 38.7     ,\n",
       "       38.691667, 38.683333, 38.675   , 38.666667, 38.658333, 38.65    ,\n",
       "       38.641667, 38.633333, 38.625   , 38.616667, 38.608333, 38.6     ,\n",
       "       38.591667, 38.583333, 38.575   , 38.566667, 38.558333, 38.55    ,\n",
       "       38.541667, 38.533333, 38.525   , 38.516667, 38.508333, 38.5     ,\n",
       "       38.491667, 38.483333, 38.475   , 38.466667, 38.458333, 38.45    ,\n",
       "       38.441667, 38.433333, 38.425   , 38.416667, 38.408333, 38.4     ,\n",
       "       38.391667, 38.383333, 38.375   , 38.366667, 38.358333, 38.35    ,\n",
       "       38.341667, 38.333333, 38.325   , 38.316667, 38.308333, 38.3     ,\n",
       "       38.291667, 38.283333, 38.275   , 38.266667, 38.258333, 38.25    ,\n",
       "       38.241667, 38.233333, 38.225   , 38.216667, 38.208333, 38.2     ,\n",
       "       38.191667, 38.183333, 38.175   , 38.166667, 38.158333, 38.15    ,\n",
       "       38.141667, 38.133333, 38.125   , 38.116667, 38.108333, 38.1     ,\n",
       "       38.091667, 38.083333, 38.075   , 38.066667, 38.058333, 38.05    ,\n",
       "       38.041667, 38.033333, 38.025   , 38.016667, 38.008333, 38.      ,\n",
       "       37.991667, 37.983333, 37.975   , 37.966667, 37.958333, 37.95    ,\n",
       "       37.941667, 37.933333, 37.925   , 37.916667, 37.908333, 37.9     ,\n",
       "       37.891667, 37.883333, 37.875   , 37.866667, 37.858333, 37.85    ,\n",
       "       37.841667, 37.833333, 37.825   ])</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'>26.23 26.24 26.25 ... 28.49 28.5</div><input id='attrs-6c2fc4d8-dc0f-4f35-8159-9af7dac4b69b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c2fc4d8-dc0f-4f35-8159-9af7dac4b69b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-651cb3a3-4a0b-4417-80cd-9ffddd76d175' class='xr-var-data-in' type='checkbox'><label for='data-651cb3a3-4a0b-4417-80cd-9ffddd76d175' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([26.233333, 26.241666, 26.249999, ..., 28.483332, 28.491666, 28.499999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-f44eefc1-781e-41c5-b76d-96b846ffa214' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f44eefc1-781e-41c5-b76d-96b846ffa214' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34a2a3b2-f52e-4892-a2cf-4788cfab02e5' class='xr-var-data-in' type='checkbox'><label for='data-34a2a3b2-f52e-4892-a2cf-4788cfab02e5' 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(1)</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'>int64</div><div class='xr-var-preview xr-preview'>1992 1993 1994 ... 2011 2012 2013</div><input id='attrs-2acc4311-fb95-4028-bb21-84fd772d2396' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acc4311-fb95-4028-bb21-84fd772d2396' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7792f55c-9477-4c16-a784-442ff0f3a879' class='xr-var-data-in' type='checkbox'><label for='data-7792f55c-9477-4c16-a784-442ff0f3a879' 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([1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,\n",
       "       2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013])</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-2c0cb666-6031-410f-b253-c95c3fe4859e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c0cb666-6031-410f-b253-c95c3fe4859e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-762c74d7-d954-4c33-89cc-dbc41f302b90' class='xr-var-data-in' type='checkbox'><label for='data-762c74d7-d954-4c33-89cc-dbc41f302b90' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>26.229165841750024 0.008333333299999942 0.0 39.395833475749996 0.0 -0.008333333299999976</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-015b2536-7c2d-4639-bf14-dcb4df57da1b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-015b2536-7c2d-4639-bf14-dcb4df57da1b' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>data-source :</span></dt><dd>dmsp</dd><dt><span>province :</span></dt><dd>izmir</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 22, y: 189, x: 273)>\n",
       "array([[[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 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],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)\n",
       "Coordinates:\n",
       "  * y            (y) float64 39.39 39.38 39.38 39.37 ... 37.85 37.84 37.83 37.83\n",
       "  * x            (x) float64 26.23 26.24 26.25 26.26 ... 28.47 28.48 28.49 28.5\n",
       "    band         int64 1\n",
       "  * time         (time) int64 1992 1993 1994 1995 1996 ... 2010 2011 2012 2013\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  1.0\n",
       "    add_offset:    0.0\n",
       "    data-source:   dmsp\n",
       "    province:      izmir"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "18f61879-ad96-428b-98e8-4aa6af5dd756",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f6eaf4f3fd0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt[0].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f74dccce-e3f2-480a-8250-f406dc538f1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f6eaf3acc70>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt[-1].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fea90da-0630-4583-a9d3-6ca97a1048fa",
   "metadata": {},
   "source": [
    "-----------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "969aff58-aae5-4b94-9e2b-3763d0769c40",
   "metadata": {},
   "source": [
    "## 2. Population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "96e824a9-b468-4b9c-a443-f62355de503e",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'izmir'\n",
    "dt = retrieve_population(province)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "41de5aae-be78-487e-85b8-7a60db893124",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Province</th>\n",
       "      <th>2000</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
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       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
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       "      <th>2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>izmir</td>\n",
       "      <td>3431204</td>\n",
       "      <td>3477209</td>\n",
       "      <td>3519233</td>\n",
       "      <td>3560544</td>\n",
       "      <td>3603838</td>\n",
       "      <td>3648575</td>\n",
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       "      <td>3739353</td>\n",
       "      <td>3795978</td>\n",
       "      <td>...</td>\n",
       "      <td>3948848</td>\n",
       "      <td>3965232</td>\n",
       "      <td>4005459</td>\n",
       "      <td>4061074</td>\n",
       "      <td>4113072</td>\n",
       "      <td>4168415</td>\n",
       "      <td>4223545</td>\n",
       "      <td>4279677</td>\n",
       "      <td>4320519</td>\n",
       "      <td>4367251</td>\n",
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       "<p>1 rows × 21 columns</p>\n",
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       "  Province     2000     2001     2002     2003     2004     2005     2006  \\\n",
       "0    izmir  3431204  3477209  3519233  3560544  3603838  3648575  3694316   \n",
       "\n",
       "      2007     2008  ...     2010     2011     2012     2013     2014  \\\n",
       "0  3739353  3795978  ...  3948848  3965232  4005459  4061074  4113072   \n",
       "\n",
       "      2015     2016     2017     2018     2019  \n",
       "0  4168415  4223545  4279677  4320519  4367251  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "dt"
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  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "59811101-41fc-4b38-ad16-c0979a268597",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data-source': 'population', 'province': 'istanbul'}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
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    "dt.attrs"
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  {
   "cell_type": "markdown",
   "id": "b457d3c9-4492-4c69-98d6-570a4a3df23e",
   "metadata": {},
   "source": [
    "-------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cfcc796-44c2-4529-a500-78cd8c282ee8",
   "metadata": {},
   "source": [
    "## 3. Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7f12b5ae-f559-477f-8fb6-73a88c0b1ac0",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'istanbul'\n",
    "dt = retrieve_station(province)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1eb66a5e-ec18-47e5-8e8e-5960abc49ec6",
   "metadata": {},
   "outputs": [
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       "      <td>4</td>\n",
       "      <td>-2.5</td>\n",
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       "      <th>87643</th>\n",
       "      <td>2018</td>\n",
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       "      <td>5.1</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.2</td>\n",
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      "text/plain": [
       "       İSTANBUL  Month  Day  Hour  17047  17059  17060  17061  17062  17063  \\\n",
       "0          2009      1    1     0   -0.6    4.5    1.8    2.8    2.7    0.9   \n",
       "1          2009      1    1     1   -1.8    4.2    0.4    3.0    2.8    0.9   \n",
       "2          2009      1    1     2   -2.1    4.3    0.5    2.2    2.7    1.0   \n",
       "3          2009      1    1     3   -2.3    3.9    0.5    2.1    2.4    1.0   \n",
       "4          2009      1    1     4   -2.5    2.5    0.6    1.2    2.0    1.1   \n",
       "...         ...    ...  ...   ...    ...    ...    ...    ...    ...    ...   \n",
       "87643      2018     12   31    19    2.5    6.7    6.7    4.9    6.3    3.7   \n",
       "87644      2018     12   31    20    2.6    4.1    6.3    5.1    6.0    3.6   \n",
       "87645      2018     12   31    21    2.8    3.2    6.1    5.0    5.9    2.9   \n",
       "87646      2018     12   31    22    2.4    3.4    6.2    4.7    5.7    2.0   \n",
       "87647      2018     12   31    23    2.4    2.7    6.0    5.0    5.4    1.5   \n",
       "\n",
       "       17064  17065  17603  17610  17636  \n",
       "0        2.8    1.0    3.1    0.9    1.9  \n",
       "1        2.5    1.1    3.0    1.0    0.9  \n",
       "2        2.8    0.8    2.4    1.1    0.4  \n",
       "3        3.1    1.0    1.9    1.1    0.7  \n",
       "4        2.9    0.7    1.7    1.0    0.4  \n",
       "...      ...    ...    ...    ...    ...  \n",
       "87643    5.0    4.1    5.6    5.0    5.6  \n",
       "87644    4.5    3.7    5.3    5.2    5.5  \n",
       "87645    4.3    3.4    5.0    4.9    5.4  \n",
       "87646    4.0    2.6    5.0    4.8    5.5  \n",
       "87647    4.0    2.7    5.1    4.7    5.2  \n",
       "\n",
       "[87648 rows x 15 columns]"
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     },
     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "dt"
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  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ce6b32ab-f32a-4afa-bfde-1d185c49f06d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data-source': 'station',\n",
       " 'var-name': 'T',\n",
       " 'unit': 'degC',\n",
       " 'province': 'izmir'}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.attrs"
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  },
  {
   "cell_type": "markdown",
   "id": "a6b3ca3d-8a8f-4d81-8615-ac6613c519b0",
   "metadata": {},
   "source": [
    "----------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd317b2d-4875-42cd-a655-3acf9ee43683",
   "metadata": {},
   "source": [
    "## 4. Corine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8bbd9f6f-d75f-417c-ae0e-95ae19e28e18",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'izmir'\n",
    "dt = retrieve_corine(province)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4422ac59-baf7-4479-8852-8bc8dad29e3d",
   "metadata": {},
   "outputs": [
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       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\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",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 4, y: 1687, x: 1968)&gt;\n",
       "dask.array&lt;where, shape=(4, 1687, 1968), dtype=float64, chunksize=(1, 1687, 1012), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * y            (y) float64 1.982e+06 1.982e+06 ... 1.813e+06 1.813e+06\n",
       "  * x            (x) float64 5.739e+06 5.739e+06 ... 5.935e+06 5.936e+06\n",
       "    band         int64 1\n",
       "  * time         (time) int64 1990 2000 2012 2018\n",
       "    spatial_ref  int64 0\n",
       "Attributes: (12/13)\n",
       "    RepresentationType:      THEMATIC\n",
       "    STATISTICS_COVARIANCES:  139.8656147919413\n",
       "    STATISTICS_MAXIMUM:      48\n",
       "    STATISTICS_MEAN:         24.548340358237\n",
       "    STATISTICS_MINIMUM:      1\n",
       "    STATISTICS_SKIPFACTORX:  1\n",
       "    ...                      ...\n",
       "    STATISTICS_STDDEV:       11.826479391262\n",
       "    scale_factor:            1.0\n",
       "    add_offset:              0.0\n",
       "    data-source:             corine\n",
       "    province:                izmir\n",
       "    _FillValue:              -128</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4</li><li><span class='xr-has-index'>y</span>: 1687</li><li><span class='xr-has-index'>x</span>: 1968</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b9bd6b28-4845-4e5c-ac84-74977a0ec6aa' class='xr-array-in' type='checkbox' checked><label for='section-b9bd6b28-4845-4e5c-ac84-74977a0ec6aa' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1687, 1012), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\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> 101.32 MiB </td>\n",
       "                        <td> 13.03 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (4, 1687, 1968) </td>\n",
       "                        <td> (1, 1687, 1012) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3621 Tasks </td>\n",
       "                        <td> 8 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"194\" height=\"167\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"102\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"106\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"110\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"114\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"117\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 24.9485979497544,14.948597949754403 24.9485979497544,117.81445160829097 10.0,102.86585365853657\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"133\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"137\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"141\" y2=\"11\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"86\" y2=\"14\" />\n",
       "  <line x1=\"130\" y1=\"0\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"144\" y2=\"14\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"117\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"144\" y1=\"14\" x2=\"144\" y2=\"117\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"24.9485979497544,14.948597949754403 144.9485979497544,14.948597949754403 144.9485979497544,117.81445160829097 24.9485979497544,117.81445160829097\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"84.948598\" y=\"137.814452\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1968</text>\n",
       "  <text x=\"164.948598\" y=\"66.381525\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,164.948598,66.381525)\">1687</text>\n",
       "  <text x=\"7.474299\" y=\"130.340153\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,7.474299,130.340153)\">4</text>\n",
       "</svg>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-713c832d-6087-437a-a04a-a7ec441b7be5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-713c832d-6087-437a-a04a-a7ec441b7be5' class='xr-section-summary' >Coordinates: <span>(5)</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'>1.982e+06 1.982e+06 ... 1.813e+06</div><input id='attrs-69965c2c-efa8-42e8-b204-e264bdfe88ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69965c2c-efa8-42e8-b204-e264bdfe88ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed3c899d-24ab-4398-91fa-7f4e95f35f0e' class='xr-var-data-in' type='checkbox'><label for='data-ed3c899d-24ab-4398-91fa-7f4e95f35f0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([1981850., 1981750., 1981650., ..., 1813450., 1813350., 1813250.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.739e+06 5.739e+06 ... 5.936e+06</div><input id='attrs-f37183a4-1745-48d2-b1a3-4f4d593a8536' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f37183a4-1745-48d2-b1a3-4f4d593a8536' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e02362d7-8a46-4df7-95f6-b2945a09f4ae' class='xr-var-data-in' type='checkbox'><label for='data-e02362d7-8a46-4df7-95f6-b2945a09f4ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([5738850., 5738950., 5739050., ..., 5935350., 5935450., 5935550.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-38ac1463-c382-488b-9f1f-cd00f85d5c6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38ac1463-c382-488b-9f1f-cd00f85d5c6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-640439f8-eeff-45bd-b95b-c74a72e5d583' class='xr-var-data-in' type='checkbox'><label for='data-640439f8-eeff-45bd-b95b-c74a72e5d583' 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(1)</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'>int64</div><div class='xr-var-preview xr-preview'>1990 2000 2012 2018</div><input id='attrs-aa0a2622-8461-4c2b-9774-fd7e96a500d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa0a2622-8461-4c2b-9774-fd7e96a500d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1e67d56-c2b4-4afb-bd3b-01c3de4f4df2' class='xr-var-data-in' type='checkbox'><label for='data-b1e67d56-c2b4-4afb-bd3b-01c3de4f4df2' 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([1990, 2000, 2012, 2018])</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-7c7e0311-af42-43cc-bec4-2363cf5e4939' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c7e0311-af42-43cc-bec4-2363cf5e4939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4cbabd8-9d97-446f-9f43-e743d34fb7c6' class='xr-var-data-in' type='checkbox'><label for='data-b4cbabd8-9d97-446f-9f43-e743d34fb7c6' 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;ETRS_1989_LAEA&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101004,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0],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],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],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>298.257222101004</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>ETRS_1989_LAEA</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;ETRS_1989_LAEA&quot;,GEOGCS[&quot;ETRS89&quot;,DATUM[&quot;European_Terrestrial_Reference_System_1989&quot;,SPHEROID[&quot;GRS 1980&quot;,6378137,298.257222101004,AUTHORITY[&quot;EPSG&quot;,&quot;7019&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6258&quot;]],PRIMEM[&quot;Greenwich&quot;,0],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],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;3035&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>5738800.0 100.0 0.0 1981900.0 0.0 -100.0</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-cf3ca786-01b9-4aef-ab43-d140683b47ae' class='xr-section-summary-in' type='checkbox'  ><label for='section-cf3ca786-01b9-4aef-ab43-d140683b47ae' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>RepresentationType :</span></dt><dd>THEMATIC</dd><dt><span>STATISTICS_COVARIANCES :</span></dt><dd>139.8656147919413</dd><dt><span>STATISTICS_MAXIMUM :</span></dt><dd>48</dd><dt><span>STATISTICS_MEAN :</span></dt><dd>24.548340358237</dd><dt><span>STATISTICS_MINIMUM :</span></dt><dd>1</dd><dt><span>STATISTICS_SKIPFACTORX :</span></dt><dd>1</dd><dt><span>STATISTICS_SKIPFACTORY :</span></dt><dd>1</dd><dt><span>STATISTICS_STDDEV :</span></dt><dd>11.826479391262</dd><dt><span>scale_factor :</span></dt><dd>1.0</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>data-source :</span></dt><dd>corine</dd><dt><span>province :</span></dt><dd>izmir</dd><dt><span>_FillValue :</span></dt><dd>-128</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 4, y: 1687, x: 1968)>\n",
       "dask.array<where, shape=(4, 1687, 1968), dtype=float64, chunksize=(1, 1687, 1012), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * y            (y) float64 1.982e+06 1.982e+06 ... 1.813e+06 1.813e+06\n",
       "  * x            (x) float64 5.739e+06 5.739e+06 ... 5.935e+06 5.936e+06\n",
       "    band         int64 1\n",
       "  * time         (time) int64 1990 2000 2012 2018\n",
       "    spatial_ref  int64 0\n",
       "Attributes: (12/13)\n",
       "    RepresentationType:      THEMATIC\n",
       "    STATISTICS_COVARIANCES:  139.8656147919413\n",
       "    STATISTICS_MAXIMUM:      48\n",
       "    STATISTICS_MEAN:         24.548340358237\n",
       "    STATISTICS_MINIMUM:      1\n",
       "    STATISTICS_SKIPFACTORX:  1\n",
       "    ...                      ...\n",
       "    STATISTICS_STDDEV:       11.826479391262\n",
       "    scale_factor:            1.0\n",
       "    add_offset:              0.0\n",
       "    data-source:             corine\n",
       "    province:                izmir\n",
       "    _FillValue:              -128"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e7293073-c3d0-4a7f-9380-f4cc709904a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f6ea76e1370>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt[-1].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b7a8913-8392-48d6-b70a-a03250712ba1",
   "metadata": {},
   "source": [
    "## 5. Modis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "009b37b6-041c-44e2-8ada-d18034696860",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'ankara'\n",
    "source_type = 'aqua'\n",
    "dt = retrieve_modis(province, source_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "496aa07d-6aea-48ff-baaf-12b319ed9762",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\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",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (y: 282, time: 2922, x: 369)\n",
       "Coordinates:\n",
       "  * y            (y) float64 4.688e+06 4.689e+06 ... 4.947e+06 4.948e+06\n",
       "  * time         (time) datetime64[ns] 2011-01-01 2011-01-02 ... 2018-12-31\n",
       "  * x            (x) float64 3.431e+06 3.432e+06 ... 3.771e+06 3.772e+06\n",
       "    band         int64 1\n",
       "    spatial_ref  int64 0\n",
       "Data variables:\n",
       "    LST_Day_1km  (time, y, x) float32 dask.array&lt;chunksize=(1, 282, 369), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d99d306a-9a40-4003-9d9a-e0dc59c0b53b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d99d306a-9a40-4003-9d9a-e0dc59c0b53b' 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>: 282</li><li><span class='xr-has-index'>time</span>: 2922</li><li><span class='xr-has-index'>x</span>: 369</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5e581535-5522-4f98-95bf-65909610b012' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e581535-5522-4f98-95bf-65909610b012' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.688e+06 4.689e+06 ... 4.948e+06</div><input id='attrs-572a6ba3-30b5-447f-bbaa-8a628ac643d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-572a6ba3-30b5-447f-bbaa-8a628ac643d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af72e5f2-3dc1-4b5a-9ad6-f7f684e16c9e' class='xr-var-data-in' type='checkbox'><label for='data-af72e5f2-3dc1-4b5a-9ad6-f7f684e16c9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([4688274.383346, 4689199.575961, 4690124.768576, ..., 4946403.123009,\n",
       "       4947328.315625, 4948253.50824 ])</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'>2011-01-01 ... 2018-12-31</div><input id='attrs-da29e3d5-2c05-4f64-a801-6cf1fc689f8d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da29e3d5-2c05-4f64-a801-6cf1fc689f8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f8c213c-965e-4ba2-9315-d32e2712d2f0' class='xr-var-data-in' type='checkbox'><label for='data-3f8c213c-965e-4ba2-9315-d32e2712d2f0' 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;2011-01-01T00:00:00.000000000&#x27;, &#x27;2011-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-03T00:00:00.000000000&#x27;, ..., &#x27;2018-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-12-30T00:00:00.000000000&#x27;, &#x27;2018-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.431e+06 3.432e+06 ... 3.772e+06</div><input id='attrs-2b508bba-aa94-4425-9d87-06cca3e1cd41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b508bba-aa94-4425-9d87-06cca3e1cd41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06558d3d-e7ad-4e9f-b206-ed6fc3239577' class='xr-var-data-in' type='checkbox'><label for='data-06558d3d-e7ad-4e9f-b206-ed6fc3239577' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([3431329.608667, 3432255.413503, 3433181.218339, ..., 3770174.178583,\n",
       "       3771099.983419, 3772025.788255])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-fdb1bded-01ea-4d63-9cd0-21216d161fc1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fdb1bded-01ea-4d63-9cd0-21216d161fc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f81f6de-4e47-4f2d-9e90-cb7e9c475450' class='xr-var-data-in' type='checkbox'><label for='data-9f81f6de-4e47-4f2d-9e90-cb7e9c475450' 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(1)</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-b3aa5ab6-7234-47ba-a069-dc88bd43743c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3aa5ab6-7234-47ba-a069-dc88bd43743c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e225574d-a8b4-442a-9b25-7937542f0464' class='xr-var-data-in' type='checkbox'><label for='data-e225574d-a8b4-442a-9b25-7937542f0464' 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;unnamed&quot;,GEOGCS[&quot;Unknown datum based upon the custom spheroid&quot;,DATUM[&quot;Not specified (based on custom spheroid)&quot;,SPHEROID[&quot;Custom spheroid&quot;,6378137,298.25722356049]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Mercator_1SP&quot;],PARAMETER[&quot;central_meridian&quot;,0],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;Meter&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245</dd><dt><span>inverse_flattening :</span></dt><dd>298.25722356049</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Custom spheroid</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>Unknown datum based upon the custom spheroid</dd><dt><span>horizontal_datum_name :</span></dt><dd>Not specified (based on custom spheroid)</dd><dt><span>projected_crs_name :</span></dt><dd>unnamed</dd><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>standard_parallel :</span></dt><dd>0.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_projection_origin :</span></dt><dd>1.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unnamed&quot;,GEOGCS[&quot;Unknown datum based upon the custom spheroid&quot;,DATUM[&quot;Not specified (based on custom spheroid)&quot;,SPHEROID[&quot;Custom spheroid&quot;,6378137,298.25722356049]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Mercator_1SP&quot;],PARAMETER[&quot;central_meridian&quot;,0],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;Meter&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>3430866.706249 925.804835837399 0.0 4948716.104547436 0.0 -925.1926152816877</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-c5d52160-52b3-49ce-9f56-4c89385620f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c5d52160-52b3-49ce-9f56-4c89385620f8' class='xr-section-summary' >Data variables: <span>(1)</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>LST_Day_1km</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, 282, 369), meta=np.ndarray&gt;</div><input id='attrs-b294e189-9a15-4b61-a420-fb6bfe721b31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b294e189-9a15-4b61-a420-fb6bfe721b31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccfc0203-acf3-4816-9a1c-4180fb3f5358' class='xr-var-data-in' type='checkbox'><label for='data-ccfc0203-acf3-4816-9a1c-4180fb3f5358' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\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> 1.13 GiB </td>\n",
       "                        <td> 812.95 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2922, 282, 369) </td>\n",
       "                        <td> (2, 282, 369) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 64269 Tasks </td>\n",
       "                        <td> 2921 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"158\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"38\" x2=\"80\" y2=\"108\" style=\"stroke-width:2\" />\n",
       "\n",
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     "execution_count": 5,
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    "dt"
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   "source": [
    "## 6. Modis - Merged"
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   "execution_count": 10,
   "id": "d5f9cca6-98a4-42ca-b2e1-61b38fdcc6de",
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   "outputs": [],
   "source": [
    "province = 'istanbul'\n",
    "source_type = 'terra'\n",
    "dt = retrieve_modis_merged(province, source_type)"
   ]
  },
  {
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   "execution_count": 12,
   "id": "da70a76f-2f6f-4ed7-b1e4-db9221f7965a",
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       "Coordinates:\n",
       "  * y            (y) float64 5.071e+06 5.07e+06 ... 4.957e+06 4.956e+06\n",
       "  * x            (x) float64 3.117e+06 3.118e+06 ... 3.33e+06 3.331e+06\n",
       "    band         int64 1\n",
       "  * time         (time) datetime64[ns] 2011-01-01 2011-01-02 ... 2018-12-31\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    grid_mapping:  spatial_ref</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'LST_Day_1km'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2899</li><li><span class='xr-has-index'>y</span>: 125</li><li><span class='xr-has-index'>x</span>: 231</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6df8bf98-2668-4f86-827d-4db47cfda371' class='xr-array-in' type='checkbox' checked><label for='section-6df8bf98-2668-4f86-827d-4db47cfda371' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[83708625 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-02c520ab-e010-464e-96b1-4aedddbe7a36' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02c520ab-e010-464e-96b1-4aedddbe7a36' class='xr-section-summary' >Coordinates: <span>(5)</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'>5.071e+06 5.07e+06 ... 4.956e+06</div><input id='attrs-12773f42-0c74-4c26-815e-7aeb7ce04245' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12773f42-0c74-4c26-815e-7aeb7ce04245' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9040a2de-4e7d-42c5-b64c-1edcf15adf2b' class='xr-var-data-in' type='checkbox'><label for='data-9040a2de-4e7d-42c5-b64c-1edcf15adf2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([5070584.720368, 5069658.791299, 5068732.86223 , 5067806.933161,\n",
       "       5066881.004092, 5065955.075023, 5065029.145953, 5064103.216884,\n",
       "       5063177.287815, 5062251.358746, 5061325.429677, 5060399.500608,\n",
       "       5059473.571539, 5058547.642469, 5057621.7134  , 5056695.784331,\n",
       "       5055769.855262, 5054843.926193, 5053917.997124, 5052992.068054,\n",
       "       5052066.138985, 5051140.209916, 5050214.280847, 5049288.351778,\n",
       "       5048362.422709, 5047436.493639, 5046510.56457 , 5045584.635501,\n",
       "       5044658.706432, 5043732.777363, 5042806.848294, 5041880.919224,\n",
       "       5040954.990155, 5040029.061086, 5039103.132017, 5038177.202948,\n",
       "       5037251.273879, 5036325.344809, 5035399.41574 , 5034473.486671,\n",
       "       5033547.557602, 5032621.628533, 5031695.699464, 5030769.770394,\n",
       "       5029843.841325, 5028917.912256, 5027991.983187, 5027066.054118,\n",
       "       5026140.125049, 5025214.195979, 5024288.26691 , 5023362.337841,\n",
       "       5022436.408772, 5021510.479703, 5020584.550634, 5019658.621564,\n",
       "       5018732.692495, 5017806.763426, 5016880.834357, 5015954.905288,\n",
       "       5015028.976219, 5014103.047149, 5013177.11808 , 5012251.189011,\n",
       "       5011325.259942, 5010399.330873, 5009473.401804, 5008547.472735,\n",
       "       5007621.543665, 5006695.614596, 5005769.685527, 5004843.756458,\n",
       "       5003917.827389, 5002991.89832 , 5002065.96925 , 5001140.040181,\n",
       "       5000214.111112, 4999288.182043, 4998362.252974, 4997436.323905,\n",
       "       4996510.394835, 4995584.465766, 4994658.536697, 4993732.607628,\n",
       "       4992806.678559, 4991880.74949 , 4990954.82042 , 4990028.891351,\n",
       "       4989102.962282, 4988177.033213, 4987251.104144, 4986325.175075,\n",
       "       4985399.246005, 4984473.316936, 4983547.387867, 4982621.458798,\n",
       "       4981695.529729, 4980769.60066 , 4979843.67159 , 4978917.742521,\n",
       "       4977991.813452, 4977065.884383, 4976139.955314, 4975214.026245,\n",
       "       4974288.097175, 4973362.168106, 4972436.239037, 4971510.309968,\n",
       "       4970584.380899, 4969658.45183 , 4968732.52276 , 4967806.593691,\n",
       "       4966880.664622, 4965954.735553, 4965028.806484, 4964102.877415,\n",
       "       4963176.948346, 4962251.019276, 4961325.090207, 4960399.161138,\n",
       "       4959473.232069, 4958547.303   , 4957621.373931, 4956695.444861,\n",
       "       4955769.515792])</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'>3.117e+06 3.118e+06 ... 3.331e+06</div><input id='attrs-042e70b6-0860-464b-b907-afe4444b7dcd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-042e70b6-0860-464b-b907-afe4444b7dcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88f60bc-457d-41d7-be31-9e8c199283a8' class='xr-var-data-in' type='checkbox'><label for='data-f88f60bc-457d-41d7-be31-9e8c199283a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([3117409.304981, 3118336.43052 , 3119263.556059, ..., 3328793.927794,\n",
       "       3329721.053332, 3330648.178871])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-26b47215-49cd-4d03-bf25-a3e97b2a7b46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26b47215-49cd-4d03-bf25-a3e97b2a7b46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e798bc5-4c3f-4f6a-ac60-0a79df533cac' class='xr-var-data-in' type='checkbox'><label for='data-4e798bc5-4c3f-4f6a-ac60-0a79df533cac' 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(1)</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'>2011-01-01 ... 2018-12-31</div><input id='attrs-2c07e60e-9982-4f08-9f55-62cd8f8be132' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c07e60e-9982-4f08-9f55-62cd8f8be132' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ff3fbb0-1a9f-46fb-ba7b-2938a81c38ca' class='xr-var-data-in' type='checkbox'><label for='data-0ff3fbb0-1a9f-46fb-ba7b-2938a81c38ca' 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;2011-01-01T00:00:00.000000000&#x27;, &#x27;2011-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-01-03T00:00:00.000000000&#x27;, ..., &#x27;2018-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-12-30T00:00:00.000000000&#x27;, &#x27;2018-12-31T00:00:00.000000000&#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-9fd28d7b-d673-4c09-8b4e-59b89705acdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fd28d7b-d673-4c09-8b4e-59b89705acdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a03946d-4d5d-4b76-a6c7-722ee52a95dd' class='xr-var-data-in' type='checkbox'><label for='data-0a03946d-4d5d-4b76-a6c7-722ee52a95dd' 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;unnamed&quot;,GEOGCS[&quot;Unknown datum based upon the custom spheroid&quot;,DATUM[&quot;Not specified (based on custom spheroid)&quot;,SPHEROID[&quot;Custom spheroid&quot;,6378137,298.25722356049]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Mercator_1SP&quot;],PARAMETER[&quot;central_meridian&quot;,0],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;Meter&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245</dd><dt><span>inverse_flattening :</span></dt><dd>298.25722356049</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Custom spheroid</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>Unknown datum based upon the custom spheroid</dd><dt><span>horizontal_datum_name :</span></dt><dd>Not specified (based on custom spheroid)</dd><dt><span>projected_crs_name :</span></dt><dd>unnamed</dd><dt><span>grid_mapping_name :</span></dt><dd>mercator</dd><dt><span>standard_parallel :</span></dt><dd>0.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_projection_origin :</span></dt><dd>1.0</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;unnamed&quot;,GEOGCS[&quot;Unknown datum based upon the custom spheroid&quot;,DATUM[&quot;Not specified (based on custom spheroid)&quot;,SPHEROID[&quot;Custom spheroid&quot;,6378137,298.25722356049]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]]],PROJECTION[&quot;Mercator_1SP&quot;],PARAMETER[&quot;central_meridian&quot;,0],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,0],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;Meter&quot;,1],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</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-7354f541-f5be-458b-b567-c9e074a7b46c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7354f541-f5be-458b-b567-c9e074a7b46c' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'LST_Day_1km' (time: 2899, y: 125, x: 231)>\n",
       "[83708625 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * y            (y) float64 5.071e+06 5.07e+06 ... 4.957e+06 4.956e+06\n",
       "  * x            (x) float64 3.117e+06 3.118e+06 ... 3.33e+06 3.331e+06\n",
       "    band         int64 ...\n",
       "  * time         (time) datetime64[ns] 2011-01-01 2011-01-02 ... 2018-12-31\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    grid_mapping:  spatial_ref"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7439f76c-47aa-4dc1-bdc7-95d8bdaa7b85",
   "metadata": {},
   "source": [
    "## 7. GHS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0a5c8526-50b3-4f9f-946d-ff40a1736fd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "province = 'ankara'\n",
    "dt = retrieve_ghs(province)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "db632c37-4c83-42da-9b44-a59c669103f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f9db09c1e50>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt.sel(time=2015).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "afc1ef4e-b1c8-459d-897e-b27155752a15",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}