SentinelSat_Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Search and Download Sentinel 2 imagery using Sentinelsat API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make sure all the libraries are installed below. Use conda if possible <br>\n",
    "For Sentinelsat use <br>\n",
    "<br>pip install sentinelsat \n",
    "<br>\n",
    "<br>\n",
    "At the conda prompt or at the cmd prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting help\n",
    "refer to the following links\n",
    "<br>\n",
    "sentinelsat git hub - https://github.com/sentinelsat/sentinelsat\n",
    "<br>\n",
    "sentinelsat API docs - https://sentinelsat.readthedocs.io/en/stable/api.html\n",
    "<br>\n",
    "<br>\n",
    "virtually everything you will see here has been borrowed or adpated from here, I've just added a bit of folium and unzipping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import folium\n",
    "from sentinelsat.sentinel import SentinelAPI, read_geojson, geojson_to_wkt\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot a boundary in WGS 84 EPSG code 4326 on a folium slipping map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x256eecfc2b0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = folium.Map([50.6, -1.3], zoom_start=10)\n",
    "boundsdata = r'D:\\sentinelsat\\bounds_IOW.geojson'\n",
    "folium.GeoJson(boundsdata).add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Connect to the API using a username and password - if you don't have these set one up on scihub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# connect to the API\n",
    "user = 'user' ## change this!\n",
    "password = 'password' ## change this!\n",
    "\n",
    "api = SentinelAPI(user, password, 'https://scihub.copernicus.eu/dhus')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POLYGON((-1.5905 50.7739,-1.5819 50.5371,-1.0038 50.5353,-1.0104 50.7757,-1.5905 50.7739))\n"
     ]
    }
   ],
   "source": [
    "# search by polygon\n",
    "footprint = geojson_to_wkt(read_geojson(boundsdata))\n",
    "\n",
    "print (footprint)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Search\n",
    "Search for images that fall with the date range 25th Feb 2019 - 27 Feb 2019, we want sentinel 2 level2A and cloud cover of 0-20%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "products = api.query(footprint,\n",
    "                     date = ('20190225', '20190227'),\n",
    "                     platformname = 'Sentinel-2',\n",
    "                     processinglevel = 'Level-2A',\n",
    "                     cloudcoverpercentage = (0, 20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n"
     ]
    }
   ],
   "source": [
    "print(len(products))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Show results in a table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>link</th>\n",
       "      <th>link_alternative</th>\n",
       "      <th>link_icon</th>\n",
       "      <th>summary</th>\n",
       "      <th>ingestiondate</th>\n",
       "      <th>beginposition</th>\n",
       "      <th>endposition</th>\n",
       "      <th>orbitnumber</th>\n",
       "      <th>relativeorbitnumber</th>\n",
       "      <th>...</th>\n",
       "      <th>platformidentifier</th>\n",
       "      <th>orbitdirection</th>\n",
       "      <th>platformserialidentifier</th>\n",
       "      <th>processingbaseline</th>\n",
       "      <th>processinglevel</th>\n",
       "      <th>producttype</th>\n",
       "      <th>platformname</th>\n",
       "      <th>size</th>\n",
       "      <th>uuid</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>09a3b3c8-1223-4133-9f2d-dbb8efd9028b</th>\n",
       "      <td>S2B_MSIL2A_20190226T111049_N0211_R137_T30UWA_2...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>Date: 2019-02-26T11:10:49.024Z, Instrument: MS...</td>\n",
       "      <td>2019-02-27 00:34:38.050</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>10316</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-013A</td>\n",
       "      <td>DESCENDING</td>\n",
       "      <td>Sentinel-2B</td>\n",
       "      <td>02.11</td>\n",
       "      <td>Level-2A</td>\n",
       "      <td>S2MSI2A</td>\n",
       "      <td>Sentinel-2</td>\n",
       "      <td>541.45 MB</td>\n",
       "      <td>09a3b3c8-1223-4133-9f2d-dbb8efd9028b</td>\n",
       "      <td>POLYGON ((-3.0002747 50.55229211062575, -1.450...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29625327-bc7a-44c4-be47-4cfa2828a760</th>\n",
       "      <td>S2B_MSIL2A_20190226T111049_N0211_R137_T30UXA_2...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>Date: 2019-02-26T11:10:49.024Z, Instrument: MS...</td>\n",
       "      <td>2019-02-27 00:34:30.848</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>10316</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-013A</td>\n",
       "      <td>DESCENDING</td>\n",
       "      <td>Sentinel-2B</td>\n",
       "      <td>02.11</td>\n",
       "      <td>Level-2A</td>\n",
       "      <td>S2MSI2A</td>\n",
       "      <td>Sentinel-2</td>\n",
       "      <td>481.23 MB</td>\n",
       "      <td>29625327-bc7a-44c4-be47-4cfa2828a760</td>\n",
       "      <td>POLYGON ((-1.5886536 50.54373917428845, -0.040...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30b9e88b-94a7-45ec-9ceb-4fa8bf86be04</th>\n",
       "      <td>S2B_MSIL2A_20190226T111049_N0211_R137_T30UXB_2...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>Date: 2019-02-26T11:10:49.024Z, Instrument: MS...</td>\n",
       "      <td>2019-02-27 00:35:03.682</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>10316</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-013A</td>\n",
       "      <td>DESCENDING</td>\n",
       "      <td>Sentinel-2B</td>\n",
       "      <td>02.11</td>\n",
       "      <td>Level-2A</td>\n",
       "      <td>S2MSI2A</td>\n",
       "      <td>Sentinel-2</td>\n",
       "      <td>1023.42 MB</td>\n",
       "      <td>30b9e88b-94a7-45ec-9ceb-4fa8bf86be04</td>\n",
       "      <td>POLYGON ((-1.5611267 51.44235231685392, 0.0170...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40128149-82fa-4d83-84a9-37155856ba6d</th>\n",
       "      <td>S2B_MSIL2A_20190226T111049_N0211_R137_T30UWB_2...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>https://scihub.copernicus.eu/dhus/odata/v1/Pro...</td>\n",
       "      <td>Date: 2019-02-26T11:10:49.024Z, Instrument: MS...</td>\n",
       "      <td>2019-02-27 00:34:10.284</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>2019-02-26 11:10:49.024</td>\n",
       "      <td>10316</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-013A</td>\n",
       "      <td>DESCENDING</td>\n",
       "      <td>Sentinel-2B</td>\n",
       "      <td>02.11</td>\n",
       "      <td>Level-2A</td>\n",
       "      <td>S2MSI2A</td>\n",
       "      <td>Sentinel-2</td>\n",
       "      <td>1.02 GB</td>\n",
       "      <td>40128149-82fa-4d83-84a9-37155856ba6d</td>\n",
       "      <td>POLYGON ((-3.0002747 51.45118220579359, -1.420...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  title  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  S2B_MSIL2A_20190226T111049_N0211_R137_T30UWA_2...   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  S2B_MSIL2A_20190226T111049_N0211_R137_T30UXA_2...   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  S2B_MSIL2A_20190226T111049_N0211_R137_T30UXB_2...   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  S2B_MSIL2A_20190226T111049_N0211_R137_T30UWB_2...   \n",
       "\n",
       "                                                                                   link  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "\n",
       "                                                                       link_alternative  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "\n",
       "                                                                              link_icon  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  https://scihub.copernicus.eu/dhus/odata/v1/Pro...   \n",
       "\n",
       "                                                                                summary  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  Date: 2019-02-26T11:10:49.024Z, Instrument: MS...   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  Date: 2019-02-26T11:10:49.024Z, Instrument: MS...   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  Date: 2019-02-26T11:10:49.024Z, Instrument: MS...   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  Date: 2019-02-26T11:10:49.024Z, Instrument: MS...   \n",
       "\n",
       "                                               ingestiondate  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b 2019-02-27 00:34:38.050   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760 2019-02-27 00:34:30.848   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04 2019-02-27 00:35:03.682   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d 2019-02-27 00:34:10.284   \n",
       "\n",
       "                                               beginposition  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b 2019-02-26 11:10:49.024   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760 2019-02-26 11:10:49.024   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04 2019-02-26 11:10:49.024   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d 2019-02-26 11:10:49.024   \n",
       "\n",
       "                                                 endposition  orbitnumber  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b 2019-02-26 11:10:49.024        10316   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760 2019-02-26 11:10:49.024        10316   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04 2019-02-26 11:10:49.024        10316   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d 2019-02-26 11:10:49.024        10316   \n",
       "\n",
       "                                      relativeorbitnumber  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b                  137   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760                  137   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04                  137   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d                  137   \n",
       "\n",
       "                                                            ...                          \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b                        ...                           \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760                        ...                           \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04                        ...                           \n",
       "40128149-82fa-4d83-84a9-37155856ba6d                        ...                           \n",
       "\n",
       "                                      platformidentifier  orbitdirection  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b           2017-013A      DESCENDING   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760           2017-013A      DESCENDING   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04           2017-013A      DESCENDING   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d           2017-013A      DESCENDING   \n",
       "\n",
       "                                      platformserialidentifier  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b               Sentinel-2B   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760               Sentinel-2B   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04               Sentinel-2B   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d               Sentinel-2B   \n",
       "\n",
       "                                      processingbaseline  processinglevel  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b               02.11         Level-2A   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760               02.11         Level-2A   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04               02.11         Level-2A   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d               02.11         Level-2A   \n",
       "\n",
       "                                      producttype  platformname        size  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b      S2MSI2A    Sentinel-2   541.45 MB   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760      S2MSI2A    Sentinel-2   481.23 MB   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04      S2MSI2A    Sentinel-2  1023.42 MB   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d      S2MSI2A    Sentinel-2     1.02 GB   \n",
       "\n",
       "                                                                      uuid  \\\n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  09a3b3c8-1223-4133-9f2d-dbb8efd9028b   \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  29625327-bc7a-44c4-be47-4cfa2828a760   \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  30b9e88b-94a7-45ec-9ceb-4fa8bf86be04   \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  40128149-82fa-4d83-84a9-37155856ba6d   \n",
       "\n",
       "                                                                               geometry  \n",
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b  POLYGON ((-3.0002747 50.55229211062575, -1.450...  \n",
       "29625327-bc7a-44c4-be47-4cfa2828a760  POLYGON ((-1.5886536 50.54373917428845, -0.040...  \n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04  POLYGON ((-1.5611267 51.44235231685392, 0.0170...  \n",
       "40128149-82fa-4d83-84a9-37155856ba6d  POLYGON ((-3.0002747 51.45118220579359, -1.420...  \n",
       "\n",
       "[4 rows x 34 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "api.to_geodataframe(products)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the table as a GeoPandas dataframe, based on the uuid field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x256eede0dd8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "areas = api.to_geodataframe(products)\n",
    "areas.plot(column='uuid', cmap=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Label these polygons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "09a3b3c8-1223-4133-9f2d-dbb8efd9028b    Annotation(-2.23334, 50.0551, '09a3b3c8-1223-4...\n",
       "29625327-bc7a-44c4-be47-4cfa2828a760    Annotation(-0.836784, 50.0375, '29625327-bc7a-...\n",
       "30b9e88b-94a7-45ec-9ceb-4fa8bf86be04    Annotation(-0.795352, 50.9358, '30b9e88b-94a7-...\n",
       "40128149-82fa-4d83-84a9-37155856ba6d    Annotation(-2.21863, 50.954, '40128149-82fa-4d...\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = areas.plot(column='uuid', cmap=None, figsize=(20, 20))\n",
    "areas.apply(lambda x: ax.annotate(s=x.uuid, xy=x.geometry.centroid.coords[0], ha='center'),axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inspect vs our bounds\n",
    "use geopandas to check which scene to download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf2 = gpd.read_file(boundsdata)\n",
    "f, ax = plt.subplots(1)\n",
    "areas.plot(ax=ax,column='uuid',cmap=None,)\n",
    "gdf2.plot(ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get the uuid and inspect produuct data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': '30b9e88b-94a7-45ec-9ceb-4fa8bf86be04',\n",
       " 'title': 'S2B_MSIL2A_20190226T111049_N0211_R137_T30UXB_20190226T172349',\n",
       " 'size': 1073194791,\n",
       " 'md5': 'BEDF8F60B10A030B54EF6710642A46C2',\n",
       " 'date': datetime.datetime(2019, 2, 26, 11, 10, 49, 24000),\n",
       " 'footprint': 'POLYGON((-1.5611267 51.44235231685392,0.017025008525814 51.41234265506691,-0.046142578 50.42629366061962,-1.5912781 50.45527216066188,-1.5611267 51.44235231685392))',\n",
       " 'url': \"https://scihub.copernicus.eu/dhus/odata/v1/Products('30b9e88b-94a7-45ec-9ceb-4fa8bf86be04')/$value\",\n",
       " 'Online': True,\n",
       " 'Creation Date': datetime.datetime(2019, 2, 27, 0, 47, 32, 672000),\n",
       " 'Ingestion Date': datetime.datetime(2019, 2, 27, 0, 35, 3, 682000)}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "api.get_product_odata('30b9e88b-94a7-45ec-9ceb-4fa8bf86be04')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': '30b9e88b-94a7-45ec-9ceb-4fa8bf86be04',\n",
       " 'title': 'S2B_MSIL2A_20190226T111049_N0211_R137_T30UXB_20190226T172349',\n",
       " 'size': 1073194791,\n",
       " 'md5': 'BEDF8F60B10A030B54EF6710642A46C2',\n",
       " 'date': datetime.datetime(2019, 2, 26, 11, 10, 49, 24000),\n",
       " 'footprint': 'POLYGON((-1.5611267 51.44235231685392,0.017025008525814 51.41234265506691,-0.046142578 50.42629366061962,-1.5912781 50.45527216066188,-1.5611267 51.44235231685392))',\n",
       " 'url': \"https://scihub.copernicus.eu/dhus/odata/v1/Products('30b9e88b-94a7-45ec-9ceb-4fa8bf86be04')/$value\",\n",
       " 'Online': True,\n",
       " 'Creation Date': datetime.datetime(2019, 2, 27, 0, 47, 32, 672000),\n",
       " 'Ingestion Date': datetime.datetime(2019, 2, 27, 0, 35, 3, 682000),\n",
       " 'path': '.\\\\S2B_MSIL2A_20190226T111049_N0211_R137_T30UXB_20190226T172349.zip',\n",
       " 'downloaded_bytes': 0}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "api.download('30b9e88b-94a7-45ec-9ceb-4fa8bf86be04')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the path name so we can unzip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_tozip = Out[12]['path'] ##notebook way - will not work in standalone script"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unzip using code found on stackoverflow\n",
    "<br>\n",
    "<br>\n",
    "https://stackoverflow.com/questions/3451111/unzipping-files-in-python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile # https://stackoverflow.com/questions/3451111/unzipping-files-in-python\n",
    "zip_ref = zipfile.ZipFile(path_tozip, 'r')\n",
    "zip_ref.extractall(r'D:\\sentinelsat')\n",
    "zip_ref.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data is now downloaded, and unzipped and waiting for you to work with it. There are plenty of things you can do with Satellite imagery for inspiration take a look at my website www.acgeospatial.co.uk\n",
    "\n",
    "<br>\n",
    "<br>\n",
    "I offer training in Geospatial Python programming contact me info@acgeospatial.co.uk\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}