From 08a4a3db4c16e2231fdd7a47340cea697cad5f87 Mon Sep 17 00:00:00 2001
From: heyarne <arne@schlueter.is>
Date: Mon, 20 Jul 2020 09:58:47 +0000
Subject: [PATCH] WIP: True-color mosaic

---
 True-Color Image/00 Brandenburg Mosaic.ipynb  | 1057 +++++++++++++++++
 ...ad and plot single true-color image.ipynb} |    0
 2 files changed, 1057 insertions(+)
 create mode 100644 True-Color Image/00 Brandenburg Mosaic.ipynb
 rename True-Color Image/{00 Download.ipynb => 00 Download and plot single true-color image.ipynb} (100%)

diff --git a/True-Color Image/00 Brandenburg Mosaic.ipynb b/True-Color Image/00 Brandenburg Mosaic.ipynb
new file mode 100644
index 0000000..bcd5f57
--- /dev/null
+++ b/True-Color Image/00 Brandenburg Mosaic.ipynb	
@@ -0,0 +1,1057 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We start by fetching the shape of Brandenburg from OpenStreetMap:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q geopandas requests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import geopandas as gp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>place_id</th>\n",
+       "      <th>osm_type</th>\n",
+       "      <th>osm_id</th>\n",
+       "      <th>display_name</th>\n",
+       "      <th>place_rank</th>\n",
+       "      <th>category</th>\n",
+       "      <th>type</th>\n",
+       "      <th>importance</th>\n",
+       "      <th>icon</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>234763399</td>\n",
+       "      <td>relation</td>\n",
+       "      <td>62504</td>\n",
+       "      <td>Brandenburg, Deutschland</td>\n",
+       "      <td>8</td>\n",
+       "      <td>boundary</td>\n",
+       "      <td>administrative</td>\n",
+       "      <td>0.766083</td>\n",
+       "      <td>https://nominatim.openstreetmap.org/images/map...</td>\n",
+       "      <td>MULTIPOLYGON (((11.26623 53.12205, 11.26780 53...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    place_id  osm_type  osm_id              display_name  place_rank  \\\n",
+       "0  234763399  relation   62504  Brandenburg, Deutschland           8   \n",
+       "\n",
+       "   category            type  importance  \\\n",
+       "0  boundary  administrative    0.766083   \n",
+       "\n",
+       "                                                icon  \\\n",
+       "0  https://nominatim.openstreetmap.org/images/map...   \n",
+       "\n",
+       "                                            geometry  \n",
+       "0  MULTIPOLYGON (((11.26623 53.12205, 11.26780 53...  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_url = 'https://nominatim.openstreetmap.org/search/?q=Brandenburg,%20Germany&format=geojson&polygon_geojson=1'\n",
+    "brandenburg = gp.read_file(search_url)[:1]\n",
+    "brandenburg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
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+      ],
+      "text/plain": [
+       "<shapely.geometry.multipolygon.MultiPolygon at 0x7f2c5831d050>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "brandenburg.iloc[0]['geometry']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"11.126244276 51.219080475999995 3.779555148 2.4799937480000054\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,104.9181547)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"0.07559110296\" opacity=\"0.6\" d=\"M 13.7633275,51.359064 L 13.5460872,51.3692268 L 13.5425377,51.3694054 L 13.2636628,51.3847675 L 13.2179195,51.394949 L 13.2163387,51.395353 L 13.2152588,51.3958909 L 13.214107,51.3967458 L 12.2764918,52.1039277 L 11.2710967,53.0989296 L 11.2687618,53.1017738 L 11.268322,53.1026298 L 11.2680466,53.1036983 L 11.2662278,53.1220488 L 11.6291082,53.2420816 L 12.0450294,53.3707565 L 13.7911487,53.5583617 L 13.7999768,53.5590907 L 14.2248157,53.4342922 L 14.2355746,53.4289095 L 14.4122208,53.3295304 L 14.4124528,53.329168 L 14.4154534,53.324377 L 14.445247,53.2744351 L 14.448945,53.26674 L 14.450125,53.264173 L 14.6395476,52.5719246 L 14.759046,52.065892 L 14.759078,52.065656 L 14.759094,52.065383 L 14.7658159,51.6106808 L 14.7653037,51.6081384 L 14.7651199,51.6074698 L 14.7622879,51.6036768 L 14.7619069,51.6031838 L 14.7609069,51.6023518 L 14.7521819,51.5957208 L 14.7298948,51.5817747 L 14.6802568,51.5532503 L 14.6774112,51.5519654 L 14.6771522,51.5518504 L 14.6741277,51.5508515 L 14.0005961,51.3725367 L 13.7633275,51.359064 z\" /></g></svg>"
+      ],
+      "text/plain": [
+       "<shapely.geometry.polygon.Polygon at 0x7f2c26c3fd10>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# let's remove the hole and simplify the shape\n",
+    "brandenburg_simple = brandenburg.convex_hull[0]\n",
+    "brandenburg_simple"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets fetch products of interest from Scihub:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install sentinelsat -q"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sentinelsat import SentinelAPI\n",
+    "from datetime import date\n",
+    "import datetime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# --------------------------------------------------------------------------#\n",
+    "# adjust these lines to search for pictures of the fire you want to look at #\n",
+    "# you should not need to changed anything below this cell                   #\n",
+    "# --------------------------------------------------------------------------#\n",
+    "\n",
+    "start_date = date.today() - datetime.timedelta(weeks=4)\n",
+    "end_date = date.today()\n",
+    "footprint = brandenburg_simple.wkt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# you s\n",
+    "user = 'heyarne'\n",
+    "password='FhnNfPppxNbBm7wCoCGLnfly'\n",
+    "api = SentinelAPI(user, password)\n",
+    "\n",
+    "# the \"footprint\" is what we can use to preselect a certain area;\n",
+    "# the lake is at (51.7874, 14.4226)\n",
+    "# footprint = 'POLYGON((14.359428613281251 51.806620319822734,14.466545312500001 51.806620319822734,14.466545312500001 51.757343872357566,14.359428613281251 51.757343872357566,14.359428613281251 51.806620319822734))'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "products = api.query(footprint,\n",
+    "                     platformname='Sentinel-2',\n",
+    "                     processinglevel='Level-2A',\n",
+    "                     date=(start_date, end_date),\n",
+    "                     cloudcoverpercentage=(0,30))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 53 results\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Found ' + str(len(products)) + ' results')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Is our entire footprint covered by the search results?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2c24554a50>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results = api.to_geodataframe(products)\n",
+    "\n",
+    "ax = results.plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "brandenburg.plot(ax=ax, color='', edgecolor='pink')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The previous approach was this:\n",
+    "\n",
+    "> We're picking our product by the following criteria:\n",
+    ">\n",
+    "> - It should be taken on the same date\n",
+    "> - It should only use one projection\n",
+    "> - It should have only a low cloud covoer percentage\n",
+    "\n",
+    "But now we need to screw the same projection part. The new approach looks like this:\n",
+    "\n",
+    "- Group pictures by day\n",
+    "- Use the ones with the lowest cloud cover percentage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "pd.set_option('display.max_rows', 999)\n",
+    "pd.set_option('display.max_columns', 999)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ingestiondate\n",
+       "2020-06-27    11\n",
+       "2020-06-22    11\n",
+       "2020-07-18     6\n",
+       "Name: title, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_per_day = results.groupby(results['ingestiondate'].dt.strftime('%Y-%m-%d')).count()['title']\n",
+    "most_results_per_day = results_per_day.sort_values(ascending=False).head(3)\n",
+    "most_results_per_day"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Do those days cover our entire footprint?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2c1fbceb50>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "most_result_dates = set(most_results_per_day.index)\n",
+    "\n",
+    "ax = results[results['ingestiondate'].dt.strftime('%Y-%m-%d').isin(most_result_dates)].plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "brandenburg.plot(ax=ax, color='', edgecolor='pink')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nicey. Does one day cover all?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/rus/.anaconda/lib/python3.7/site-packages/geopandas/plotting.py:487: UserWarning: The GeoDataFrame you are attempting to plot is empty. Nothing has been displayed.\n",
+      "  UserWarning,\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2c1fb5b750>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = results[results['ingestiondate'].dt.strftime('%Y-%m-%d') == '2020-06-16'].plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "brandenburg.plot(ax=ax, color='', edgecolor='pink')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2c1faca9d0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = results[results['ingestiondate'].dt.strftime('%Y-%m-%d') == '2020-06-22'].plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "brandenburg.plot(ax=ax, color='', edgecolor='pink')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2c1fab3610>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = results[results['ingestiondate'].dt.strftime('%Y-%m-%d') == '2020-06-27'].plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "brandenburg.plot(ax=ax, color='', edgecolor='pink')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Hmmm… that's not really ideal, is it? Let's take another approach and see for each date, regardless of how many results we have."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-07-18\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-07-15\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-07-13\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-07-12\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-07-04\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-06-30\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-06-27\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-06-25\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-06-23\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "On 2020-06-22\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "formatted = results['ingestiondate'].dt.strftime('%Y-%m-%d')\n",
+    "dates = formatted.unique()\n",
+    "for d in dates:\n",
+    "    on_this_date = results[formatted == d]\n",
+    "    print('On ' + d)\n",
+    "    ax = on_this_date.plot(color='', edgecolor='blue', alpha=0.1)\n",
+    "    brandenburg.plot(ax=ax, color='', edgecolor='pink')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# let's just pick 16th and 22nd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ZeroDivisionError",
+     "evalue": "division by zero",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-21-790f197c8e39>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m16\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m22\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m27\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0msubset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mproducts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ingestiondate'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0md\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m     \u001b[0mcloudcover\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcalc_cloudcover\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'cloud cover on {}: {}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%d %B %Y'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcloudcover\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-21-790f197c8e39>\u001b[0m in \u001b[0;36mcalc_cloudcover\u001b[0;34m(products)\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcalc_cloudcover\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mproducts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mcloudcover\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cloudcoverpercentage'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mproducts\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ingestiondate'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcloudcover\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mproducts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m16\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m22\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m27\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
+     ]
+    }
+   ],
+   "source": [
+    "# let's pick between 16th, 22nd and 27th\n",
+    "\n",
+    "def calc_cloudcover(products):\n",
+    "    cloudcover = [v['cloudcoverpercentage'] for v in products if v['ingestiondate']]\n",
+    "    return sum(cloudcover) / len(products)\n",
+    "\n",
+    "for d in [date(2020, 6, 16), date(2020, 6, 22), date(2020, 6, 27)]:\n",
+    "    subset = [v for v in products.values() if v['ingestiondate'].date() == d]\n",
+    "    cloudcover = calc_cloudcover(subset)\n",
+    "    print('cloud cover on {}: {}'.format(d.strftime('%d %B %Y'), cloudcover))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Let's take the 27th!\n",
+    "to_download = {k: v for k, v in products.items() if v['ingestiondate'].date() in {date(2020, 6, 16), date(2020, 6, 22)}}\n",
+    "\n",
+    "# they will not be in the same orbit of course\n",
+    "set(v['orbitnumber'] for v in to_download.values())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we create the directory structure we need for the following notebooks\n",
+    "! mkdir -p input/raster/brandenburg_mosaic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print('Downloading {} files…'.format(len(to_download)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "api.download_all(to_download, 'input/raster/brandenburg_mosaic')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Previewing Downloaded Files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from glob import glob\n",
+    "downloaded = glob('input/raster/brandenburg_mosaic/*.zip')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "downloaded"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "import rasterio as r\n",
+    "from rasterio import plot\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Path(downloaded[1]).name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import zipfile\n",
+    "\n",
+    "def band_paths(p, bands, resolution=None):\n",
+    "    '''\n",
+    "    Given a zip file at `p`, returns the paths inside p to the raster files containing\n",
+    "    information for the given bands. Because some bands are available in more than one\n",
+    "    resolution, this can be filtered by prodiding a third parameter (e.g. resolution='10m').\n",
+    "    \n",
+    "    The returned paths are formatted in the zip scheme as per Apache Commons VFS and can\n",
+    "    thus be directly opened by rasterio.\n",
+    "    '''\n",
+    "    with zipfile.ZipFile(p) as f:\n",
+    "        files = f.namelist()\n",
+    "        rasters = [f for f in files if f.endswith('.jp2')]\n",
+    "        rasters = ['zip+file://' + p + '!/' + r for r in rasters for b in bands if b in r and (not resolution or resolution in r)]\n",
+    "        return rasters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rgb_paths(zip_file, resolution='10m'):\n",
+    "    return band_paths(zip_file, ['B02', 'B03', 'B04'], resolution)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# preview the first downloaded image\n",
+    "with r.open(band_paths(downloaded[3], ['TCI'], '20m')[0]) as true_color:\n",
+    "    # we do not need\n",
+    "    fig, (axr, axg, axb) = plt.subplots(1,3, figsize=(21,7))\n",
+    "    plot.show((true_color, 1), ax=axr, cmap='Reds', title='red channel')\n",
+    "    plot.show((true_color, 2), ax=axg, cmap='Greens', title='green channel')\n",
+    "    plot.show((true_color, 3), ax=axb, cmap='Blues', title='blue channel')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plotting the combined rgb image\n",
+    "true_color = r.open(band_paths(downloaded[3], ['TCI'], '20m')[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# note that in order to get the real colors, we need to reverse the bands into \"rasterio band order\"\n",
+    "plt.figure(figsize=(20,20))\n",
+    "plot.show(true_color.read()[::-1], transform=true_color.transform)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating a True-Color Mosaic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from rasterio.merge import merge"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test = [r.open(band_paths(f, ['TCI'], '60m')[0]) for f in downloaded[:2]]\n",
+    "test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_mosaic, test_trans = merge(test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=(8,16))\n",
+    "plot.show(test_mosaic)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# coolcoolcool"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "downloaded"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mosaic, mosaic_transform = merge([r.open(band_paths(f, ['TCI'], '20m')[0]) for f in downloaded if 'T33' in f])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=(8,16))\n",
+    "plot.show(mosaic, transform=mosaic_transform)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we need to make sure both have the same CRS if we want to plot them on top of each other\n",
+    "src_meta = r.open(band_paths(downloaded[0], ['TCI'], '60')[0]).meta\n",
+    "src_meta"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, (ax) = plt.subplots(1, 1, figsize=(8,16))\n",
+    "plot.show(mosaic, transform=mosaic_transform, ax=ax)\n",
+    "brandenburg.to_crs(src_meta['crs']).plot(ax=ax, color='', edgecolor='pink')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "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": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/True-Color Image/00 Download.ipynb b/True-Color Image/00 Download and plot single true-color image.ipynb
similarity index 100%
rename from True-Color Image/00 Download.ipynb
rename to True-Color Image/00 Download and plot single true-color image.ipynb