cdec/04_land_surface_temperature.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3d887eed-ce30-4984-abd3-762deb9af0cc",
   "metadata": {},
   "source": [
    "# Oberflächentemperatur (Land Surface Temperature)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee91c281-afd2-43b5-ba42-fdcef475dc81",
   "metadata": {},
   "source": [
    "## Authentifizierung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dca5e519-d0ff-48f9-b493-80f42101eb35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "Visit <a href=\"https://identity.dataspace.copernicus.eu/auth/realms/CDSE/device?user_code=QHKA-VXMK\" title=\"Authenticate at https://identity.dataspace.copernicus.eu/auth/realms/CDSE/device?user_code=QHKA-VXMK\" target=\"_blank\" rel=\"noopener noreferrer\">https://identity.dataspace.copernicus.eu/auth/realms/CDSE/device?user_code=QHKA-VXMK</a> <a href=\"#\" onclick=\"navigator.clipboard.writeText('https://identity.dataspace.copernicus.eu/auth/realms/CDSE/device?user_code=QHKA-VXMK');return false;\" title=\"Copy authentication URL to clipboard\">&#128203;</a> to authenticate."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "✅ Authorized successfully"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Authenticated using device code flow.\n"
     ]
    }
   ],
   "source": [
    "import openeo\n",
    "\n",
    "connection = openeo.connect(\"https://openeo.dataspace.copernicus.eu/\").authenticate_oidc()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc5b84c1-271a-436c-9363-8e6525e6fec7",
   "metadata": {},
   "source": [
    "## Verwaltungsgrenzen von Bremen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3140ba0c-bedc-4314-876e-01598e2826c8",
   "metadata": {},
   "source": [
    "## Räumliche Ausdehnung\n",
    "\n",
    "Bestimmung der räumlichen Ausdehnung anhand der Vektorgeometrien"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c86786f-1fd3-4859-9853-8e8b6fb20b30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'west': 8.481758449250766,\n",
       " 'south': 53.01115244699335,\n",
       " 'east': 8.990813245344944,\n",
       " 'north': 53.2289106605276}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "spatial_extent = {'west': 8.721771, 'south': 53.025027, 'east': 8.904419, 'north': 53.114965}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b52c35ce-9880-438f-8ed7-eb92e325eb7f",
   "metadata": {},
   "source": [
    "## Zeitliche Ausdehnung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d985ba77-3ba7-418f-b84a-a8c817b9f512",
   "metadata": {},
   "outputs": [],
   "source": [
    "temporal_extent = [\"2024-06-01\", \"2024-08-31\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cca0787b-5f23-4c17-b2a7-e0c9f812fa15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:00 Job 'j-2510111146024febaf1f1d58a9a115af': send 'start'\n",
      "0:00:13 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:00:18 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:00:24 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:00:32 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:00:42 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:00:55 Job 'j-2510111146024febaf1f1d58a9a115af': created (progress 0%)\n",
      "0:01:10 Job 'j-2510111146024febaf1f1d58a9a115af': running (progress N/A)\n",
      "0:01:29 Job 'j-2510111146024febaf1f1d58a9a115af': running (progress N/A)\n",
      "0:01:53 Job 'j-2510111146024febaf1f1d58a9a115af': running (progress N/A)\n",
      "0:02:23 Job 'j-2510111146024febaf1f1d58a9a115af': running (progress N/A)\n",
      "0:03:00 Job 'j-2510111146024febaf1f1d58a9a115af': running (progress N/A)\n",
      "0:03:47 Job 'j-2510111146024febaf1f1d58a9a115af': finished (progress 100%)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PosixPath('results/lst.tif')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cube = connection.load_collection(\n",
    "    \"SENTINEL3_SLSTR_L2_LST\",\n",
    "    spatial_extent=spatial_extent,\n",
    "    temporal_extent=temporal_extent,\n",
    "    bands=[\"LST\"]\n",
    ")\n",
    "\n",
    "\n",
    "cube = cube.mean_time()\n",
    "\n",
    "lst = cube.save_result(format=\"GTIFF\")\n",
    "job = lst.create_job(title=\"LST\")\n",
    "job.start_and_wait().download_result('results/lst.tif')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c840c746-b6f3-4baa-b198-905387509990",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2565447ee8f44fbfb5f467641971172e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[53.1173035, 8.740687], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title',…"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import leafmap\n",
    "\n",
    "m = leafmap.Map()\n",
    "\n",
    "m.add_raster(\n",
    "    'results/lst.tif',\n",
    "    cmap=\"coolwarm\",\n",
    "    layer_name=\"Land Surface Temperature\"\n",
    ")\n",
    "\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e1849544-030e-4b5b-8402-dad9f9911c6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rasterio as rio\n",
    "\n",
    "src = rio.open('results/lst.tif')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1ad30415-08eb-4c28-8e05-86a6dd605157",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Temperatur von Kelvin in Celsius umrechnen\n",
    "lst = src.read() - 272.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f95d4a2d-0060-43c0-9cd8-2f5e9e2c4ec2",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
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      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mValueError\u001b[39m                                Traceback (most recent call last)",
      "\u001b[36mFile \u001b[39m\u001b[32m~/cdec-hackathon/game/.venv/lib/python3.12/site-packages/IPython/core/formatters.py:984\u001b[39m, in \u001b[36mIPythonDisplayFormatter.__call__\u001b[39m\u001b[34m(self, obj)\u001b[39m\n\u001b[32m    982\u001b[39m method = get_real_method(obj, \u001b[38;5;28mself\u001b[39m.print_method)\n\u001b[32m    983\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m984\u001b[39m     \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    985\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/cdec-hackathon/game/.venv/lib/python3.12/site-packages/plotly/basedatatypes.py:850\u001b[39m, in \u001b[36mBaseFigure._ipython_display_\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m    847\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mplotly\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mio\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpio\u001b[39;00m\n\u001b[32m    849\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m pio.renderers.render_on_display \u001b[38;5;129;01mand\u001b[39;00m pio.renderers.default:\n\u001b[32m--> \u001b[39m\u001b[32m850\u001b[39m     \u001b[43mpio\u001b[49m\u001b[43m.\u001b[49m\u001b[43mshow\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m    851\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m    852\u001b[39m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mrepr\u001b[39m(\u001b[38;5;28mself\u001b[39m))\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/cdec-hackathon/game/.venv/lib/python3.12/site-packages/plotly/io/_renderers.py:415\u001b[39m, in \u001b[36mshow\u001b[39m\u001b[34m(fig, renderer, validate, **kwargs)\u001b[39m\n\u001b[32m    410\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m    411\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mMime type rendering requires ipython but it is not installed\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    412\u001b[39m     )\n\u001b[32m    414\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m nbformat \u001b[38;5;129;01mor\u001b[39;00m Version(nbformat.__version__) < Version(\u001b[33m\"\u001b[39m\u001b[33m4.2.0\u001b[39m\u001b[33m\"\u001b[39m):\n\u001b[32m--> \u001b[39m\u001b[32m415\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m    416\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mMime type rendering requires nbformat>=4.2.0 but it is not installed\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    417\u001b[39m     )\n\u001b[32m    419\u001b[39m display_jupyter_version_warnings()\n\u001b[32m    421\u001b[39m ipython_display.display(bundle, raw=\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
      "\u001b[31mValueError\u001b[39m: Mime type rendering requires nbformat>=4.2.0 but it is not installed"
     ]
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      "application/vnd.plotly.v1+json": {
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        "plotlyServerURL": "https://plot.ly"
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         "coloraxis": "coloraxis",
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         "name": "0",
         "type": "heatmap",
         "xaxis": "x",
         "yaxis": "y",
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      ],
      "text/plain": [
       "Figure({\n",
       "    'data': [{'coloraxis': 'coloraxis',\n",
       "              'hovertemplate': 'x: %{x}<br>y: %{y}<br>color: %{z}<extra></extra>',\n",
       "              'name': '0',\n",
       "              'type': 'heatmap',\n",
       "              'xaxis': 'x',\n",
       "              'yaxis': 'y',\n",
       "              'z': {'bdata': ('gIXtQEA3+UCgiQxBwH4QQeB4DkFAJw' ... 'FAhAlBICoJQYDzBUHAw/9AwED/QA=='),\n",
       "                    'dtype': 'f4',\n",
       "                    'shape': '25, 58'}}],\n",
       "    'layout': {'coloraxis': {'colorscale': [[0.0, 'rgb(3, 35, 51)'],\n",
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       "               'margin': {'t': 60},\n",
       "               'template': '...',\n",
       "               'xaxis': {'anchor': 'y', 'constrain': 'domain', 'domain': [0.0, 1.0], 'scaleanchor': 'y'},\n",
       "               'yaxis': {'anchor': 'x', 'autorange': 'reversed', 'constrain': 'domain', 'domain': [0.0, 1.0]}}\n",
       "})"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "px.imshow(\n",
    "    lst[0],\n",
    "    color_continuous_scale='thermal',\n",
    "    #zmin=5,\n",
    "    #zmax=12\n",
    ")"
   ]
  }
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