{ "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 https://identity.dataspace.copernicus.eu/auth/realms/CDSE/device?user_code=QHKA-VXMK 📋 to authenticate." ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "âś… 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": "code", "execution_count": 19, "id": "828a58ad-3988-4024-8ffb-0cf9a6e60d39", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idbez_lansch_lanrepentuncdunaggidagglomeratinhabitantsizegeometry
01Bremen04000000NoneNoneNoneNaN318.195497MULTIPOLYGON (((474358.64 5894064.42, 474311.0...
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" ], "text/plain": [ " id bez_lan sch_lan repentuncd unaggid agglomerat inhabitant size \\\n", "0 1 Bremen 04000000 None None None NaN 318.195497 \n", "\n", " geometry \n", "0 MULTIPOLYGON (((474358.64 5894064.42, 474311.0... " ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import geopandas as gpd\n", "\n", "gdf = gpd.read_file('Verwaltungsgrenzen_HB_BHV', layer=\"hb_landesflaeche_Teil_I_BRE\")\n", "gdf" ] }, { "cell_type": "code", "execution_count": 22, "id": "1cc183c8-ef90-4870-8f36-c6436c91d419", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gdf.explore()" ] }, { "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": 23, "id": "fc491aa9-36a4-4c00-9c66-abc98df32b1a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[8.481758449250766, 53.01115244699335, 8.990813245344944, 53.2289106605276]" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Bounding Box bestimmen\n", "bbox = gdf.to_crs('WGS84').total_bounds.tolist()\n", "bbox" ] }, { "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": [ "spatial_extent=dict(zip([\"west\", \"south\", \"east\", \"north\"], bbox))\n", "\n", "spatial_extent\n", "\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", "evalue": "Mime type rendering requires nbformat>=4.2.0 but it is not installed", "output_type": "error", "traceback": [ "\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" ] }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "coloraxis": "coloraxis", "hovertemplate": "x: %{x}
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