{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Data retrieval from the Long-Term Archive\n", "\n", "Sentinel data that has not been accessed for a longer period of time is moved to a Long-Term Archive (LTA).\n", "Data in the LTA can not be retrieved immediately but instead has to moved out of this archive first.\n", "\n", "This notebook shows how API responses in this case look like and what to do in this situation.\n", "The relevant part is at the end of this notebook, the rest is documented for the sake of completeness." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining the area of interest\n", "\n", "The data retrieval process looks like in other notebooks:\n", "The sentinelsat API client is initialized and the geometry of an area of interest is fetched using OpenStreetMap nominatim and narrowed down using GeoPandas." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from sentinel_helpers import search_osm, geodataframe_on_map\n", "from datetime import date\n", "import os\n", "from sentinelsat import SentinelAPI\n", "from tqdm.notebook import tqdm\n", "\n", "api = SentinelAPI(os.getenv('SCIHUB_USERNAME'), os.getenv('SCIHUB_PASSWORD'))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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place_idosm_typeosm_iddisplay_nameplace_rankcategorytypeimportanceicongeometry
0257891092relation422436Jüterbog, Teltow-Fläming, Brandenburg, 14913, ...16boundaryadministrative0.685236https://nominatim.openstreetmap.org/ui/mapicon...POLYGON ((12.95605 52.03939, 12.96134 52.03944...
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" ], "text/plain": [ " place_id osm_type osm_id \\\n", "0 257891092 relation 422436 \n", "\n", " display_name place_rank category \\\n", "0 Jüterbog, Teltow-Fläming, Brandenburg, 14913, ... 16 boundary \n", "\n", " type importance \\\n", "0 administrative 0.685236 \n", "\n", " icon \\\n", "0 https://nominatim.openstreetmap.org/ui/mapicon... \n", "\n", " geometry \n", "0 POLYGON ((12.95605 52.03939, 12.96134 52.03944... " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "jueterbog = search_osm('Jüterbog, Brandenburg')\n", "jueterbog = jueterbog[(jueterbog['type'] == 'administrative') & (jueterbog['osm_type'] == 'relation')]\n", "jueterbog" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "geodataframe_on_map(jueterbog)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The API query is initialized for a time span we are interested in and using an area that slightly extends the geometry fetched from OpenStreetMap. This is done to increase the likelihood that the phenomenon we are interested in is visible on the products we download - we don't know where exactly we will need to look, we only know proximity." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "start_date = date(2018, 7, 1)\n", "end_date = date(2018, 8, 31)\n", "\n", "# we increase the geometry size by buffering it by 2.5km\n", "buffered = jueterbog.to_crs('epsg:25833').buffer(2500).to_crs('epsg:4326')\n", "footprint = buffered.iloc[0].convex_hull.wkt\n", "\n", "results = api.query(footprint,\n", " platformname='Sentinel-2',\n", " processinglevel='Level-2A',\n", " date=(start_date, end_date),\n", " cloudcoverpercentage=(0, 30))\n", "\n", "gdf = SentinelAPI.to_geodataframe(results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Deciding which products we are interested in\n", "\n", "We are only interested in products that have a low cloud coverage value:" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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pYBgLcBnw1Pr2EVRX5dqv/vlyZ7sxtuecI5u1bu+v5nXP2F7TwDAWZr77+lSq8y8Pp/+/YGOVzVq35+z91dVs5rpnbK9pYBgLsAbYtWfdHsB64C5nuzG255wjm7Vu76/mdc/YXtPAMBbg+cDes6zfEXivs90Y23POkc1at/dX87p7F1/MyswsqSIXs5L0aEknSbpG0s/qZWO9bkdnuzG255wjm7Vu76/mdfcqdTXCzwFbgAMiYmlELKU6vWYL8HlnOzO255wjm7Vu76/mdU/X9JjLMBbg2kHuG8ds1ro9Z++vrmYz1927lHoFfoOkd0raZXKFpF0kvYuHvmbI2fJje845slnr9v5qXvc0pRr4kcBS4GJJd0q6E7gI2Bl4hbOdGdtzzpHNWrf3V/O6p/FZKGZmSXXmK9UmSXqGs90f23POkS05dsZsybEHyXaugQNvcjbF2J5zjmzJsTNmS47dOOtDKGZmSZX6TkwAJK0GVgD3AddFxDWLkZ1je08edBsLzbatOeOch50tOfZi/D2XfIyMWzZz3Q9up8QrcEnPAz4E/Jzqu+G+DewE3AscHRFznk7TJtunphsjYuUosm1rzjjnUWVLjj3Kv+eSj5Fxy2auu1epV+AfAV4YEZslPR74cETsL+kFwCnAC0eRlfTRue6iupjMnNpk29TcNl9qzi33V9a6P0KBx3XhsTNmM9c9Tak3MZdExOb69o3A4wAi4nxg9xFmXwdsANb2LGuA34ww26bmtvlSc26TzVp3qcd1ybEzZjPXPU2pV+BrJJ0CXAAcRnUiO5K2pfpyz1FlLwM2RMR3eu+QdOIIs21qbpsvNec22ZJjl/p7LvkYGbds5rqnKXUMfBvg9cBTgCuAUyPifkmPAh4TETeMKLszcHdE/GqAmttkB665bb7gnAfOlhy71N9z4cfIWGUz1z1jeyUauJmZtde5D/JI+sqospJ+W9J/l/TPkl7Vc9/HR5VtU3PbfKk5t91fLcfeVdInJP2jpKWSTpR0laTPSdptVNk+2x3Z47qrY3f1udw236U+UuoQylwfGRVwTkTM+URpmf0C1bdAXwr8GdWpO6+KiHskrYuIOT/K2jI7cM1t8wXnPHB2CGN/FTgX2A54FXAG8FmqY47Pj4jDRpQt8rguOXbG53LbfMnnxYztFWrg9wMXU/1F9dovIh41ouz6iFg15ef3Ai8GDgXO77Pj22QHrrltvuCcB84OYezLI2Kf+va0c7d7tzvkbJHHdcmxMz6X2+ZLPi9miIYXEB/GQnWa1hPnuO8nI8xuBLbqWXcMcDVwwwizA9eceM4DZ4cw9hVTbr+v574rR5gt8rguOXbG5/IQHl/Fnhczttc0MIwFOAJ40hz3vXSE2b+j+m9w7/qDqT7OOqrswDUnnvPA2SGM/TfA9rOsfwJw1gizRR7XJcfO+FwewuOr2POid/FZKGZmSRU/C6X3jYx53tgY+2zJsT3nHNmSY2fMlhy7bd3QgQbOzGvgNrkm7rhlS47tOefIlhw7Y7bk2G3r9iEUM7Osil0PXJKAfaku4BLALcD3YwH/ooxbNmvdnrP3V1ezmeuetq0Sr8AlvRD4ONUJ7TfXq/egeqf/zRHxNWfLj+0558hmrdv7q3ndMzQ9bWUYC9W5kBOzrH88sNHZboztOefIZq3b+6t53b1LqTcxtwZummX9zcA2znZmbM85R7bk2BmzJcduW/eMjZVwKnCZpDOBya8QWgG8kupbKZztxtiec45s1rq9v5rXPU2xs1Ak7UV1gaDdqa6FcBNwdkT8wNnujN0y+xSqazwMOueB8xnnPIT9NVZzHsfn1IxtlWrgZmbWThc+yDONOnr94S5mS47dL6vp1z0+que+ptdrbpyfZ7udnPOo5lvnx2rOD9fn1GyKHAPX/NcBXuVsN8ZuWfc/UZ0q9QXgzyQdQX3dY2C/PtlW+aRzbrW/xm3OY/qcmqHUm5iXMfd1gHd0tjNjt8nuGRF/Ut/+oqrrHn9D0qF9csPIZ5xz2/01bnMex+fUTE3POxzGQs7rD/taz82yJa/XnG7OQ9hfYzXncXxOzZppGhjGQs7rD/taz82yJa/XnG7OQ9hfYzXncXxOzbb4LBQzs6SKn4XSe1B/noP8Y58tObbnnCNbcuyM2ZJjt60bOtDAyXktXl+72HPuarbk2BmzJcf29cDNzMZVqdMIkfJdi7dUNmvdnrP3V1ezmeuetq0Sr8CV8Fq8pbJZ6/acvb+6ms1c9wxNT1sZxkLCa/GWymat23P2/upqNnPdvYuvB979bMmxPecc2ZJjZ8yWHLtt3TM2VkLGa/H62sWLl81at/dXjmzmuqfx9cATZLPW7Tl7f3U1m7nuadsq1cDNzKydLnyQZxoluhZv6WzJsT3nHNmSY2fMlhx7kGyRY+BKeC3eUtmSY3vOObIlx86YLTl227p7+Xrg3c+WHNtzzpEtOXbGbMmxfT3wccpmrdtz9v7qajZz3b1LqWPgJzL38ff/5Gxnxi6VLTl2xmzJsTNmS47dJjuDz0IxM0uqc2ehmJnZwriBm5kl5QZuZpZUsQYu6bcl7TnL+qePKivpUEmPbFZp+2ydH3i+bfIl5zzPdl8w6rykP5D0pPr270t6h6RDFrj9gbKSVk7uL1VeJ+ljkt4kad5Tdttkp2xjV0m71reXS3qZpKeOMltyzm3m2zZfKjtD09NWhrEAr6C6iPl64GrgWVPuWzfC7K+BO4B/Bl4MLGlQc5vswDVnnXOf7d44yjzwEeA7wPeBv61v/xfg68AHR5jdAGxb3/4AcBbwaqoLGJ06qmydeQPwY2AT1Vdzfa/OXgscO8JskTm3qbnw/mpV94zttXkiDbpQNaLd6tv7AtcAL6t/vnyE2cuBnYDXAxcAtwGfBJ63gJrbZAeuOfGcz55j+T/Af4wyT/WPnIBtgS081CS2ATaMMPuDKbfXAltN+fmKUWXr37mqrnkp8Etg13r9TsD6EWaLzLlNzYX3V6u6e5dSn8RcEhG3AkTE9yUdCJwjaQ+qrxgaVTYiYgvwKeBT9X9jXgGcJGmPiFgxomybmrPO+blUr6Z+2bN+8uuk+mmTj4gISQ9M/lz/+QD9Dxu2yf5E0h9GxDeoXmGtAG6QtLRPrm0W4N6I+BXwK0n/NyJ+Wk9mi6R+j5E22VJzblNz23yp7ExNO/4wFqr/lu7Zs24Hqld594wwe/k89z1uhNmBa048568AB85x3yULmPPAear/jn+T6mPLH6R61f5e4GvAJ0eYXQFcCFxS57YA36D6n8xBo8rW+TXANvXtPaasfyT9X822yRaZc5uaC++vVnX3LqW+E3Nv4FcRcV3P+m2AV0TEGSPKHhARFw1Yc5vs3lT/7b++Z33fmtvmS825NEnPoXo1famqN38PB24EzoqIB0aVrfN7Ab/DQ9++ctlCcm2yklYCt0bEvT3rdwf2ioivjyLbtu5Bs3XNt0TEfYPU3CZfel9Py5Vo4FaGpJ156LDIomXNHq5KP6eKnEYoaYWkMyV9U9J76leSk/d9cVTZPtu9Klt2Ifn6VK0zJW2mesf7Mkm31+smRph9sqSvSDpX0p6STpP0c0nfr19x9ZvXwPlSj6+Sj2s/p4aTXUi+1HNqNiW/E/MLwKXAscDFkv44In4GPG5UWUkvm+suYNcuZoeQ/1eqU+P+NCLur7e3BHg5cCaw34iyJ1MdQ96e6rjmu4DXAS8B/idwUJ+62+SLPL4KZouN7efUoj6nZhZb6Bj4+ohYNeXnVwPvBg4FPh8Rc130vG32XuAMZj9z44iI2KFr2SGMfV1EPLHpfUPIXh4R+9S3r4+IJ0y5b918f09t8wUfX0Wyhev2c2qB97XNzqrpu57DWKjOtX1kz7rnA9dTHeAfVXYt8LQ57ut3Hd8i2SGMfSbwceDZwGPr5dn1us+NMHvllNtv7rlv3vOp2+YLPr6KZAvX7efUIj2nZt1e08AwFuBtzPJhEGAf4PwRZp8LrJzjvtVdzA5h7EdQfeLrq1QfIthQ334z8FsjzL4B2H6W9U8APrKAOQ+cL/j4KpItXLefU4v0nJpt8VkoZmZJdeZqhJLWOdv9sT3nHNmSY2fMlhy7TbYzDRxm/ZJPZ7s3tuecI1ty7IzZkmMPnO1SAz/X2RRje845siXHzpgtOfbA2c4cA5e0LCLucLbbY7et28yGp9QnMf9I0o8lfUvSPpKuBr4n6SZJ837AY9yyWeuWdKekT0s6SFLj/yK2yY9btuTYGbMlx25b9wxNT1sZxkJ1feu9gOcAPwP2q9fvRf8vKBirbNa6qS5QfzzwbeBm4H9M5hf4GBk4P27ZrHV7fzWve8b2Bg22WaY++ek5aZ7+F0Qfq2zWunuyK4F3AuuAHwH/reGcG+XHLZu1bu+v5nX3LqXexPy5pDdI+s/AFklvk7S7pGOYeQH/cc9mrfvB/x5GxI0R8XdRfST7j4B7+mTb5sctm7Vu76/mdU/XtOMPY6G6kPv/ovp6rl2pPgm2gerd2L2c7cbYLbMfbvkYGTg/btmsdXt/tV86cxaKmZk1U+pyskh6EfBSYHeqK4LdAnwxIs5ztjtjjyD7pYj4ar9s2/y4ZbPW7f3VvO5p2yrxClzSR6i+Qul/U32FEsAewGuA6yLiLc6WH9tzzpHNWrf3V/O6Zxjm8ZgGx4F+OMd61ZNwtgNje845slnr9v5qXnfvUuoslLsl7TvL+mcBdzvbmbE95xzZkmNnzJYcu23d05Q6Bv5a4BOSduCh/0asAH5R3+dsN8Yulc1ad6ls1rpLZTPXPU3Rs1Ak7Up1IF/ATRHxU2e7N7bnnCObtW7vr+Z1P6jpMZdRLcCJznZ/bM85RzZr3d5fzZYuXU72UGdTjO0558iWHDtjtuTYA2e71MDTXUy9YLbk2J5zjmzJsTNmS449cLYzn8SUtFVEPOBst8f2nHNkS46dMVty7DbZUtcD31nSf5X056q8Fzhb0gcl7eRsN8b2nHNks9bt/dW87l6lDqH8C7Ad8EzgQqoLJX0A+DVwmrOdGdtzzpHNWrf3V/O6p2vzrm2Ld13X138KuHm2+5wtP7bnnCObtW7vr+Z19y6lXoFvVf93YQWwvaQJAElLgUc425mxPecc2ax1e381r3u6ph1/GAtwFHBbvfwJ8HXgfKqvGDrO2W6M7TnnyGat2/ured0zttc0MKwFWAJsXd/eGlgN7OZst8b2nHNks9bt/dW87qlLZ04jnCTpyRFxjbPdHttzzpEtOXbGbMmxB8l2sYHfGBErne322J5zjmzJsTNmS449SLbI1QglfXSuu4Adne3G2J5zjmzJsTNmS47dtu4ZoRKvwCXdBbyd2b+F+UMRsczZ8mN7zjmyWev2/mpe9wyDHDhvuwDfAH5vjvt+7Gw3xvacc2Sz1u391bzu3qXUK/Cdgbsj4lfOdndszzlHtuTYGbMlx25b94ztlWjgZmbWXqmLWT1a0kmSrpH0s3rZWK/b0dlujO0558hmrdv7q3ndvUp9lP5zwBbggIhYGhFLgQPrdZ93tjNje845slnr9v5qXvd0TQ+aD2MBrh3kvnHMZq3bc/b+6mo2c929S6lX4DdIeqekXSZXSNpF0ruAnzjbmbE95xzZrHV7fzWve5pSDfxIYClwsaQ7Jd0JXATsDLzC2c6M7TnnyGat2/ured3T+CwUM7Okin2psaQnSzpI0nY96w92tjtje845slnr9v5qXvc0TQ+aD2MB/hK4FvgisAk4bMp965ztxtiec45s1rq9v5rXPWN7TQPDWICrgO3r2xPAGuAt9c+XO9uNsT3nHNmsdXt/Na+7dylyNUJgSUT8EiAiNkk6ADhL0uMAOduZsT3nHNmsdXt/Na97mlLHwH8qadXkD/WEXgIsA37X2c6M7TnnyGat2/ured3TNX3JPowF2APYdY779ne2G2N7zjmyWev2/mped+/i0wjNzJIqdhqhmZm14wZuZpaUG7gVJ2lC0oYhbGe15v7OwaGS9EZJr6lvv1bSY6fc92lJT1mMOmy8+Ri4FSdpAjgnIp5WupZBSLoIeEdErCldi40XvwK3rtha0umSrpR0lqRtJT1T0sWS1ko6T9JuAJKeVf/edyV9cPLVu6QDJJ1T3z5R0qmSLpL0I0l/Wa+fUHUx/Wlj1fcdJOlySVfV2d+q158k6Qf17//9lO2/Q9IRwGrgDEnrJT2qHnN1/XtH1dvbIOkDk5OV9EtJ75d0haRLNeXqdGYL5QZuXfEk4OSIeDrwC+AvgI8BR0TEM4FTgffXv/tPwBsj4jnA/fNs88nAi4B9gb+WtM0cY71Z0iOB04AjI+J3ga2BN6n6DsPDgafWv/++qQNExFlUn6b704hYFRG/nryvPqzyAeAPgVXAsyS9tL57O+DSiNgbuAR4/UJ3lNkkN3Drip9ExLfr2/9C1XifBpwvaT3wV8Aeqr52aoeI+E79u5+ZZ5vnRsQ9EXEHcDsw+Sq3d6zfp2rqP46IH9brTwf+gKrB3w18WtLLgCZfRvss4KKI2BwR9wFn1NsE+A1wTn17LdXHqs0aKfVRerNevW/G3AVcXb/KfpCknRps854pt+/nocd771jBHB9jjoj7JO0LHAS8Ejie6hX1Qsz30eh746E3oKbWZrZgfgVuXbFS0mSzPgq4FFg+uU7SNpKeGhFbgLsk7Vf/7iuHMNa3gGuACUlPqNcfTXXR/e2BR0fEl4G3Uh0K6XUXsMMs678HPE/SMklL6rEuHqBes1m5gVtXbASOkXQl1beTfAw4AviApCuA9cDv1b97LHCypO9Svcr9fy3H+kRE3A28Dvi8pKuAB4BPUjXmc+rfvRh42yzbOw345OSbmJMrI+JW4N3AhcAVVJcL/VLDWs3m5NMILR1J20d9RTdJJwC7RcRbFpidIPEpi2ZT+bibZXSIpHdTPX5vAF5bthyzMvwK3MwsKR8DNzNLyg3czCwpN3Azs6TcwM3MknIDNzNLyg3czCyp/w9KHXZu5JkD8AAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "gdf.set_index('beginposition')['cloudcoverpercentage'].plot(kind='bar')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also want to avoid merging or reprojecting adjacent tiles if possible, so we prefer tiles that easily cover the entire area of interest:" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from sentinel_helpers import plot_all\n", "\n", "plot_all([\n", " gdf, buffered\n", "], [\n", " { 'facecolor': 'none', 'edgecolor': 'blue', 'alpha': 0.1 },\n", " { 'facecolor': 'none', 'edgecolor': 'red' }\n", "])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can subset the result to only take products covering one tile because they all cover the area well.\n", "We select one product before, one during and one after the fire:" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "gdf['tile'] = gdf['title'].apply(lambda t: t.split('_')[5])\n", "gdf = gdf[gdf['tile'] == 'T32UQC']\n", "gdf = gdf.sort_values(by='beginposition')\n", "\n", "before = gdf.iloc[0]\n", "during = gdf.loc['ad590142-a9f2-49a8-8be7-2a6c06454514']\n", "after = gdf.iloc[-1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Download process from LTA" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "downloads, initialized, failed = api.download_all([before['uuid'], during['uuid'], after['uuid']])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dict containing information about succesful donwloads is empty:" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{}" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "downloads" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The second dict contains information about one product.\n", "Notice that the key `'Online'` is `False`: " ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'3506220d-5b7e-4e7a-a3a7-01d272cb5d26': {'id': '3506220d-5b7e-4e7a-a3a7-01d272cb5d26',\n", " 'title': 'S2B_MSIL2A_20180703T101029_N0208_R022_T32UQC_20180703T145931',\n", " 'size': 993411628,\n", " 'md5': '0D93BA047833391172FD8B225E803C27',\n", " 'date': datetime.datetime(2018, 7, 3, 10, 10, 29, 25000),\n", " 'footprint': 'POLYGON((11.977099413076383 51.32472577627447,11.994731157159846 51.36762213853489,12.055061629611966 51.513432056907135,12.115427796855911 51.65922453067321,12.176098601701987 51.80496081562056,12.237329664976563 51.950657514587945,12.298786150689434 52.096349964051925,12.3603752724967 52.24204550642036,12.384930178970409 52.299737130429605,13.539979680877822 52.26313739791785,13.442095184333063 51.27892518278613,11.977099413076383 51.32472577627447))',\n", " 'url': \"https://scihub.copernicus.eu/apihub/odata/v1/Products('3506220d-5b7e-4e7a-a3a7-01d272cb5d26')/$value\",\n", " 'Online': False,\n", " 'Creation Date': datetime.datetime(2018, 7, 3, 18, 8, 57, 716000),\n", " 'Ingestion Date': datetime.datetime(2018, 7, 3, 18, 4, 38, 477000)}}" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ "initialized" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `failed` downloads contains information about two products.\n", "The individual dict entries have a similar shape and contain information comparable to the `initialized` product:" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'ad590142-a9f2-49a8-8be7-2a6c06454514': {'id': 'ad590142-a9f2-49a8-8be7-2a6c06454514',\n", " 'title': 'S2A_MSIL2A_20180728T101031_N0208_R022_T32UQC_20180728T132514',\n", " 'size': 981847648,\n", " 'md5': '012461B4865515B6EC78E09FF4AC91EC',\n", " 'date': datetime.datetime(2018, 7, 28, 10, 10, 31, 24000),\n", " 'footprint': 'POLYGON((11.974785982028196 51.32479810174945,12.002441117705246 51.39206582453723,12.063020073618857 51.537961187081926,12.123890293708246 51.68386315912,12.184952232955526 51.82975048038856,12.24633772850238 51.975531385227455,12.307978784112072 52.121253595050256,12.369726217769836 52.26691782002904,12.383685377764667 52.29977657409941,13.539979680877822 52.26313739791785,13.442095184333063 51.27892518278613,11.974785982028196 51.32479810174945))',\n", " 'url': \"https://scihub.copernicus.eu/apihub/odata/v1/Products('ad590142-a9f2-49a8-8be7-2a6c06454514')/$value\",\n", " 'Online': False,\n", " 'Creation Date': datetime.datetime(2018, 7, 28, 21, 42, 40, 577000),\n", " 'Ingestion Date': datetime.datetime(2018, 7, 28, 21, 40, 25, 18000)},\n", " '0db8938c-7e2c-416d-a41a-5e78544e45c8': {'id': '0db8938c-7e2c-416d-a41a-5e78544e45c8',\n", " 'title': 'S2B_MSIL2A_20180822T101019_N0208_R022_T32UQC_20180822T161243',\n", " 'size': 995797823,\n", " 'md5': 'C43AB0A26A2F6AE6A968E7297E7F12F3',\n", " 'date': datetime.datetime(2018, 8, 22, 10, 10, 19, 24000),\n", " 'footprint': 'POLYGON((11.986535187458271 51.32443078288596,12.027678810555647 51.42474483154029,12.08790243893789 51.570570208036926,12.148431758145344 51.71641516707598,12.201747504713714 51.84399558403028,12.209310176844154 51.86204874930037,12.270959405070856 52.00783765337086,12.312570906902195 52.10583029549706,12.332980270718044 52.15381206631835,12.394862135676313 52.29942241927813,13.539979680877822 52.26313739791785,13.442095184333063 51.27892518278613,11.986535187458271 51.32443078288596))',\n", " 'url': \"https://scihub.copernicus.eu/apihub/odata/v1/Products('0db8938c-7e2c-416d-a41a-5e78544e45c8')/$value\",\n", " 'Online': False,\n", " 'Creation Date': datetime.datetime(2018, 8, 22, 22, 17, 10, 881000),\n", " 'Ingestion Date': datetime.datetime(2018, 8, 22, 22, 14, 23, 699000)}}" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "failed" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0, 1, 2)" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(downloads), len(initialized), len(failed)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`failed` means that a retrieval process could not yet be initialized.\n", "Other instances of failure included an exception that was raised due to an unexpected response of the Copernicus Open Access Hub API with an HTTP response code of `200` - a code that normally indicates that the request was successful.\n", "It is unclear why that response was unexpected.\n", "\n", "Through repeated execution of the cell containing the call to `api.download_all`, all products could be moved from the Long-Term Archive to hot storage and could be downloaded.\n", "The first products could be downloaded after one day and the last product after approximately two days.\n", "Note that the last product might have been available earlier than two days because the re-execution of this cell was a manual process with intermissions." ] }, { "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": "3.8.6" } }, "nbformat": 4, "nbformat_minor": 4 }