"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# The GeoJSON representation has to be slightly adapted for the time slider\n",
"adapted_prods = products.as_geojson_object()\n",
"for feature in adapted_prods[\"features\"]:\n",
" feature[\"properties\"][\"time\"] = feature[\"properties\"][\"startTimeFromAscendingNode\"]\n",
"\n",
"# Create a map zoomed over the search area\n",
"fmap = folium.Map([44.5, 5], zoom_start=8)\n",
"# Add a layer that map the tile's centroid\n",
"folium.GeoJson(\n",
" data=targeted_tile,\n",
" tooltip = targeted_tile_name,\n",
").add_to(fmap)\n",
"# Add layer that temporally maps the products found\n",
"TimestampedGeoJson(\n",
" adapted_prods,\n",
" transition_time=50, # Transition duration in ms\n",
" period=\"PT3H\", # Array of times, here every 3 hours\n",
" duration=\"PT12H\", # Feature display duragion, here 6 hours\n",
" time_slider_drag_update=True, # Update the map when the slider is dragged\n",
" auto_play=False, # Don't auto play the animation\n",
").add_to(fmap)\n",
"fmap"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"Note\n",
"\n",
"Instead of using the tile's centroid we could have directly used its extent and filter the returned products to keep only those fully contained within the tile. Check out the section dedicated to [filtering products](../api_user_guide/6_crunch.ipynb) in the API user guide.\n",
"\n",
"
\n",
"\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Multiple tiles"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can search for products that overlap with several tiles using a **regular expression**. We use the expression `\"31T[CDE][MLK]\"` to look for products over 9 different tiles (*31TCM*, *31TCL*, *31TCK*, *31TDM*, etc.) over France."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2023-10-17 15:39:55,883 eodag.core [INFO ] Searching product type 'S2_MSI_L1C' on provider: peps\n",
"2023-10-17 15:39:55,884 eodag.core [INFO ] Iterate search over multiple pages: page #1\n",
"2023-10-17 15:39:55,885 eodag.search.qssearch [INFO ] Sending search request: https://peps.cnes.fr/resto/api/collections/S2ST/search.json?startDate=2018-06-01&completionDate=2018-06-15&geometry=MULTIPOINT (3.7147 46.4567, 3.7032 45.5565, 3.6922 44.6568, 2.4122 46.4574, 2.4216 45.5572, 1.1109 46.4433, 1.1413 45.5436, 1.1703 44.6442, 2.4306 44.6575)&productType=S2MSI1C&maxRecords=500&page=1\n",
"2023-10-17 15:39:57,428 eodag.core [INFO ] Found 32 result(s) on provider 'peps'\n"
]
}
],
"source": [
"products = dag.search_all(\n",
" locations=dict(s2_tile_centroid=\"31T[CDE][MLK]\"),\n",
" **default_search_criteria\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"32 were found given the above search criteria\n"
]
}
],
"source": [
"print(f\"{len(products)} were found given the above search criteria\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The products are displayed on an interactive map. By hovering over them you can observe that the MGRS number of the tiles match with the regular expressions we used."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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