Merge pull request #138 from clausmichele/master

Update of Eurac example
Open-EO · May 8, 2020 · 8a28458 · 8a28458
2 parents d2b8016 + 39302c1
commit 8a28458
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diff --git a/examples/eurac_example.py b/examples/eurac_example.py
@@ -27,19 +27,15 @@
 print(con.list_collections())
 
 # Load a specific dataset
-datacube = con.load_collection(collection_id="S2_L2A_T32TPS_20M", bands=['AOT', 'B02', 'B03', 'B04',
-                                                                         'B05', 'B06', 'B07', 'B8A',
-                                                                         'B11', 'B12', 'SCL', 'VIS',
-                                                                         'WVP', 'CLD', 'SNW'])
-
+datacube = con.load_collection(collection_id="openEO_S2_32632_10m_L2A_D22", bands=['B02', 'B03', 'B04', 'B08'])
 # Perform spatial subsetting (e.g around the city of Bolzano)
-datacube = datacube.filter_bbox(west=11.279182434082033, south=46.464349400461145, east=11.406898498535158,
-                                north=46.522729291844286, crs="EPSG:32632")
-# Perform temporal subsetting (e.g. for the month of august in 2017)
-temp = datacube.filter_temporal(extent=["2017-08-01T00:00:00Z", "2017-08-31T00:00:00Z"])
+datacube = datacube.filter_bbox(west=11.279182434082033, south=46.464349400461145, 
+                                east=11.406898498535158, north=46.522729291844286, crs="EPSG:32632")
+# Perform temporal subsetting (e.g. for the month of june in 2018, only this data available in this collection)
+temp = datacube.filter_temporal(extent=["2018-06-06T00:00:00Z", "2018-06-22T00:00:00Z"])
 # Map features of the dataset to variables (e.g. the red and near infrared band)
 red = temp.band('B04')
-nir = temp.band("B8A")
+nir = temp.band("B08")
 # Perform operation using feature variables (e.g. calculation of NDVI (normalized difference vegetation index))
 datacube = (nir - red) / (nir + red)
 # Reduce on temporal dimension with max operator

diff --git a/examples/notebooks/openEO_Python_Sentinel2_EURAC.ipynb b/examples/notebooks/openEO_Python_Sentinel2_EURAC.ipynb
@@ -73,18 +73,15 @@
    "outputs": [],
    "source": [
     "# load a specific dataset\n",
-    "datacube = con.load_collection(collection_id=\"S2_L2A_T32TPS_20M\", bands=['AOT', 'B02', 'B03', 'B04',\n",
-    "                                                                         'B05', 'B06', 'B07', 'B8A',\n",
-    "                                                                         'B11', 'B12', 'SCL', 'VIS',\n",
-    "                                                                         'WVP', 'CLD', 'SNW'])\n",
+    "datacube = con.load_collection(collection_id=\"openEO_S2_32632_10m_L2A_D22\", bands=['B02', 'B03', 'B04', 'B08'])\n",
     "# perform spatial subsetting (e.g around the city of Bolzano)\n",
     "datacube = datacube.filter_bbox(west=11.279182434082033, south=46.464349400461145, \n",
     "                                east=11.406898498535158, north=46.522729291844286, crs=\"EPSG:32632\")\n",
-    "# perform temporal subsetting (e.g. for the month of august in 2017)\n",
-    "temp = datacube.filter_temporal(extent=[\"2017-08-01T00:00:00Z\", \"2017-08-31T00:00:00Z\"])\n",
+    "# perform temporal subsetting (e.g. for the month of june in 2018, only this data available in this collection)\n",
+    "temp = datacube.filter_temporal(extent=[\"2018-06-06T00:00:00Z\", \"2018-06-22T00:00:00Z\"])\n",
     "# map features of the dataset to variables (e.g. the red and near infrared band)\n",
     "red = temp.band('B04')\n",
-    "nir = temp.band(\"B8A\")\n",
+    "nir = temp.band(\"B08\")\n",
     "# perform operation using feature variables (e.g. calculation of NDVI (normalized difference vegetation index))\n",
     "datacube = (nir - red) / (nir + red)\n",
     "# reduce on temporal dimension with max operator\n",