Hello!
I am attempting to export NO2 emissions data as a vector data cube at predefined datapoint. My process graph looks similar to below:
{
"process_graph": {
"load2": {
"process_id": "load_collection",
"arguments": {
"id": "SENTINEL_5P_L2",
"spatial_extent": {
"west": 74.1369094108679,
"east": 86.18811680201414,
"south": 20.134290774220062,
"north": 25.61491962553862
},
"temporal_extent": [
"2020-09-01T00:00:00Z",
"2020-09-01T00:00:00Z"
],
"bands": [
"NO2"
]
}
},
"aggregate8": {
"process_id": "aggregate_spatial",
"arguments": {
"data": {
"from_node": "load2"
},
"reducer": {
"process_graph": {
"first1": {
"process_id": "first",
"arguments": {},
"result": true
}
}
},
"geometries": {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
74.96572043489255,
23.299111778868507
]
},
"properties": {
"my_id": 101
}
}
]
}
}
},
"save9": {
"process_id": "save_result",
"arguments": {
"format": "CSV",
"data": {
"from_node": "aggregate8"
}
},
"result": true
}
},
"parameters": []
}
The output csv looks like:
date,feature_index,first(band_0)
2020-09-01T00:00:00.000Z,5,2.0137875253567472E-5
It appears that each feature is getting a seemingly random index. Its difficult to deduce which location the above value belongs. Ideally, I would like to include (wkt) geometry for each row, and at the lease would like to preserve the property I am associating with each feature so that I can do the geometry mapping back as my own post processing step.
Documentation for aggregate_spatial seems to suggest that feature properties should be preserved: “Feature properties are preserved for vector data cubes and all GeoJSON Features.”, yet I do not see those in the output file.
Alternatively, I would appreciate a pointer the most optimal way to convert the sentinel 5 data to vector data if my process in inefficient (I am new to the openEO platform).
I am grateful for the help in advance.