Match-Up¶
Given a SENTINEL-3 OLCI, i.e. S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004 with specified attributes:
geometry,- [
properties.start_datetime,properties.end_datetime]
search all active AERONET acquisitions, where:
properties.start_datetime- 1h <=Date(dd:mm:yyyy),Time(hh:mm:ss)<=properties.end_datetime+ 1hSite_Latitude(Degrees),Site_Longitude(Degrees)ingeometry
In [1]:
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from datetime import (
datetime,
timedelta,
timezone
)
from dateutil import parser
from httpx import (
Client,
Response
)
from pathlib import Path
from pystac import Item
from typing import Any
import json
import sys
out_dir: Path = Path('.')
with Client() as client:
response: Response = client.get('https://stac.dataspace.copernicus.eu/v1/collections/sentinel-3-olci-1-efr-ntc/items/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004')
item_str: str = response.text
item_dict = json.loads(item_str)
json.dump(item_dict, sys.stdout, indent=2)
from datetime import (
datetime,
timedelta,
timezone
)
from dateutil import parser
from httpx import (
Client,
Response
)
from pathlib import Path
from pystac import Item
from typing import Any
import json
import sys
out_dir: Path = Path('.')
with Client() as client:
response: Response = client.get('https://stac.dataspace.copernicus.eu/v1/collections/sentinel-3-olci-1-efr-ntc/items/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004')
item_str: str = response.text
item_dict = json.loads(item_str)
json.dump(item_dict, sys.stdout, indent=2)
{
"id": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004",
"bbox": [
-1.51876,
39.545,
18.484,
52.4535
],
"type": "Feature",
"links": [
{
"rel": "collection",
"type": "application/json",
"href": "https://stac.dataspace.copernicus.eu/v1/collections/sentinel-3-olci-1-efr-ntc"
},
{
"rel": "parent",
"type": "application/json",
"href": "https://stac.dataspace.copernicus.eu/v1/collections/sentinel-3-olci-1-efr-ntc"
},
{
"rel": "root",
"type": "application/json",
"href": "https://stac.dataspace.copernicus.eu/v1/"
},
{
"rel": "self",
"type": "application/geo+json",
"href": "https://stac.dataspace.copernicus.eu/v1/collections/sentinel-3-olci-1-efr-ntc/items/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004"
},
{
"rel": "version-history",
"href": "https://trace.dataspace.copernicus.eu/api/v1/traces/name/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3.zip",
"type": "application/json",
"title": "Product history record from the CDSE traceability service"
},
{
"rel": "enclosure",
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/",
"type": "application/x-directory",
"title": "S3 path to source directory",
"auth:refs": [
"s3"
],
"storage:refs": [
"cdse-s3",
"creodias-s3"
]
}
],
"assets": {
"product": {
"href": "https://download.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/$value",
"roles": [
"data",
"metadata",
"archive"
],
"auth:refs": [
"oidc"
],
"file:size": 917010187,
"file:checksum": "d501104eee1e9c02472469f718b2230d1ef3da",
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3.zip",
"type": "application/zip",
"title": "Zipped product"
},
"thumbnail": {
"href": "https://catalogue-svc.prod-catalogue.svc.cluster.local:8250/odata/v1/Assets(6686dd76-8f19-4b71-9bf6-ad5ab63488f1)/$value",
"roles": [
"thumbnail"
],
"alternate": {
"s3": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/quicklook.jpg",
"auth:refs": [
"s3"
],
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"alternate:name": "S3"
}
},
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/quicklook.jpg",
"type": "image/jpeg",
"title": "Thumbnail",
"alternate:name": "HTTPS"
},
"tie-meteo": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/tie_meteo.nc",
"roles": [
"data"
],
"alternate": {
"https": {
"href": "https://zipper.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/Nodes(S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3)/Nodes(tie_meteo.nc)/$value",
"auth:refs": [
"oidc"
],
"storage:refs": [],
"alternate:name": "HTTPS"
}
},
"auth:refs": [
"s3"
],
"file:size": 19943871,
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"file:checksum": "d50110916aec3a576cb7a1d77d7b71b0ccf372",
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/tie_meteo.nc",
"type": "application/netcdf",
"title": "Tie Meteo Annotations",
"alternate:name": "S3"
},
"xfdumanifest": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/xfdumanifest.xml",
"roles": [
"metadata"
],
"alternate": {
"https": {
"href": "https://zipper.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/Nodes(S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3)/Nodes(xfdumanifest.xml)/$value",
"auth:refs": [
"oidc"
],
"storage:refs": [],
"alternate:name": "HTTPS"
}
},
"auth:refs": [
"s3"
],
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/xfdumanifest.xml",
"type": "application/xml",
"title": "Product manifest",
"alternate:name": "S3"
},
"quality-flags": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/qualityFlags.nc",
"roles": [
"data"
],
"alternate": {
"https": {
"href": "https://zipper.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/Nodes(S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3)/Nodes(qualityFlags.nc)/$value",
"auth:refs": [
"oidc"
],
"storage:refs": [],
"alternate:name": "HTTPS"
}
},
"auth:refs": [
"s3"
],
"file:size": 2593891,
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"file:checksum": "d501106a1eec127177ba7acb4fdda9abaec180",
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/qualityFlags.nc",
"type": "application/netcdf",
"title": "Quality Flags Annotations",
"alternate:name": "S3"
},
"removed-pixels": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/removed_pixels.nc",
"type": "application/netcdf",
"roles": [
"data"
],
"title": "Removed Pixels information used for SYN L1c reconstruction",
"alternate": {
"https": {
"href": "https://zipper.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/Nodes(S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3)/Nodes(removed_pixels.nc)/$value",
"auth:refs": [
"oidc"
],
"storage:refs": [],
"alternate:name": "HTTPS"
}
},
"auth:refs": [
"s3"
],
"file:size": 26427908,
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"file:checksum": "d50110e085ff6b3623d8f6919b2bf86888e125",
"alternate:name": "S3",
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/removed_pixels.nc"
},
"tie-geometries": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/tie_geometries.nc",
"roles": [
"data"
],
"alternate": {
"https": {
"href": "https://zipper.dataspace.copernicus.eu/odata/v1/Products(464ae0c3-b8b0-46c0-a53c-f42188c413d4)/Nodes(S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3)/Nodes(tie_geometries.nc)/$value",
"auth:refs": [
"oidc"
],
"storage:refs": [],
"alternate:name": "HTTPS"
}
},
"auth:refs": [
"s3"
],
"file:size": 2140363,
"storage:refs": [
"cdse-s3",
"creodias-s3"
],
"file:checksum": "d501101785ec68ec5f232d300aa2d5adaca452",
"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/tie_geometries.nc",
"type": "application/netcdf",
"title": "Tie Geometries Annotations",
"alternate:name": "S3"
},
"geo-coordinates": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/geo_coordinates.nc",
"roles": [
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],
"alternate": {
"https": {
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}
},
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"type": "application/netcdf",
"title": "Geo Coordinates Annotations",
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},
"instrument-data": {
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"roles": [
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],
"alternate": {
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}
},
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],
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"type": "application/netcdf",
"title": "Instrument Data Annotations",
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},
"time-coordinates": {
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"roles": [
"data"
],
"alternate": {
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}
],
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],
"roles": [
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"alternate": {
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"type": "application/netcdf",
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"eo:center_wavelength": 0.4425,
"eo:full_width_half_max": 0.01
}
],
"roles": [
"data"
],
"alternate": {
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"auth:refs": [
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],
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}
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],
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"file:local_path": "S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/Oa03_radiance.nc",
"type": "application/netcdf",
"title": "TOA radiance for OLCI acquisition band Oa03",
"alternate:name": "S3"
},
"Oa04_radianceData": {
"href": "s3://eodata/Sentinel-3/OLCI/OL_1_EFR___/2025/10/31/S3A_OL_1_EFR____20251031T094707_20251031T095007_20251101T104938_0180_132_136_2160_PS1_O_NT_004.SEN3/Oa04_radiance.nc",
"bands": [
{
"name": "Oa04",
"description": "Chlorophyll",
"eo:center_wavelength": 0.49,
"eo:full_width_half_max": 0.01
}
],
"roles": [
"data"
],
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"invalid": 4.0,
"cosmetic": 0.0,
"saturated": 0.0,
"duplicated": 23.0,
"saline_water": 21.0,
"tidal_region": 1.0,
"dubious_samples": 0.0,
"fresh_inland_water": 1.0
},
"instruments": [
"olci"
],
"auth:schemes": {
"s3": {
"type": "s3"
},
"oidc": {
"type": "openIdConnect",
"openIdConnectUrl": "https://identity.dataspace.copernicus.eu/auth/realms/CDSE/.well-known/openid-configuration"
}
},
"end_datetime": "2025-10-31T09:50:06.893754Z",
"product:type": "OL_1_EFR___",
"constellation": "sentinel-3",
"start_datetime": "2025-10-31T09:47:06.893754Z",
"sat:orbit_cycle": 132,
"sat:orbit_state": "descending",
"storage:schemes": {
"cdse-s3": {
"type": "custom-s3",
"title": "Copernicus Data Space Ecosystem S3",
"platform": "https://eodata.dataspace.copernicus.eu",
"description": "This endpoint provides access to EO data which is stored on the object storage of both CloudFerro Cloud and OpenTelekom Cloud (OTC). See the [documentation](https://documentation.dataspace.copernicus.eu/APIs/S3.html) for more information, including how to get credentials.",
"requester_pays": false
},
"creodias-s3": {
"type": "custom-s3",
"title": "CREODIAS S3",
"platform": "https://eodata.cloudferro.com",
"description": "Comprehensive Earth Observation Data (EODATA) archive offered by CREODIAS as a commercial part of CDSE, designed to provide users with access to a vast repository of satellite data without predefined quota limits.",
"requester_pays": true
}
},
"processing:level": "L1",
"processing:version": "03.50",
"product:timeliness": "P1M",
"sat:absolute_orbit": 50544,
"sat:relative_orbit": 136,
"processing:datetime": "2025-11-01T10:50:32.000000Z",
"processing:software": {
"eometadatatool": "251021130925+dirty"
},
"eopf:origin_datetime": "2025-11-01T10:54:46.627000Z",
"product:timeliness_category": "NT",
"sat:platform_international_designator": "2016-011A"
},
"stac_extensions": [
"https://cs-si.github.io/eopf-stac-extension/v1.2.0/schema.json",
"https://stac-extensions.github.io/alternate-assets/v1.2.0/schema.json",
"https://stac-extensions.github.io/authentication/v1.1.0/schema.json",
"https://stac-extensions.github.io/eo/v2.0.0/schema.json",
"https://stac-extensions.github.io/file/v2.1.0/schema.json",
"https://stac-extensions.github.io/processing/v1.2.0/schema.json",
"https://stac-extensions.github.io/product/v1.0.0/schema.json",
"https://stac-extensions.github.io/projection/v2.0.0/schema.json",
"https://stac-extensions.github.io/sat/v1.1.0/schema.json",
"https://stac-extensions.github.io/storage/v2.0.0/schema.json",
"https://stac-extensions.github.io/timestamps/v1.1.0/schema.json"
],
"stac_version": "1.1.0"
}
Execute the search operation¶
In [2]:
Copied!
source_item: Item = Item.from_dict(item_dict)
def _parse_date_from_properties(date_string_id: str) -> datetime:
return parser.parse(source_item.properties[date_string_id])
start_datetime = _parse_date_from_properties('start_datetime') - timedelta(hours=1)
end_datetime = _parse_date_from_properties('end_datetime') + timedelta(hours=1)
def _serialize_date(input_date: datetime) -> str:
dt_utc = input_date.astimezone(timezone.utc)
return dt_utc.isoformat().replace("+00:00", "Z")
cql2_filter = {
"op": "and",
"args": [
{"op": "eq", "args": [{"property": "data_type"}, "AOD10"]},
{"op": "eq", "args": [{"property": "format"}, "csv"]},
{"op": "eq", "args": [{"property": "data_format"}, "daily-average"]},
{
"op": "t_after",
"args": [
{"property": "time"},
{"timestamp": _serialize_date(start_datetime)},
],
},
{
"op": "t_before",
"args": [
{"property": "time"},
{"timestamp": _serialize_date(end_datetime)},
],
},
{
"op": "s_intersects",
"args": [
{"property": "geometry"},
source_item.geometry,
],
}
],
}
json.dump(cql2_filter, sys.stdout, indent=2)
source_item: Item = Item.from_dict(item_dict)
def _parse_date_from_properties(date_string_id: str) -> datetime:
return parser.parse(source_item.properties[date_string_id])
start_datetime = _parse_date_from_properties('start_datetime') - timedelta(hours=1)
end_datetime = _parse_date_from_properties('end_datetime') + timedelta(hours=1)
def _serialize_date(input_date: datetime) -> str:
dt_utc = input_date.astimezone(timezone.utc)
return dt_utc.isoformat().replace("+00:00", "Z")
cql2_filter = {
"op": "and",
"args": [
{"op": "eq", "args": [{"property": "data_type"}, "AOD10"]},
{"op": "eq", "args": [{"property": "format"}, "csv"]},
{"op": "eq", "args": [{"property": "data_format"}, "daily-average"]},
{
"op": "t_after",
"args": [
{"property": "time"},
{"timestamp": _serialize_date(start_datetime)},
],
},
{
"op": "t_before",
"args": [
{"property": "time"},
{"timestamp": _serialize_date(end_datetime)},
],
},
{
"op": "s_intersects",
"args": [
{"property": "geometry"},
source_item.geometry,
],
}
],
}
json.dump(cql2_filter, sys.stdout, indent=2)
{
"op": "and",
"args": [
{
"op": "eq",
"args": [
{
"property": "data_type"
},
"AOD10"
]
},
{
"op": "eq",
"args": [
{
"property": "format"
},
"csv"
]
},
{
"op": "eq",
"args": [
{
"property": "data_format"
},
"daily-average"
]
},
{
"op": "t_after",
"args": [
{
"property": "time"
},
{
"timestamp": "2025-10-31T08:47:06.893754Z"
}
]
},
{
"op": "t_before",
"args": [
{
"property": "time"
},
{
"timestamp": "2025-10-31T10:50:06.893754Z"
}
]
},
{
"op": "s_intersects",
"args": [
{
"property": "geometry"
},
{
"type": "Polygon",
"coordinates": [
[
[
-1.5187599999999999,
41.97070000000001
],
[
13.725899999999998,
39.545
],
[
18.484,
49.88549999999999
],
[
0.10018799999999999,
52.45349999999999
],
[
-1.5187599999999999,
41.97070000000001
]
]
]
}
]
}
]
}
In [3]:
Copied!
from pygeofilter_aeronet import aeronet_search
resulting_item: Item = aeronet_search(
cql2_filter=cql2_filter,
output_dir=out_dir
)
json.dump(resulting_item.to_dict(), sys.stdout, indent=2)
from pygeofilter_aeronet import aeronet_search
resulting_item: Item = aeronet_search(
cql2_filter=cql2_filter,
output_dir=out_dir
)
json.dump(resulting_item.to_dict(), sys.stdout, indent=2)
2025-11-17 16:50:45.008 | SUCCESS | pygeofilter_aeronet:aeronet_search:235 - Query on https://aeronet.gsfc.nasa.gov successfully obtained data: 2025-11-17 16:50:45.029 | SUCCESS | pygeofilter_aeronet:aeronet_search:248 - Data saved to to CSV file: /home/stripodi/Documents/pygeofilter/pygeofilter-aeronet/docs/use_cases/2a3dc9e8-21fd-4e1e-b1be-dbd54e382c4a.csv 2025-11-17 16:50:45.055 | SUCCESS | pygeofilter_aeronet:aeronet_search:282 - Data saved to GeoParquet file: /home/stripodi/Documents/pygeofilter/pygeofilter-aeronet/docs/use_cases/2a3dc9e8-21fd-4e1e-b1be-dbd54e382c4a.parquet
{
"type": "Feature",
"stac_version": "1.1.0",
"stac_extensions": [
"https://stac-extensions.github.io/table/v1.2.0/schema.json"
],
"id": "urn:uuid:2a3dc9e8-21fd-4e1e-b1be-dbd54e382c4a",
"geometry": {
"type": "Polygon",
"coordinates": [
[
[
-170.5644,
-64.239996
],
[
174.768143,
-64.239996
],
[
174.768143,
68.661089
],
[
-170.5644,
68.661089
],
[
-170.5644,
-64.239996
]
]
]
},
"bbox": [
-170.5644,
-64.239996,
174.768143,
68.661089
],
"properties": {
"datetime": "2025-11-17T16:50:45.059928Z"
},
"links": [
{
"rel": "related",
"href": "https://aeronet.gsfc.nasa.gov/cgi-bin/print_web_data_v3?AOD10=1&if_no_html=1&AVG=20&year=2025&month=10&day=31&hour=8&year2=2025&month2=10&day2=31&hour2=10&lon1=-1.5187599999999999&lat1=39.545&lon2=18.484&lat2=52.45349999999999",
"type": "text/csv",
"title": "AERONET Web Service search"
}
],
"assets": {
"csv": {
"href": "2a3dc9e8-21fd-4e1e-b1be-dbd54e382c4a.csv",
"type": "text/csv",
"description": "Search result - CVS Format",
"table:row_count": 634,
"table:columns": [
{
"name": "AERONET_Site",
"col_type": "object"
},
{
"name": "Date(dd:mm:yyyy)",
"col_type": "object"
},
{
"name": "Time(hh:mm:ss)",
"col_type": "object"
},
{
"name": "Day_of_Year",
"col_type": "int64"
},
{
"name": "AOD_1640nm",
"col_type": "float64"
},
{
"name": "AOD_1020nm",
"col_type": "float64"
},
{
"name": "AOD_870nm",
"col_type": "float64"
},
{
"name": "AOD_865nm",
"col_type": "float64"
},
{
"name": "AOD_779nm",
"col_type": "float64"
},
{
"name": "AOD_675nm",
"col_type": "float64"
},
{
"name": "AOD_667nm",
"col_type": "float64"
},
{
"name": "AOD_620nm",
"col_type": "float64"
},
{
"name": "AOD_560nm",
"col_type": "float64"
},
{
"name": "AOD_555nm",
"col_type": "float64"
},
{
"name": "AOD_551nm",
"col_type": "float64"
},
{
"name": "AOD_532nm",
"col_type": "float64"
},
{
"name": "AOD_531nm",
"col_type": "float64"
},
{
"name": "AOD_510nm",
"col_type": "float64"
},
{
"name": "AOD_500nm",
"col_type": "float64"
},
{
"name": "AOD_490nm",
"col_type": "float64"
},
{
"name": "AOD_443nm",
"col_type": "float64"
},
{
"name": "AOD_440nm",
"col_type": "float64"
},
{
"name": "AOD_412nm",
"col_type": "float64"
},
{
"name": "AOD_400nm",
"col_type": "float64"
},
{
"name": "AOD_380nm",
"col_type": "float64"
},
{
"name": "AOD_340nm",
"col_type": "float64"
},
{
"name": "Precipitable_Water(cm)",
"col_type": "float64"
},
{
"name": "AOD_681nm",
"col_type": "float64"
},
{
"name": "AOD_709nm",
"col_type": "float64"
},
{
"name": "AOD_Empty",
"col_type": "float64"
},
{
"name": "AOD_Empty.1",
"col_type": "float64"
},
{
"name": "AOD_Empty.2",
"col_type": "float64"
},
{
"name": "AOD_Empty.3",
"col_type": "float64"
},
{
"name": "AOD_Empty.4",
"col_type": "float64"
},
{
"name": "440-870_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "380-500_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "440-675_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "500-870_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "340-440_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "440-675_Angstrom_Exponent[Polar]",
"col_type": "float64"
},
{
"name": "N[AOD_1640nm]",
"col_type": "int64"
},
{
"name": "N[AOD_1020nm]",
"col_type": "int64"
},
{
"name": "N[AOD_870nm]",
"col_type": "int64"
},
{
"name": "N[AOD_865nm]",
"col_type": "int64"
},
{
"name": "N[AOD_779nm]",
"col_type": "int64"
},
{
"name": "N[AOD_675nm]",
"col_type": "int64"
},
{
"name": "N[AOD_667nm]",
"col_type": "int64"
},
{
"name": "N[AOD_620nm]",
"col_type": "int64"
},
{
"name": "N[AOD_560nm]",
"col_type": "int64"
},
{
"name": "N[AOD_555nm]",
"col_type": "int64"
},
{
"name": "N[AOD_551nm]",
"col_type": "int64"
},
{
"name": "N[AOD_532nm]",
"col_type": "int64"
},
{
"name": "N[AOD_531nm]",
"col_type": "int64"
},
{
"name": "N[AOD_510nm]",
"col_type": "int64"
},
{
"name": "N[AOD_500nm]",
"col_type": "int64"
},
{
"name": "N[AOD_490nm]",
"col_type": "int64"
},
{
"name": "N[AOD_443nm]",
"col_type": "int64"
},
{
"name": "N[AOD_440nm]",
"col_type": "int64"
},
{
"name": "N[AOD_412nm]",
"col_type": "int64"
},
{
"name": "N[AOD_400nm]",
"col_type": "int64"
},
{
"name": "N[AOD_380nm]",
"col_type": "int64"
},
{
"name": "N[AOD_340nm]",
"col_type": "int64"
},
{
"name": "N[Precipitable_Water(cm)]",
"col_type": "int64"
},
{
"name": "N[AOD_681nm]",
"col_type": "int64"
},
{
"name": "N[AOD_709nm]",
"col_type": "int64"
},
{
"name": "N[AOD_Empty]",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].1",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].2",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].3",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].4",
"col_type": "int64"
},
{
"name": "N[440-870_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[380-500_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[440-675_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[500-870_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[340-440_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[440-675_Angstrom_Exponent[Polar]]",
"col_type": "int64"
},
{
"name": "Data_Quality_Level",
"col_type": "object"
},
{
"name": "AERONET_Instrument_Number",
"col_type": "int64"
},
{
"name": "AERONET_Site_Name",
"col_type": "object"
},
{
"name": "Site_Latitude(Degrees)",
"col_type": "float64"
},
{
"name": "Site_Longitude(Degrees)",
"col_type": "float64"
},
{
"name": "Site_Elevation(m)",
"col_type": "float64"
}
]
},
"geoparquet": {
"href": "2a3dc9e8-21fd-4e1e-b1be-dbd54e382c4a.parquet",
"type": "application/vnd.apache.parquet",
"description": "Search result - GeoParquet Format",
"table:row_count": 634,
"table:columns": [
{
"name": "AERONET_Site",
"col_type": "object"
},
{
"name": "Date(dd:mm:yyyy)",
"col_type": "object"
},
{
"name": "Time(hh:mm:ss)",
"col_type": "object"
},
{
"name": "Day_of_Year",
"col_type": "int64"
},
{
"name": "AOD_1640nm",
"col_type": "float64"
},
{
"name": "AOD_1020nm",
"col_type": "float64"
},
{
"name": "AOD_870nm",
"col_type": "float64"
},
{
"name": "AOD_865nm",
"col_type": "float64"
},
{
"name": "AOD_779nm",
"col_type": "float64"
},
{
"name": "AOD_675nm",
"col_type": "float64"
},
{
"name": "AOD_667nm",
"col_type": "float64"
},
{
"name": "AOD_620nm",
"col_type": "float64"
},
{
"name": "AOD_560nm",
"col_type": "float64"
},
{
"name": "AOD_555nm",
"col_type": "float64"
},
{
"name": "AOD_551nm",
"col_type": "float64"
},
{
"name": "AOD_532nm",
"col_type": "float64"
},
{
"name": "AOD_531nm",
"col_type": "float64"
},
{
"name": "AOD_510nm",
"col_type": "float64"
},
{
"name": "AOD_500nm",
"col_type": "float64"
},
{
"name": "AOD_490nm",
"col_type": "float64"
},
{
"name": "AOD_443nm",
"col_type": "float64"
},
{
"name": "AOD_440nm",
"col_type": "float64"
},
{
"name": "AOD_412nm",
"col_type": "float64"
},
{
"name": "AOD_400nm",
"col_type": "float64"
},
{
"name": "AOD_380nm",
"col_type": "float64"
},
{
"name": "AOD_340nm",
"col_type": "float64"
},
{
"name": "Precipitable_Water(cm)",
"col_type": "float64"
},
{
"name": "AOD_681nm",
"col_type": "float64"
},
{
"name": "AOD_709nm",
"col_type": "float64"
},
{
"name": "AOD_Empty",
"col_type": "float64"
},
{
"name": "AOD_Empty.1",
"col_type": "float64"
},
{
"name": "AOD_Empty.2",
"col_type": "float64"
},
{
"name": "AOD_Empty.3",
"col_type": "float64"
},
{
"name": "AOD_Empty.4",
"col_type": "float64"
},
{
"name": "440-870_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "380-500_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "440-675_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "500-870_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "340-440_Angstrom_Exponent",
"col_type": "float64"
},
{
"name": "440-675_Angstrom_Exponent[Polar]",
"col_type": "float64"
},
{
"name": "N[AOD_1640nm]",
"col_type": "int64"
},
{
"name": "N[AOD_1020nm]",
"col_type": "int64"
},
{
"name": "N[AOD_870nm]",
"col_type": "int64"
},
{
"name": "N[AOD_865nm]",
"col_type": "int64"
},
{
"name": "N[AOD_779nm]",
"col_type": "int64"
},
{
"name": "N[AOD_675nm]",
"col_type": "int64"
},
{
"name": "N[AOD_667nm]",
"col_type": "int64"
},
{
"name": "N[AOD_620nm]",
"col_type": "int64"
},
{
"name": "N[AOD_560nm]",
"col_type": "int64"
},
{
"name": "N[AOD_555nm]",
"col_type": "int64"
},
{
"name": "N[AOD_551nm]",
"col_type": "int64"
},
{
"name": "N[AOD_532nm]",
"col_type": "int64"
},
{
"name": "N[AOD_531nm]",
"col_type": "int64"
},
{
"name": "N[AOD_510nm]",
"col_type": "int64"
},
{
"name": "N[AOD_500nm]",
"col_type": "int64"
},
{
"name": "N[AOD_490nm]",
"col_type": "int64"
},
{
"name": "N[AOD_443nm]",
"col_type": "int64"
},
{
"name": "N[AOD_440nm]",
"col_type": "int64"
},
{
"name": "N[AOD_412nm]",
"col_type": "int64"
},
{
"name": "N[AOD_400nm]",
"col_type": "int64"
},
{
"name": "N[AOD_380nm]",
"col_type": "int64"
},
{
"name": "N[AOD_340nm]",
"col_type": "int64"
},
{
"name": "N[Precipitable_Water(cm)]",
"col_type": "int64"
},
{
"name": "N[AOD_681nm]",
"col_type": "int64"
},
{
"name": "N[AOD_709nm]",
"col_type": "int64"
},
{
"name": "N[AOD_Empty]",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].1",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].2",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].3",
"col_type": "int64"
},
{
"name": "N[AOD_Empty].4",
"col_type": "int64"
},
{
"name": "N[440-870_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[380-500_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[440-675_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[500-870_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[340-440_Angstrom_Exponent]",
"col_type": "int64"
},
{
"name": "N[440-675_Angstrom_Exponent[Polar]]",
"col_type": "int64"
},
{
"name": "Data_Quality_Level",
"col_type": "object"
},
{
"name": "AERONET_Instrument_Number",
"col_type": "int64"
},
{
"name": "AERONET_Site_Name",
"col_type": "object"
},
{
"name": "Site_Latitude(Degrees)",
"col_type": "float64"
},
{
"name": "Site_Longitude(Degrees)",
"col_type": "float64"
},
{
"name": "Site_Elevation(m)",
"col_type": "float64"
},
{
"name": "geometry",
"col_type": "geometry"
},
{
"name": "datetime",
"col_type": "datetime64[ns]"
}
]
}
}
}
Visualize the results as Data Frame¶
In [4]:
Copied!
from geopandas import read_parquet
from geopandas.geodataframe import GeoDataFrame
geoparquet_file: str = resulting_item.get_assets()['geoparquet'].href
geoparquet_data: GeoDataFrame = read_parquet(geoparquet_file)
geoparquet_data
from geopandas import read_parquet
from geopandas.geodataframe import GeoDataFrame
geoparquet_file: str = resulting_item.get_assets()['geoparquet'].href
geoparquet_data: GeoDataFrame = read_parquet(geoparquet_file)
geoparquet_data
Out[4]:
| AERONET_Site | Date(dd:mm:yyyy) | Time(hh:mm:ss) | Day_of_Year | AOD_1640nm | AOD_1020nm | AOD_870nm | AOD_865nm | AOD_779nm | AOD_675nm | ... | N[340-440_Angstrom_Exponent] | N[440-675_Angstrom_Exponent[Polar]] | Data_Quality_Level | AERONET_Instrument_Number | AERONET_Site_Name | Site_Latitude(Degrees) | Site_Longitude(Degrees) | Site_Elevation(m) | geometry | datetime | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Tucson | 30:10:2025 | 12:00:00 | 303 | 0.022759 | 0.030613 | 0.032073 | -999.0 | -999.0 | 0.034822 | ... | 99 | 0 | lev10 | 1171 | Tucson | 32.233002 | -110.953003 | 779.000 | POINT (-110.953 32.233) | 2025-10-30 12:00:00 |
| 1 | Tucson | 31:10:2025 | 12:00:00 | 304 | 0.060602 | 0.065395 | 0.065430 | -999.0 | -999.0 | 0.067265 | ... | 96 | 0 | lev10 | 1171 | Tucson | 32.233002 | -110.953003 | 779.000 | POINT (-110.953 32.233) | 2025-10-31 12:00:00 |
| 2 | GSFC | 30:10:2025 | 12:00:00 | 303 | 0.007240 | 0.016739 | 0.022338 | -999.0 | -999.0 | 0.033286 | ... | 32 | 0 | lev10 | 1072 | GSFC | 38.992500 | -76.839833 | 87.000 | POINT (-76.83983 38.9925) | 2025-10-30 12:00:00 |
| 3 | GSFC | 31:10:2025 | 12:00:00 | 304 | 0.012323 | 0.020479 | 0.024331 | -999.0 | -999.0 | 0.031947 | ... | 82 | 0 | lev10 | 1072 | GSFC | 38.992500 | -76.839833 | 87.000 | POINT (-76.83983 38.9925) | 2025-10-31 12:00:00 |
| 4 | Wallops | 30:10:2025 | 12:00:00 | 303 | 0.033409 | 0.050313 | 0.056961 | -999.0 | -999.0 | 0.073485 | ... | 1 | 0 | lev10 | 1490 | Wallops | 37.932850 | -75.471950 | 37.000 | POINT (-75.47195 37.93285) | 2025-10-30 12:00:00 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 629 | Jeonju_RDA | 30:10:2025 | 12:00:00 | 303 | 1.320580 | 1.250719 | 1.240559 | -999.0 | -999.0 | 1.241184 | ... | 37 | 0 | lev10 | 1535 | Jeonju_RDA | 35.828371 | 127.055012 | 42.174 | POINT (127.05501 35.82837) | 2025-10-30 12:00:00 |
| 630 | Invercargill_TROPOS | 30:10:2025 | 12:00:00 | 303 | 0.043877 | 0.052294 | 0.056676 | -999.0 | -999.0 | 0.061928 | ... | 18 | 0 | lev10 | 1378 | Invercargill_TROPOS | -46.417479 | 168.330753 | 5.000 | POINT (168.33075 -46.41748) | 2025-10-30 12:00:00 |
| 631 | Invercargill_TROPOS | 31:10:2025 | 12:00:00 | 304 | 0.091755 | 0.093959 | 0.104787 | -999.0 | -999.0 | 0.102952 | ... | 1 | 0 | lev10 | 1378 | Invercargill_TROPOS | -46.417479 | 168.330753 | 5.000 | POINT (168.33075 -46.41748) | 2025-10-31 12:00:00 |
| 632 | CIBA | 30:10:2025 | 12:00:00 | 303 | 0.484599 | 0.444755 | 0.428063 | -999.0 | -999.0 | 0.410291 | ... | 7 | 0 | lev10 | 383 | CIBA | 41.814000 | -4.932400 | 839.000 | POINT (-4.9324 41.814) | 2025-10-30 12:00:00 |
| 633 | CIBA | 31:10:2025 | 12:00:00 | 304 | 0.659554 | 0.604430 | 0.603941 | -999.0 | -999.0 | 0.572371 | ... | 2 | 0 | lev10 | 383 | CIBA | 41.814000 | -4.932400 | 839.000 | POINT (-4.9324 41.814) | 2025-10-31 12:00:00 |
634 rows × 84 columns
Visualize results on Map screen¶
In [5]:
Copied!
from folium import (
GeoJson,
LayerControl,
Map
)
from geopandas import GeoSeries
from folium.plugins import (
Fullscreen
)
from shapely.geometry import shape
from shapely.geometry.base import BaseGeometry
from stac_geoparquet.arrow import parse_stac_items_to_arrow
geoparquet_data = geoparquet_data.dissolve(by='AERONET_Site')
if source_item.geometry:
filter_geom: BaseGeometry = shape(source_item.geometry)
if geoparquet_data.crs:
filter_series = GeoSeries(
[filter_geom],
crs="EPSG:4326"
).to_crs(geoparquet_data.crs).iloc[0]
geoparquet_data = geoparquet_data[geoparquet_data.geometry.within(filter_geom)]
map: Map = Map()
layer_control = LayerControl(position="topright", collapsed=True)
fullscreen = Fullscreen()
GeoJson(
geoparquet_data.to_json(default=str),
name="Stac Item footprints",
style_function=lambda x: {"fillColor": "#00000000", "color": "#0000ff", "weight": 1},
control=True,
).add_to(map)
GeoJson(
source_item,
name="Polygon",
style_function=lambda f: {
"fillColor": "yellow",
"color": "red",
"weight": 2,
"fillOpacity": 0.3,
}
).add_to(map)
layer_control.add_to(map)
fullscreen.add_to(map)
map.fit_bounds(map.get_bounds()) # type: ignore not to important for the demo
map
from folium import (
GeoJson,
LayerControl,
Map
)
from geopandas import GeoSeries
from folium.plugins import (
Fullscreen
)
from shapely.geometry import shape
from shapely.geometry.base import BaseGeometry
from stac_geoparquet.arrow import parse_stac_items_to_arrow
geoparquet_data = geoparquet_data.dissolve(by='AERONET_Site')
if source_item.geometry:
filter_geom: BaseGeometry = shape(source_item.geometry)
if geoparquet_data.crs:
filter_series = GeoSeries(
[filter_geom],
crs="EPSG:4326"
).to_crs(geoparquet_data.crs).iloc[0]
geoparquet_data = geoparquet_data[geoparquet_data.geometry.within(filter_geom)]
map: Map = Map()
layer_control = LayerControl(position="topright", collapsed=True)
fullscreen = Fullscreen()
GeoJson(
geoparquet_data.to_json(default=str),
name="Stac Item footprints",
style_function=lambda x: {"fillColor": "#00000000", "color": "#0000ff", "weight": 1},
control=True,
).add_to(map)
GeoJson(
source_item,
name="Polygon",
style_function=lambda f: {
"fillColor": "yellow",
"color": "red",
"weight": 2,
"fillOpacity": 0.3,
}
).add_to(map)
layer_control.add_to(map)
fullscreen.add_to(map)
map.fit_bounds(map.get_bounds()) # type: ignore not to important for the demo
map
Out[5]:
Make this Notebook Trusted to load map: File -> Trust Notebook