Prerequisites:
To search and access DEDL data a DestinE user account is needed
Code used in this context takes inspiration from the Python API User Guide produced by CS Group.
EODAG is a command line tool and a Python package for searching and downloading earth observation data via a unified API.
This tutorial demonstrates how to use EODAG to search and access DEDL data. The notebook uses the DEDL provider in EODAG to access data via Python code.
Setup: EODAG configuration to use the provider DEDL .
Search: search DEDL data, we search for Sentinel-3 data.
Filter: filter DEDL data.
Download: download DEDL data.
The complete guide on how to use EODAG Python API is available via https://
Note:
Please note that the two factor authentication (2FA) is still not implemented in EODAG. The users who have enabled 2FA on DESP will not be able to run this notebook.
Setup¶
In this section, we set:
The output_dir, the directory where to store downloaded products.
The DEDL credentials, you’ll be asked to enter your DEDL credentials.
The search timeout, it is of 60 seconds to avoid any unexpected errors because of long running search queries.
import os
from getpass import getpass
workspace = 'eodag_workspace'
if not os.path.isdir(workspace):
os.mkdir(workspace)
os.environ["EODAG__DEDL__DOWNLOAD__OUTPUT_DIR"] = os.path.abspath(workspace)
#os.environ["EODAG__DEDL__DOWNLOAD__OUTPUTS_PREFIX"] = os.path.abspath(workspace)
os.environ["EODAG__DEDL__PRIORITY"]="10"
os.environ["EODAG__DEDL__SEARCH__TIMEOUT"]="60"
DESP_USERNAME = input("Please input your DESP username or email: ")
DESP_PASSWORD = getpass("Please input your DESP password: ")
os.environ["EODAG__DEDL__AUTH__CREDENTIALS__USERNAME"]=DESP_USERNAME
os.environ["EODAG__DEDL__AUTH__CREDENTIALS__PASSWORD"]=DESP_PASSWORD
Please input your DESP username or email: eum-dedl-user
Please input your DESP password: ········
Import EODAG and list available products on DEDL¶
We now need to import the EODataAccessGateway class. The class is going to take care of all the following operations.
We can start listing the products available using dedl as provider.
from eodag import EODataAccessGateway, setup_logging
dag = EODataAccessGateway()
setup_logging(0)print("\033[1mID - Title\033[0m")
# Rows
for pt in dag.list_product_types("dedl"):
print(f'{pt["ID"]} - {pt["title"]}')ID - Title
EO.AERIS.DAT.IAGOS - In-service Aircraft for a Global Observing System
EO.CLMS.DAT.CORINE - CORINE Land Cover
EO.CLMS.DAT.GLO.DMP300_V1 - 10-daily Dry Matter Productivity 333M
EO.CLMS.DAT.GLO.FAPAR300_V1 - Global 10-daily Fraction of Absorbed PAR 333m
EO.CLMS.DAT.GLO.FCOVER300_V1 - Global 10-daily Fraction of Vegetation Cover 333m
EO.CLMS.DAT.GLO.GDMP300_V1 - 10-daily Gross Dry Matter Productivity 333M
EO.CLMS.DAT.GLO.LAI300_V1 - Global 10-daily Leaf Area Index 333m
EO.CLMS.DAT.GLO.NDVI300_V1 - Global 10-daily Normalized Difference Vegetation Index 333M
EO.CLMS.DAT.GLO.NDVI_1KM_V2 - Normalized Difference Vegetation Index: global Long Term Statistics (raster 1km) - version 2, Apr 2019
EO.CLMS.DAT.SENTINEL-2.HRVPP.VI - Vegetation Indices, daily, UTM projection
EO.DEM.DAT.COP-DEM_GLO-30-DGED - Copernicus DEM GLO-30 DGED
EO.DEM.DAT.COP-DEM_GLO-30-DTED - Copernicus DEM GLO-30 DTED
EO.DEM.DAT.COP-DEM_GLO-90-DGED - Copernicus DEM GLO-90 DGED
EO.DEM.DAT.COP-DEM_GLO-90-DTED - Copernicus DEM GLO-90 DTED
EO.ECMWF.DAT.CAMS_EUROPE_AIR_QUALITY_FORECASTS - CAMS European air quality forecasts
EO.ECMWF.DAT.CAMS_EUROPE_AIR_QUALITY_REANALYSES - CAMS European air quality reanalyses
EO.ECMWF.DAT.CAMS_GLOBAL_ATMOSHERIC_COMPO_FORECAST - CAMS global atmospheric composition forecasts
EO.ECMWF.DAT.CAMS_GLOBAL_EMISSION_INVENTORIES - CAMS global emission inventories
EO.ECMWF.DAT.CAMS_GLOBAL_FIRE_EMISSIONS_GFAS - CAMS global biomass burning emissions based on fire radiative power (GFAS)
EO.ECMWF.DAT.CAMS_GLOBAL_GREENHOUSE_GAS_REANALYSIS - CAMS global greenhouse gas reanalysis (EGG4)
EO.ECMWF.DAT.CAMS_GLOBAL_GREENHOUSE_GAS_REANALYSIS_MONTHLY_AV_FIELDS - CAMS global greenhouse gas reanalysis (EGG4) monthly averaged fields
EO.ECMWF.DAT.CAMS_GLOBAL_RADIATIVE_FORCING - CAMS global radiative forcings
EO.ECMWF.DAT.CAMS_GLOBAL_RADIATIVE_FORCING_AUX - CAMS global radiative forcing - auxilliary variables
EO.ECMWF.DAT.CAMS_GLOBAL_REANALYSIS_EAC4 - CAMS global reanalysis (EAC4)
EO.ECMWF.DAT.CAMS_GLOBAL_REANALYSIS_EAC4_MONTHLY_AV_FIELDS - CAMS global reanalysis (EAC4) monthly averaged fields
EO.ECMWF.DAT.CAMS_GREENHOUSE_GAS_FLUXES - CAMS global inversion-optimised greenhouse gas fluxes and concentrations
EO.ECMWF.DAT.CAMS_SOLAR_RADIATION_TIMESERIES - CAMS solar radiation time-series
EO.ECMWF.DAT.CEMS_FIRE_HISTORICAL - Fire danger indices historical data from the Copernicus Emergency Management Service
EO.ECMWF.DAT.CEMS_GLOFAS_FORECAST - River discharge and related forecasted data by the Global Flood Awareness System
EO.ECMWF.DAT.CEMS_GLOFAS_HISTORICAL - River discharge and related historical data from the Global Flood Awareness System
EO.ECMWF.DAT.CEMS_GLOFAS_REFORECAST - Reforecasts of river discharge and related data by the Global Flood Awareness System
EO.ECMWF.DAT.CEMS_GLOFAS_SEASONAL - Seasonal forecasts of river discharge and related data by the Global Flood Awareness System
EO.ECMWF.DAT.CEMS_GLOFAS_SEASONAL_REFORECAST - Seasonal reforecasts of river discharge and related data from the Global Flood Awareness System
EO.ECMWF.DAT.CO2_DATA_FROM_SATELLITE_SENSORS_2002_PRESENT - Carbon dioxide data from 2002 to present derived from satellite observations
EO.ECMWF.DAT.DERIVED_GRIDDED_GLACIER_MASS_CHANGE - Glacier mass change gridded data from 1976 to present derived from the Fluctuations of Glaciers Database
EO.ECMWF.DAT.DT_CLIMATE_ADAPTATION - Climate Change Adaptation Digital Twin (DT)
EO.ECMWF.DAT.DT_EXTREMES - Weather and Geophysical Extremes Digital Twin (DT)
EO.ECMWF.DAT.EFAS_FORECAST - River discharge and related forecasted data by the European Flood Awareness System
EO.ECMWF.DAT.EFAS_HISTORICAL - River discharge and related historical data from the European Flood Awareness System
EO.ECMWF.DAT.EFAS_REFORECAST - Reforecasts of river discharge and related data by the European Flood Awareness System
EO.ECMWF.DAT.EFAS_SEASONAL - Seasonal forecasts of river discharge and related data by the European Flood Awareness System
EO.ECMWF.DAT.EFAS_SEASONAL_REFORECAST - Seasonal reforecasts of river discharge and related data by the European Flood Awareness System
EO.ECMWF.DAT.ERA5_HOURLY_VARIABLES_ON_PRESSURE_LEVELS - ERA5 hourly data on pressure levels from 1940 to present
EO.ECMWF.DAT.ERA5_LAND_HOURLY - ERA5-Land hourly data from 1950 to present
EO.ECMWF.DAT.ERA5_LAND_MONTHLY - ERA5-Land monthly averaged data from 1950 to present
EO.ECMWF.DAT.ERA5_MONTHLY_MEANS_VARIABLES_ON_PRESSURE_LEVELS - ERA5 monthly averaged data on pressure levels from 1940 to present
EO.ECMWF.DAT.GLACIERS_DISTRIBUTION_DATA_FROM_RANDOLPH_GLACIER_INVENTORY_2000 - Glaciers distribution data from the Randolph Glacier Inventory for year 2000
EO.ECMWF.DAT.METHANE_DATA_SATELLITE_SENSORS_2002_PRESENT - Methane data from 2003 to present derived from satellite observations
EO.ECMWF.DAT.REANALYSIS_ERA5_SINGLE_LEVELS - ERA5 hourly data on single levels from 1940 to present
EO.ECMWF.DAT.REANALYSIS_ERA5_SINGLE_LEVELS_MONTHLY_MEANS - ERA5 monthly averaged data on single levels from 1940 to present
EO.ECMWF.DAT.REANALYSIS_UERRA_EUROPE_SINGLE_LEVELS - UERRA regional reanalysis for Europe on single levels from 1961 to 2019
EO.ECMWF.DAT.SATELLITE_SEA_ICE_CONCENTRATION - Sea ice concentration daily gridded data from 1978 to present derived from satellite observations
EO.ECMWF.DAT.SATELLITE_SEA_ICE_EDGE_TYPE - Sea ice edge and type daily gridded data from 1978 to present derived from satellite observations
EO.ECMWF.DAT.SATELLITE_SEA_ICE_THICKNESS - Sea ice thickness monthly gridded data for the Arctic from 2002 to present derived from satellite observations
EO.ECMWF.DAT.SEASONAL_FORECAST_ANOMALIES_ON_PRESSURE_LEVELS_2017_PRESENT - Seasonal forecast anomalies on pressure levels
EO.ECMWF.DAT.SEASONAL_FORECAST_ANOMALIES_ON_SINGLE_LEVELS_2017_PRESENT - Seasonal forecast anomalies on single levels
EO.ECMWF.DAT.SEASONAL_FORECAST_DAILY_DATA_ON_PRESSURE_LEVELS_2017_PRESENT - Seasonal forecast subdaily data on pressure levels
EO.ECMWF.DAT.SEASONAL_FORECAST_DAILY_DATA_ON_SINGLE_LEVELS_2017_PRESENT - Seasonal forecast daily and subdaily data on single levels
EO.ECMWF.DAT.SEASONAL_FORECAST_MONTHLY_STATISTICS_ON_PRESSURE_LEVELS_2017_PRESENT - Seasonal forecast monthly statistics on pressure levels
EO.ECMWF.DAT.SEASONAL_FORECAST_MONTHLY_STATISTICS_ON_SINGLE_LEVELS_2017_PRESENT - Seasonal forecast monthly statistics on single levels
EO.ECMWF.DAT.SEA_LEVEL_DAILY_GRIDDED_DATA_FOR_GLOBAL_OCEAN_1993_PRESENT - Sea level gridded data from satellite observations for the global ocean
EO.ECMWF.DAT.SIS_HYDROLOGY_METEOROLOGY_DERIVED_PROJECTIONS - Temperature and precipitation climate impact indicators from 1970 to 2100 derived from European climate projections
EO.ECMWF.DAT.SIS_HYDROLOGY_VARIABLES_DERIVED_PROJECTIONS - Hydrology-related climate impact indicators from 1970 to 2100 derived from bias adjusted European climate projections
EO.ESA.DAT.SENTINEL-1.L1_GRD - SENTINEL1 Level-1 Ground Range Detected
EO.ESA.DAT.SENTINEL-1.L1_SLC - SENTINEL1 Level-1 Single Look Complex
EO.ESA.DAT.SENTINEL-2.MSI.L1C - SENTINEL2 Level-1C
EO.ESA.DAT.SENTINEL-2.MSI.L2A - SENTINEL2 Level-2A
EO.ESA.DAT.SENTINEL-3.OL_2_LFR___ - SENTINEL3 OLCI Level-2 Land Full Resolution
EO.ESA.DAT.SENTINEL-3.OL_2_LRR___ - SENTINEL3 OLCI Level-2 Land Reduced Resolution
EO.ESA.DAT.SENTINEL-3.SL_2_LST___ - SENTINEL3 SLSTR Level-2 LST
EO.ESA.DAT.SENTINEL-3.SR_2_LAN___ - SENTINEL3 SRAL Level-2 LAN
EO.ESA.DAT.SENTINEL-5P.TROPOMI.L1 - Sentinel-5 Precursor Level 1B Irradiances for the SWIR and UNV bands
EO.ESA.DAT.SENTINEL-5P.TROPOMI.L2 - Sentinel-5 Precursor Level 2 Data
EO.EUM.CM.METOP.ASCSZFR02 - ASCAT Level 1 SZF Climate Data Record Release 2 - Metop
EO.EUM.CM.METOP.ASCSZOR02 - ASCAT Level 1 SZO Climate Data Record Release 2 - Metop
EO.EUM.CM.METOP.ASCSZRR02 - ASCAT Level 1 SZR Climate Data Record Release 2 - Metop
EO.EUM.DAT.AMVR02 - Atmospheric Motion Vectors Climate Data Record Release 2 - MFG and MSG - 0 degree
EO.EUM.DAT.GSAL2R02 - GSA Level 2 Climate Data Record Release 2 - MFG and MSG - 0 degree
EO.EUM.DAT.METOP.AMSUL1 - AMSU-A Level 1B - Metop - Global
EO.EUM.DAT.METOP.ASCSZF1B - ASCAT Level 1 Sigma0 Full Resolution - Metop - Global
EO.EUM.DAT.METOP.ASCSZO1B - ASCAT Level 1 Sigma0 resampled at 25 km Swath Grid - Metop - Global
EO.EUM.DAT.METOP.ASCSZR1B - ASCAT Level 1 Sigma0 resampled at 12.5 km Swath Grid - Metop - Global
EO.EUM.DAT.METOP.AVHRRGACR02 - AVHRR GAC Atmospheric Motion Vectors Climate Data Record Release 2 - Multimission - Polar
EO.EUM.DAT.METOP.AVHRRL1 - AVHRR Level 1B - Metop - Global
EO.EUM.DAT.METOP.GLB-SST-NC - Global L3C AVHRR Sea Surface Temperature (GHRSST) - Metop
EO.EUM.DAT.METOP.GOMEL1 - GOME-2 Level 1B - Metop - Global
EO.EUM.DAT.METOP.GOMEL1R03 - GOME-2 Level 1B Fundamental Data Record Release 3 - Metop-A and -B
EO.EUM.DAT.METOP.IASIL1C-ALL - IASI Level 1C - All Spectral Samples - Metop - Global
EO.EUM.DAT.METOP.IASSND02 - IASI Combined Sounding Products - Metop
EO.EUM.DAT.METOP.IASTHR011 - IASI All Sky Temperature and Humidity Profiles - Climate Data Record Release 1.1 - Metop-A and -B
EO.EUM.DAT.METOP.LSA-002 - Daily Land Surface Temperature - Metop
EO.EUM.DAT.METOP.MHSL1 - MHS Level 1B - Metop - Global
EO.EUM.DAT.METOP.OSI-104 - ASCAT Coastal Winds at 12.5 km Swath Grid - Metop
EO.EUM.DAT.METOP.OSI-150-A - ASCAT L2 25 km Winds Data Record Release 1 - Metop
EO.EUM.DAT.METOP.OSI-150-B - ASCAT L2 12.5 km Winds Data Record Release 1 - Metop
EO.EUM.DAT.METOP.SOMO12 - ASCAT Soil Moisture at 12.5 km Swath Grid in NRT - Metop
EO.EUM.DAT.METOP.SOMO25 - ASCAT Soil Moisture at 25 km Swath Grid in NRT - Metop
EO.EUM.DAT.MFG.GSA-57 - GSA Level 2 Climate Data Record Release 2 - MFG - 57 degree
EO.EUM.DAT.MFG.GSA-63 - GSA Level 2 Climate Data Record Release 2 - MFG - 63 degree
EO.EUM.DAT.MSG.CLM - Cloud Mask - MSG - 0 degree
EO.EUM.DAT.MSG.CLM-IODC - Cloud Mask - MSG - Indian Ocean
EO.EUM.DAT.MSG.HRSEVIRI - High Rate SEVIRI Level 1.5 Image Data - MSG - 0 degree
EO.EUM.DAT.MSG.HRSEVIRI-IODC - High Rate SEVIRI Level 1.5 Image Data - MSG - Indian Ocean
EO.EUM.DAT.MSG.LSA-FRM - Fire Risk Map - Released Energy Based - MSG
EO.EUM.DAT.MSG.LSA-LST-CDR - Land Surface Temperature Climate Data Record - MSG
EO.EUM.DAT.MSG.LSA-LSTDE - Land Surface Temperature with Directional Effects - MSG
EO.EUM.DAT.MSG.MSG15-RSS - Rapid Scan High Rate SEVIRI Level 1.5 Image Data - MSG
EO.EUM.DAT.MSG.OCA-CDR - Optimal Cloud Analysis Climate Data Record Release 1 - MSG - 0 degree
EO.EUM.DAT.MSG.RSS-CLM - Rapid Scan Cloud Mask - MSG
EO.EUM.DAT.MTG.FCI-AMV-BUFR - Atmospheric Motion Vectors (BUFR) - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-AMV-NETCDF - Atmospheric Motion Vectors (netCDF) - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-ASR-BUFR - All Sky Radiance (BUFR) - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-ASR-NETCDF - All Sky Radiance (netCDF) - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-CLM - Cloud Mask - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-GII - Global Instability Indices - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-OCA - Optimal Cloud Analysis - MTG - 0 degree
EO.EUM.DAT.MTG.FCI-OLR - Outgoing LW radiation at TOA - MTG - 0 degree
EO.EUM.DAT.MTG.LI-AF - LI Accumulated Flashes - MTG - 0 degree
EO.EUM.DAT.MTG.LI-AFA - LI Accumulated Flash Area - MTG - 0 degree
EO.EUM.DAT.MTG.LI-AFR - LI Accumulated Flash Radiance - MTG - 0 degree
EO.EUM.DAT.MTG.LI-LEF - LI Lightning Events Filtered - MTG - 0 degree
EO.EUM.DAT.MTG.LI-LFL - LI Lightning Flashes - MTG - 0 degree
EO.EUM.DAT.MTG.LI-LGR - LI Lightning Groups - MTG - 0 degree
EO.EUM.DAT.MULT.HIRSL1 - HIRS Level 1B - Metop - Global
EO.EUM.DAT.MULT.HIRSL1C-FDR - HIRS Level 1C Fundamental Data Record Release 1 - Multimission - Global
EO.EUM.DAT.SENTINEL-3.AOD - SENTINEL3 SLSTR Level-2 AOD
EO.EUM.DAT.SENTINEL-3.FRP - SENTINEL3 SLSTR Level-2 FRP
EO.EUM.DAT.SENTINEL-3.OL_1_EFR___ - SENTINEL3 EFR
EO.EUM.DAT.SENTINEL-3.OL_1_ERR___ - SENTINEL3 ERR
EO.EUM.DAT.SENTINEL-3.OL_2_WFR___ - SENTINEL3 OLCI Level-2 Water Full Resolution
EO.EUM.DAT.SENTINEL-3.OL_2_WRR___ - SENTINEL3 OLCI Level-2 Water Reduced Resolution
EO.EUM.DAT.SENTINEL-3.SL_1_RBT___ - SENTINEL3 SLSTR Level-1
EO.EUM.DAT.SENTINEL-3.SL_2_WST___ - SENTINEL3 SLSTR Level-2 WST
EO.EUM.DAT.SENTINEL-3.SR_1_SRA_A_ - SENTINEL3 SRAL Level-1 SRA_A
EO.EUM.DAT.SENTINEL-3.SR_1_SRA_BS - SENTINEL3 SRAL Level-1 SRA_BS
EO.EUM.DAT.SENTINEL-3.SR_1_SRA___ - SENTINEL3 SRAL Level-1
EO.EUM.DAT.SENTINEL-3.SR_2_WAT___ - SENTINEL3 SRAL Level-2 WAT
EO.EUM.DAT.SENTINEL-6.L1B-RADIO_OCCULTATION - Radio Occultation Level 1B Products - Sentinel-6
EO.GSW.DAT.CHANGE - Global Surface Water Occurrence Change Intensity 1984-2020
EO.GSW.DAT.EXTENT - Global Surface Water Maximum Water Extent 1984-2021
EO.GSW.DAT.OCCURRENCE - Global Surface Water Occurrence 1984-2021
EO.GSW.DAT.RECURRENCE - Global Surface Water Recurrence 1984-2021
EO.GSW.DAT.SEASONALITY - Global Surface Water Seasonality 2014-2020
EO.GSW.DAT.TRANSITIONS - Global Surface Water Transitions 1984-2021
EO.ISIMIP.DAT.CLIMATE-FORCING_ISIMIP3b - ISIMIP3b climate input data
EO.ISIMIP.DAT.SOCIO-ECONOMIC-FORCING_ISIMIP3b - ISIMIP3b socio-economic input data
EO.MO.DAT.GLOBAL_ANALYSISFORECAST_BGC_001_028 - Global Ocean Biogeochemistry Analysis and Forecast
EO.MO.DAT.GLOBAL_ANALYSISFORECAST_PHY_001_024 - Global Ocean Physics Analysis and Forecast
EO.MO.DAT.GLOBAL_ANALYSISFORECAST_WAV_001_027 - Global Ocean Waves Analysis and Forecast
EO.MO.DAT.GLOBAL_MULTIYEAR_BGC_001_033 - Global ocean low and mid trophic levels biomass content hindcast
EO.MO.DAT.GLOBAL_MULTIYEAR_PHY_ENS_001_031 - Global Ocean Ensemble Physics Reanalysis
EO.MO.DAT.GLOBAL_MULTIYEAR_WAV_001_032 - Global Ocean Waves Reanalysis
EO.MO.DAT.INSITU_GLO_PHY_TS_OA_MY_013_052 - Global Ocean- Delayed Mode gridded CORA- In-situ Observations objective analysis in Delayed Mode
EO.MO.DAT.INSITU_GLO_PHY_TS_OA_NRT_013_002 - Global Ocean- Real time in-situ observations objective analysis
EO.MO.DAT.INSITU_GLO_PHY_UV_DISCRETE_NRT_013_048 - Global Ocean- in-situ Near real time observations of ocean currents
EO.MO.DAT.MULTIOBS_GLO_BGC_NUTRIENTS_CARBON_PROFILES_MYNRT_015_009 - Nutrient and carbon profiles vertical distribution
EO.MO.DAT.MULTIOBS_GLO_BIO_CARBON_SURFACE_MYNRT_015_008 - Global Ocean Surface Carbon
EO.MO.DAT.MULTIOBS_GLO_PHY_MYNRT_015_003 - Global Total (COPERNICUS-GLOBCURRENT), Ekman and Geostrophic currents at the Surface and 15m
EO.MO.DAT.MULTIOBS_GLO_PHY_S_SURFACE_MYNRT_015_013 - Multi Observation Global Ocean Sea Surface Salinity and Sea Surface Density
EO.MO.DAT.MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 - Multi Observation Global Ocean 3D Temperature Salinity Height Geostrophic Current and MLD
EO.MO.DAT.MULTIOBS_GLO_PHY_W_3D_REP_015_007 - Global Observed Ocean Physics 3D Quasi-Geostrophic Currents (OMEGA3D)
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L3_MY_009_103 - Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L3 (daily) from Satellite Observations (1997-ongoing)
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L3_MY_009_107 - Global Ocean Colour Plankton and Reflectances MY L3 daily observations
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L3_NRT_009_101 - Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L3 (daily) from Satellite Observations (Near Real Time)
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L4_MY_009_104 - Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L4 (monthly and interpolated) from Satellite Observations (1997-ongoing)
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L4_MY_009_108 - Global Ocean Colour Plankton MY L4 monthly observations
EO.MO.DAT.OCEANCOLOUR_GLO_BGC_L4_NRT_009_102 - Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L4 (monthly and interpolated) from Satellite Observations (Near Real Time)
EO.MO.DAT.SEAICE_GLO_SEAICE_L4_NRT_OBSERVATIONS_011_001 - Global Ocean - Arctic and Antarctic - Sea Ice Concentration, Edge, Type and Drift (OSI-SAF)
EO.MO.DAT.SEAICE_GLO_SEAICE_L4_NRT_OBSERVATIONS_011_006 - Global Ocean - High Resolution SAR Sea Ice Drift
EO.MO.DAT.SEAICE_GLO_SEAICE_L4_REP_OBSERVATIONS_011_009 - Global Ocean Sea Ice Concentration Time Series REPROCESSED (OSI-SAF)
EO.MO.DAT.SEALEVEL_GLO_PHY_L4_NRT_008_046 - GLOBAL OCEAN GRIDDED L4 SEA SURFACE HEIGHTS AND DERIVED VARIABLES NRT
EO.MO.DAT.SEALEVEL_GLO_PHY_MDT_008_063 - GLOBAL OCEAN MEAN DYNAMIC TOPOGRAPHY
EO.MO.DAT.SST_GLO_SST_L3S_NRT_OBSERVATIONS_010_010 - ODYSSEA Global Ocean - Sea Surface Temperature Multi-sensor L3 Observations
EO.MO.DAT.SST_GLO_SST_L4_NRT_OBSERVATIONS_010_001 - Global Ocean OSTIA Sea Surface Temperature and Sea Ice Analysis
EO.MO.DAT.SST_GLO_SST_L4_REP_OBSERVATIONS_010_011 - Global Ocean OSTIA Sea Surface Temperature and Sea Ice Reprocessed
EO.MO.DAT.SST_GLO_SST_L4_REP_OBSERVATIONS_010_024 - ESA SST CCI and C3S reprocessed sea surface temperature analyses
EO.MO.DAT.WAVE_GLO_PHY_SPC_FWK_L3_NRT_014_002 - Global Ocean L3 Spectral Parameters From NRT Satellite Measurements
EO.MO.DAT.WAVE_GLO_PHY_SWH_L3_NRT_014_001 - GLOBAL OCEAN L3 SIGNIFICANT WAVE HEIGHT FROM NRT SATELLITE MEASUREMENTS
EO.MO.DAT.WAVE_GLO_PHY_SWH_L4_NRT_014_003 - GLOBAL OCEAN L4 SIGNIFICANT WAVE HEIGHT FROM NRT SATELLITE MEASUREMENTS
EO.MO.DAT.WIND_GLO_PHY_CLIMATE_L4_MY_012_003 - Global Ocean Monthly Mean Sea Surface Wind and Stress from Scatterometer and Model
EO.MO.DAT.WIND_GLO_PHY_L3_MY_012_005 - Global Ocean Daily Gridded Reprocessed L3 Sea Surface Winds from Scatterometer
EO.MO.DAT.WIND_GLO_PHY_L3_NRT_012_002 - Global Ocean Daily Gridded Sea Surface Winds from Scatterometer
EO.MO.DAT.WIND_GLO_PHY_L4_MY_012_006 - Global Ocean Hourly Reprocessed Sea Surface Wind and Stress from Scatterometer and Model
EO.MO.DAT.WIND_GLO_PHY_L4_NRT_012_004 - Global Ocean Hourly Sea Surface Wind and Stress from Scatterometer and Model
EO.NASA.DAT.LANDSAT.C2_L1 - Landsat Collection 2 Level-1 Product
EO.NASA.DAT.LANDSAT.C2_L2 - Landsat OLI and TIRS Collection 2 Level-2 Science Products 30-meter multispectral data.
MO_MULTIOBS_GLO_BIO_BGC_3D_REP_015_010 - Global Ocean 3D Chlorophyll-a concentration, Particulate Backscattering coefficient and Particulate Organic Carbon
STAT.EUSTAT.DAT.AVAILABLE_BEDS_HOSPITALS_NUTS2 - Available beds in hospitals by NUTS 2 region
STAT.EUSTAT.DAT.BATHING_SITES_WATER_QUALITY - Bathing sites with excellent water quality by location
STAT.EUSTAT.DAT.GREENHOUSE_GAS_EMISSION_AGRICULTURE - Eurostat - Greenhouse gas emissions from agriculture
STAT.EUSTAT.DAT.POP_AGE_GROUP_SEX_NUTS3 - Population on 1 January by age, sex and NUTS 3 region
STAT.EUSTAT.DAT.POP_AGE_SEX_NUTS2 - Population on 1 January by age, sex and NUTS 2 region
STAT.EUSTAT.DAT.POP_CHANGE_DEMO_BALANCE_CRUDE_RATES_NUTS3 - Population change - Demographic balance and crude rates at regional level (NUTS 3)
STAT.EUSTAT.DAT.POP_DENSITY_NUTS3 - Population density by NUTS 3 region
STAT.EUSTAT.DAT.SHARE_ENERGY_FROM_RENEWABLE - Share of energy from renewable sources
STAT.EUSTAT.DAT.SOIL_SEALING_INDEX - Soil sealing index
STAT.EUSTAT.DAT.SURFACE_TERRESTRIAL_PROTECTED_AREAS - Surface of the terrestrial protected areas
Search¶
To search we use the search method passing the ID of our dataset of interest and a geo-time filter.
The search method returns a SearchResult object that stores the products obtained from a given page (default: page=1) and a given maximum number of items per page (default: items_per_page=20).
In the following cell, we change the default value of items_per_page and define the search criteria to retrieve Sentinel-2 MSI Level-2 images over Sicily, first days of July 2024. Our goal is to check whether any effects of Mount Etna’s eruptions during that period are visible in the Sentinel-2 imagery.
search_criteria = {
"provider":"dedl",
"productType": "EO.ESA.DAT.SENTINEL-2.MSI.L2A",
"start": "2024-07-04T07:00:00.00Z",
"end": "2024-07-08T07:00:00.00Z",
"geom": {"lonmin": 12, "latmin": 37, "lonmax": 16, "latmax": 39},
"count": True,
"items_per_page": 50
}products_first_page = dag.search(**search_criteria)Results are stored in a ‘SearchResult’ object that contains the details on the single search result.
products_first_pageLoading...
It is possible to list the metadata associated with a certain product, we choose the first one returned [0], and look into it.
one_product = products_first_page[0]
one_product.properties.keys()dict_keys(['alias', 'abstract', 'instrument', 'platform', 'platformSerialIdentifier', 'processingLevel', 'keywords', 'sensorType', 'license', 'title', 'missionStartDate', '_id', 'productType', 'publicationDate', 'orbitNumber', 'cloudCover', 'modificationDate', 'sensorMode', 'startTimeFromAscendingNode', 'completionTimeFromAscendingNode', 'id', 'downloadLink', 'thumbnail', 'storageStatus', 'defaultGeometry', 'quicklook', 'providers', 'start_datetime', 'sat:absolute_orbit', 'sar:product_type', 'dedl:processorVersion', 'dedl:sourceProductOriginDate', 'dedl:uid', 'dedl:datastripId', 'dedl:beginningDateTime', 'dedl:sourceProduct', 'dedl:productGroupId', 'dedl:endingDateTime', 'dedl:origin', 'dedl:scope', 'dedl:granuleIdentifier', 'dedl:tileIdentifier'])one_product.properties['cloudCover']0.000265Filter¶
EODAG can filter the search result. We can then refine our initial search without asking the provider again. Products can be filtered according to their properties or also with finer geometry filters.
The following example shows how to filter products to keep only those whose cloud coverage is less than 20%. And then restrict the results to products containing a smaller area over the mount Etna.
Let’s define now a smaller area around the mount Etna and a function to see the area on a map together with the results
from eodag.crunch import FilterProperty
from eodag.crunch import FilterOverlap
import shapely
import folium
from shapely.geometry import Polygon
small_geom = Polygon([[15.1, 37.7], [15.5, 37.7], [15.1, 37.75], [15.1, 37.75], [15.1, 37.7]])
smaller_area = {"lonmin": 15.1, "latmin": 37.7, "lonmax": 15.5, "latmax": 37.75}
search_geometry = shapely.geometry.box(
smaller_area["lonmin"],
smaller_area["latmin"],
smaller_area["lonmax"],
smaller_area["latmax"],
)
def create_search_result_map(search_results, extent):
"""Small utility to create an interactive map with folium
that displays an extent in red and EO Producs in blue"""
fmap = folium.Map([38, 14], zoom_start=7)
folium.GeoJson(
extent,
style_function=lambda x: dict(color="red")
).add_to(fmap)
folium.GeoJson(
search_results
).add_to(fmap)
return fmap# Crunch the results
filtered_results = products_first_page.crunch(FilterProperty({"cloudCover": 20, "operator" : "lt"}))
print(f"Got now {len(filtered_results)} products after filtering by cloudCover.")Got now 22 products after filtering by cloudCover.
filtered_products = filtered_results.crunch(
FilterOverlap(dict(contains=True)),
geometry=small_geom
)
print(f"Got now {len(filtered_products)} products after filtering by geometry.")Got now 1 products after filtering by geometry.
Let’s use the function defined to see the area defined on a map (red) together with the initial results (blue) filtered by cloud coverage and geometry (green).
fmap = create_search_result_map(products_first_page, search_geometry)
# Create a layer that represents the filtered products in green
folium.GeoJson(
filtered_products,
style_function=lambda x: dict(color="green")
).add_to(fmap)
fmap
Loading...
Download¶
Before downloading any product, it can be useful to have a quick look at them.
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
quicklooks_dir = os.path.join(workspace, "quicklooks")
if not os.path.isdir(quicklooks_dir):
os.mkdir(quicklooks_dir)
fig = plt.figure(figsize=(20, 40))
for i, product in enumerate(filtered_products, start=1):
# This line takes care of downloading the quicklook
quicklook_path = product.get_quicklook()
img = mpimg.imread(quicklook_path)
ax = fig.add_subplot(8, 2, i)
ax.set_title(product.properties['dedl:beginningDateTime'] + "TILE: " +product.properties['dedl:tileIdentifier'])
plt.imshow(img)
plt.tight_layout()
The quicklook shows effectively the ash plume caused by the eruptions.
EOProducts can be downloaded individually. The last image is going to be downloaded.
product_to_download = filtered_products[-1]
product_path = dag.download(product_to_download)
product_path'/home/jovyan/dev-branch/DestinE-DataLake-Lab/HDA/EODAG/eodag_workspace/S2A_MSIL2A_20240707T094041_N0510_R036_T33SWB_20240707T131659'The location property of this product now points to a local path.
product_to_download.location'file:///home/jovyan/dev-branch/DestinE-DataLake-Lab/HDA/EODAG/eodag_workspace/S2A_MSIL2A_20240707T094041_N0510_R036_T33SWB_20240707T131659'