earth online
  • All Categories (10298)
  • Data (11)
  • News (18)
  • Missions (3)
  • Events (21)
  • Tools (5)
  • Activities (7)
  • Campaigns (7)
  • Documents (10226)

DATA

Discover and download the Earth observation data you need from the broad catalogue of missions the European Space Agency operate and support.

  • Data - Announcement of Opportunity (Restrained)

    prompt photo

    Announcement of Opportunity for G-POD

    ESA is offering all scientists the possibility to perform bulk processing and/or validation of their own algorithms exploiting the large ESA Earth-observation archive.

  • Data - Fast Registration with immediate access (Open)

    prompt photo

    Envisat SCIAMACHY Geo-located atmospheric spectra [SCI_NL__1P]

    This data product covers geo-located, radiometrically and spectrally calibrated limb and nadir radiance spectra for Nadir, Limb, and Occultation measurements with additional monitoring and calibration measurements. The Level 1b product is the lowest level of SCIAMACHY data delivered to the users. The instrument Instantaneous Field of View (IFoV) is approximately 0.045 deg (scan direction) x 1.8 deg (flight direction). This corresponds to a ground pixel size of 25 km x 0.6 km at the sub-satellite point (nadir) and of 103 km x 2.6 km at the Earth's horizon (limb). Nadir measurements have a maximum swath width of 960 km (in scan direction) and a typical footprint of 30 km (along track) x 60 km (across track). Limb measurements have a tangent height range spanning from 0 to 100 km with 3 km vertical resolution. Azimuth scans are performed for constant elevation angle, typically 34 elevation steps per limb scan. Maximum azimuth range is +/- 44 deg relative to S/C velocity (Note that the azimuth range is adjusted to observe the same atmospheric volume as for nadir measurements within five minutes). The radiometric resolution is 16 bits, with a spectral resolution of 0.24 nm to 1.5 nm, depending on the spectral range. The Sun normalized radiometric accuracy is 2 to 3% in unpolarized light, and 3 to 4% in polarized light. The relative radiometric accuracy is less than 1% and the spectral accuracy spans form 0.005 nm to 0.035 nm. Individual measurements from dedicated monitoring states include: Sun over diffuser Subsolar calibration Spectral lamp measurements White light source measurements Elevation mirror monitoring (Sun/Moon) ADC calibration Level 1b products are corrected for degradation applying a scan mirror model and m-factors. The latest Level 1b dataset is version 8.0X.

  • Data - Fast Registration with immediate access (Open)

    prompt photo

    Envisat SCIAMACHY Total column densities and stratospheric profiles [SCI_OL__2P]

    The data product provides global column distributions and stratospheric profiles of various trace gases. Total column densities of O3, NO2, OClO, H2O, SO2, BrO, CO, HCHO, CHOCHO and CH4 are retrieved from Nadir measurements. Additional cloud parameters (fractional cloud coverage, cloud-top height, cloud optical thickness) and an aerosol absorption indicator are enclosed. Stratospheric profiles of O3, NO2, and BrO are derived from limb measurements and with flagging information for cloud-types. Tropospheric NO2 columns are retrieved combining limb and nadir measurements. The latest Level 2 dataset is Version 6.01.

  • Data - Fast Registration with immediate access (Open)

    prompt photo

    ERS-2 SCATTEROMETER Surface Soil Moisture Time Series and Orbit product in High and Nominal Resolution [SSM.H/N.TS - SSM.H/N]

    Surface soil moisture records are derived from the backscatter coefficient measured by the Scatterometer on-board the European Remote Sensing satellite (ERS-2) using the Technische Universität (TU) Wien soil moisture retrieval algorithm called WARP (WAter Retrieval Package). In the WARP algorithm, the relative surface soil moisture estimates, given in degree of saturation Sd, range between 0% and 100% are derived by scaling the normalized backscatter between the lowest/highest backscatter values corresponding to the driest/wettest soil conditions. Surface Soil Moisture - Time Series product: The products generated are the surface soil moisture time series, where for each grid point defined in a DGG (Discrete Global Grid) is stored the time series of soil moisture and its noise, the surface state flag, the geolocation and the satellite parameters. The spatial resolution of the products is about 25 km x 25 km (high resolution) or 50 km x 50 km (nominal resolution) geo-referenced on the WARP grid. The location of the points can be viewed interactively with the tool DGG Point Locator. Surface Soil Moisture - Orbit product: In addition to WARP, a second software package, referred to as WARP orbit, was developed in response to the strong demand of soil moisture estimates in satellite orbit geometry. The Level 2 soil moisture orbit product contains a series of Level 1 data information, such as the backscatter, the incidence angle and the azimuth angle for each triplet together with the surface soil moisture and its noise, normalized backscatter at 40° incidence angle, parameters useful for soil moisture, the geolocation and the satellite parameters. The soil moisture orbit product is available in two spatial resolutions with different spatial sampling distances: Spatial sampling on a regular 12.5 km grid in orbit geometry with a spatial resolution of about 25 km x 25 km (High resolution) Spatial sampling on a regular 25 km grid in orbit geometry with a spatial resolution of about 50 km x 50 km (Nominal resolution). The spatial resolution is defined by the Hamming window function, which is used for re-sample of raw backscatter measurements to the orbit grid in the Level-1 ground processor. Please consult the Product Quality Readme file before using the ERS-2 Surface Soil Moisture data.

  • Data - Fast Registration with immediate access (Open)

    prompt photo

    ERS-1/2 SCATTEROMETER Ocean Wind field and Sea Ice probability [ASPS20.H/ASPS20.N]

    The ASPS Level 2 products contain, for each node: the radar backscattering sigma nought for the three beams of the instrument, the four aliased wind solutions (Rank 1-4 wind vector) and the de-aliased wind vector flag, the sea-ice probability and sea-ice flag, the YAW quality flag. The wind retrieval is performed with the CMOD5N geophysical model function derived by ECMWF to compute the neutral winds rather than 10 m winds. ASPS L2.0 High resolution products are provided with a spatial resolution of 25x25 km and a grid spacing of 12.5 km. ASPS L2.0 Nominal resolution products are provided with a spatial resolution of 50x50 km and a grid spacing of 25 km. One product covers one orbit from ascending node crossing. Please consult the Product Quality Readme file before using the ERS ASPS data.

  • Data - Fast Registration with immediate access (Open)

    prompt photo

    ERS-1/2 SCATTEROMETER Nominal Resolution back-scattering measurements, Ocean Wind field [UWI]

    The ERS data reprocessed with the ASPS facility is also available in the UWI format to maintain the compatibility with the FD (Fast Delivery) products. The ASPS UWI product is organised in frames of 500 x 500 km providing the radar backscattering sigma nought for the three beams of the instrument plus the wind speed and direction. The wind retrieval is performed with the CMOD5N geophysical model function derived by ECMWF to compute the neutral winds rather than 10m winds. ASPS UWI products are provided with a spatial resolution of 50 x 50 km and a grid spacing of 25 km. One product covers one orbit from ascending node crossing. Please consult the Product Quality Readme file before using the ERS ASPS data.

  • Data - External Data (Restrained)

    prompt photo

    ADAM Surface Reflectance Database v4.0

    ADAM enables generating typical monthly variations of the global Earth surface reflectance at 0.1° spatial resolution (Plate Carree projection) and over the spectral range 240-4000 nm. The ADAM product is made of gridded monthly mean climatologies over land and ocean surfaces, and of a companion API toolkit that enables the calculation of hyperspectral (at 1 nm resolution over the whole 240-4000 nm spectral range) and multidirectional reflectances (i.e. in any illumination/viewing geometry) depending on user choices. The ADAM climatologies that feed the ADAM calculation tools are: For ocean: Monthly chlorophyll concentration derived from SeaWiFS-OrbView-2 (1999-2009); it is used to compute the water column reflectance (which shows large spectral variations in the visible, but is insignificant in the near and mid infrared). Monthly wind speed derived from SeaWinds-QuikSCAT-(1999-2009); it is used to calculate the ocean glint reflectance. For land: Monthly normalized surface reflectances in the 7 MODIS narrow spectral bands derived from FondsdeSol processing chain of MOD09A1 products (derived from Aqua and Terra observations), on which relies the modelling of the hyperspectral/multidirectional surface (soil/vegetation/snow) reflectance. Uncertainty variance-covariance matrix for the 7 spectral bands associated to the normalized surface reflectance. For sea-ice: Sea ice pixels (masked in the original MOD09A1 products) have been accounted for by a gap-filling approach relying on the spatial-temporal distribution of sea ice coverage provided by the CryoClim climatology for year 2005.

  • Data - Campaigns (Open)

    prompt photo

    AirScatterGNSS

    In this project an Airborne Wind Vector Scatterometer (AWVS) system was designed and built for measurements of sea surface backscattering from an aircraft.

  • Data - Campaigns (Open)

    prompt photo

    AfriScat

    AfriScat campaign, a follow on to TropiSCAT campaign, was to acquire long-term P-Band radar data in an African tropical forest.

  • Data - Campaigns (Open)

    prompt photo

    AROMAT-II

    This campaign covers the fields of atmospheric composition: NO2, SO2, aerosols, over Romania (Bucharest and Turceni) and Germany (Berlin).

  • Data - Campaigns (Open)

    prompt photo

    AROMAT-I

    The main objective of this AROMAT-I campaign was to test newly developed airborne sensors and to evaluate their capabilities as validation tools for future air quality space borne sensors, in particular TROPOMI.