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  • All Categories (550)
  • Data (3)
  • News (4)
  • Missions (1)
  • Events (4)
  • Tools (2)
  • Activities (2)
  • Campaigns (4)
  • Documents (530)
  • News - Success Stories

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    Trailblazing ERS-2 mission enables climate change applications

    As ESA’s ERS-2 satellite approaches Earth’s atmosphere for reentry, it’s time to reflect on the mission’s great achievements in powering climate-related applications.

  • Data - Campaigns (Open)

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    AfriScat

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

  • News - Thematic area articles

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    Transforming space data into climate action

    ESA’s Earth observation activities are playing a key role in the revitalised global drive to combat climate change.

  • Activity - Projects

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    Dragon 2 Cooperation Programme

    The Dragon 2 Programme focussed on the exploitation of ESA, ESA's Third Party Missions and Chinese Earth observation data for science and applications development in land, ocean and atmospheric applications.

  • News - Success Stories

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    ERS Heritage Data allow for 30 years of science

    At their time of launch thirty years ago, the two ERS satellites were the most sophisticated Earth observation spacecraft ever developed and launched by Europe.

  • Tools - Apps

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    Heritage Missions app for iOS

    Download the Heritage Missions application to discover what the missions were about, how it worked and what the elements of the space and ground segment that make these missions unique.

  • Tools - Apps

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    Heritage Missions app for Android

    Download the Heritage Missions application to discover what the missions were about, how it worked and what the elements of the space and ground segment that make these missions unique.

  • Document - Publication - Paper

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    Calibration strategy for ERS scatterometer data reprocessing.pdf

    Paper included in the Proceedings of SPIE Remote Sensing of the Ocean and Sea Ice 2005 - vol.5977- Brugge (Belgium): Calibration strategy for ERS scatterometer data reprocessing. WS Cal/Val.

  • Document - Product Cal/Val Plan/Report

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    ECMWF Report on ERS-2 scatterometer - cycle 74

  • Document - Product Cal/Val Plan/Report

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    ECMWF Report on ERS-2 scatterometer - cycle 53

  • Data - Fast Registration with immediate access (Open)

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    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 - External Data (Restrained)

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    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.

  • Mission - Heritage Missions

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    ERS

    The ERS programme was composed of two missions, ERS-1 and ERS-2, which together observed the Earth for 20 years, from 1991 to 2011.

  • Campaign

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    TropiScat

    The major objectives of the experiment were the temporal survey of the variation of the measurements in time scales ranging from diurnal, weekly, monthly, up to 12 months of observation.

  • Campaign

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    ROVE (1975-1981)

    The Dutch research team ROVE (Radar Observation on Vegetation), funded by the remote sensing organization NIWARS, started in 1974 to investigate the scattering of microwaves by crops and soils, in order to help interpretation of radar imagery.

  • Campaign

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    AfriScat

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

  • Activity - Quality

    SCIRoCCo

    The SCIRoCCo project is an interdisciplinary cooperation of scatterometry experts aimed at promoting the continuing exploitation of ESA's unique 20 years' worth of ERS Scatterometer data.

  • Document - Publication - Paper

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    The ERS Wind Scatterometer performances

  • Document - Publication - Paper

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    Stability of Amazon Backscatter at C-band- ERS1-2 and RADARSAT-1

    Stability of Amazon Backscatter at C-band: Spaceborne Results from ERS-1/2 and RADARSAT-1