- All Categories
- Data
- News
- Missions
- Events
- Tools
- Activities
- Instruments
- Campaigns
- Documents
Event - Conference
Dragon 3 2014 Symposium
The Dragon 3 2014 Symposium was part of the Dragon 3 Programme, focussed on exploitation of ESA, ESA's Third Party Missions and Chinese Earth observation data for geo-science and applications development in land, ocean and atmospheric applications.
Event - Conference
Dragon 3 2015 Symposium
The Dragon 3 2015 Symposium was part of the Dragon 3 Programme, focussed on exploitation of ESA, ESA's Third Party Missions and Chinese Earth observation data for geo-science and applications development in land, ocean and atmospheric applications.
Event - Conference
Dragon 3 2016 Symposium
The Dragon 3 2016 Symposium served as the close of the Dragon 3 Cooperation Programme (2012 to 2016) and formal kick off for Dragon 4 Cooperation projects.
Activity - Projects
Dragon 3 Cooperation Programme
The Dragon 3 Programme focussed on the exploitation of ESA, ESA's Third Party Missions and Chinese Earth observation data for geo-science and applications development in land, ocean and atmospheric applications.
News - Thematic area articles
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
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
ERS' Contribution to Altimetry
Satellite radar altimetry missions have transformed the way we see Earth and its oceans. Using the ranging capability of radars, they measure the surface topography profile along a satellite’s track.
News - Data Release news
New reprocessing of datasets celebrates 30 years of ERS
The ERS programme celebrated its 30th anniversary on 17 July. Today, we are still exploiting ERS data and experts continue to work on improving the altimeter, radiometer and SAR data the programme acquired.
News - Success Stories
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
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
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 - Product Specifications
wind-scatterometer-processing-requirements-from-sigma-nought-triplets-to-dealiased-wind.pdf
This document defines the ground processing algorithms for the ERS-1 AMI wind mode (Scatterometer) from the sigma nought triplets to the wind speed and direction, including the wind retrieval and the ambiguity removal processing.
Document - Publication - Paper
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.
Instrument - Scatterometers
SAR (ERS)
The Synthetic Aperture Radar (SAR) instrument aboard ERS-1 and ERS-2 was capable of high precision change detection of surface heights.
Instrument - Scatterometers
WS
The Wind Scatterometer (WS) instrument, on board the ERS-1 and ERS-2 missions, obtained information on wind speed and direction over the sea surface.
Tools - Visualisation
EVDC Orbit Prediction Tool
The EVDC Orbit Prediction and Overpass Tool generates and visualises satellite's overpasses.
Data - Data Description
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 - Data Description
ERS-1/2 SCATTEROMETER Ocean Wind field and Sea Ice probability [ASPS20.H/ASPS20.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.
