- All Categories (610)
- Data (10)
- News (4)
- Missions (1)
- Events (4)
- Tools (2)
- Activities (2)
- Campaigns (5)
- Documents (582)
News - Success Stories
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.
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 - 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 - 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.
Data - Fast Registration with immediate access (Open)
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 - EO Sign In Authentication (Open)
ERS-1/2 SAR IM Single Look Complex L1 [SAR_IMS_1P]
The SAR SLC product is a single look complex acquired in Image Mode. It is a digital image, with slant range and phase preserved, generated from raw SAR data using up-to-date auxiliary parameters. The products are intended for use in SAR quality assessment, calibration and interferometric applications. A minimum number of corrections and interpolations are performed on the data. Absolute calibration parameters (when available) are provided in the product annotation. Product characteristics: Pixel size: 8 m (range - across track) x 4 m (azimuth - along track – varying slightly depending on acquisition Pulse Repetition Frequency) Scene area: 100 km (range) x at least 102.5 km (azimuth) Scene size: 5000 samples (range) x at least 30000 lines (azimuth) Pixel depth: 32 bits signed integer (16 bits I, 16 bits Q) Total product volume: 575 MB Projection: Slant range- Number of looks: 1.
Data - Data Service Request (Restrained)
ERS-1/2 SAR IM L0 [SAR_IM__0P]
This SAR Level 0 product is acquired in Image Mode. The products consist of the SAR telemetry data and are supplied as standard scenes. It also contains all the required auxiliary data necessary for data processing. The product serves two main purposes: For testing ERS SAR processors independently from the HDDR system For users interested in full SAR data processing. Product characteristics: Scene area: 100 km (range - across track) x full segment length (azimuth - along track) Scene size: 5616 samples (range) x full segment length (azimuth) Pixel depth: 10 bits signed integer (5 bits I, 5 bits Q) Projection: Slant range.
Data - EO Sign In Authentication (Open)
ERS-1/2 SAR IM Precision L1 [SAR_IMP_1P]
The SAR Precision product is a multi-look (speckle-reduced), ground range image acquired in Image Mode. This product type is most applicable to users interested in remote sensing applications, but is also suitable for calibration purposes. The products are calibrated and corrected for the SAR antenna pattern and range-spreading loss. Radar backscatter can be derived from the products for geophysical modelling, but no correction is applied for terrain-induced radiometric effects. The images are not geocoded, and terrain distortion (foreshortening and layover) has not been removed. The numbering sequence relates to the satellite position and therefore differs between Ascending and Descending scenes. Product characteristics: Pixel size: 12.5 m (range - across track) x 12.5 m (azimuth - along track) Scene area: 100 km (range) x at least 102.5 km (azimuth) Scene size: 8000 pixels range x at least 8200 lines (azimuth) Pixel depth: 16 bits unsigned integer Total product volume: 125 MB Projection: Ground-range Number of looks: 3.
Data - EO Sign In Authentication (Open)
ERS-1/2 SAR IM Medium Resolution L1 [SAR_IMM_1P]
This ERS Medium Resolution stripline product is generated from the Image Mode Level 0 Product. Stripline image products contain image data for an entire segment, up to a maximum size of 10 minutes per product for IM mode. The processor concatenates together several sub-images called "slices" that were processed separately on a dataset-by-dataset basis in order to form the entire stripline image. The product is processed to an approximately 150 m x 150 m resolution and has a radiometric resolution that is good enough for ice applications. This product has a lower spatial resolution than the SAR_IMP_1P and SAR_IMS_1P products. Product Characteristics: Pixel size: 5 m (ground range – across track) x 75 m (azimuth – along track) Scene area: 100 km (range) x at least 102.5 km Scene Size: 1300 pixels (range) x at least 1350 lines (azimuth) Pixel depth: 16 bits unsigned integer- Total product volume: at least 3.5 MB Projection: Ground-range Number of looks: 8 (azimuth) x 7 (range).
Data - External Data (Restrained)
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
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.
Data - Campaigns (Open)
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)
AROMAT-II
This campaign covers the fields of atmospheric composition: NO2, SO2, aerosols, over Romania (Bucharest and Turceni) and Germany (Berlin).
Data - Campaigns (Open)
NoSREx-I -II and -III
The Nordic Snow Radar Experiment (NoSREx) took place between November 2009 and May 2010. The objective of the campaign was to provide a continuous time series of active and passive microwave observations of snow cover in a representative location.