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INSTRUMENTS

Explore the many instruments the European Space Agency use to observe the Earth. ESA offer data from a wide range of optical, radar, atmospheric, altimetric and gravimetric instrumentation.

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  • Instrument - Scatterometers

    Instrument - Scatterometers

    WS Quality Control Reports

    Quality Control Reports Products Availability The ERS Scatterometer mission has been reprocessed with the Advanced Scatterometer Processing System (ASPS) facility, providing data with improved radiometric quality and spatial resolution. ERS-2 AMI Wind Scatterometer data set has been reprocessed covering the period from 30 December 1996 to 5 July 2011 (end of mission). Read More Cyclic Reports The cyclic reports include a summary of the daily quality control made within the IDEAS (Instrument Data quality Evaluation and Analysis Service) and various sections describing the results of the investigations related to the Scatterometer. In each section, results are shown from the beginning of the mission in order to see the evolution and to outline possible "seasonal" effects. An explanation for the major events which have impacted the performance since launch is given, and comments about the events which occurred during the cycle are included. Read More ERS-2 Yaw Error Angle Monitoring - Weekly Reportsy The full set of results of the yaw processing is stored in an internal ESA product named HEY (Helpful ESA Yaw). The estimation of the yaw error angle is based on the Doppler shift measured on the received echo (first three plots for the Fore, Mid and Aft antenna) and aims to compute the correct acquisition geometry for the three Scatterometer antenna throughout the entire orbit. The Yaw error angle information is also used in the radar equation to derive the calibrated backscattering from the Earth surface and to select the echo samples associated to each node in the spatial filter. Read More Cyclone Archive The activities of cyclone tracking were interrupted at the end of September 2001. The data used for these cyclone tracking activities are ERS-2 Fast Delivery scatterometer data. Read More Telemetry Data This section provides information related to the acquisition of the instrument telemetry data. The data includes instrument working modes, temperatures, currents and voltages of the transmitter and calibration chain, and finally the antenna temperatures. Read More

  • Instrument - Scatterometers

    Instrument - Scatterometers

    WS Processor Releases

    The current processor software version for the operational ground segment is ASPS v 10

  • Instrument - Scatterometers

    Instrument - Scatterometers

    WS Cal/Val

    ERS-2 Scatterometer: Mission Performances and Current Reprocessing Achievements Calibration strategy for ERS scatterometer data reproce...

  • Instrument - Imaging Radars, Scatterometers

    Instrument - Imaging Radars, Scatterometers

    SAR (ERS) Processor Releases

    Processor Releases It should be noted that for SAR, each product ordered is processed directly from the raw data, using the current vers...

  • Instrument - Imaging Radars, Scatterometers

    Instrument - Imaging Radars, Scatterometers

    SAR (ERS) Overview

    Scientists are studying the radar backscatter from the ocean surface related to wind and current fronts, to eddies and to internal wave...

  • Instrument - Imaging Radars, Scatterometers

    Instrument - Imaging Radars, Scatterometers

    SAR (ERS) Interferometry

    ERS SAR Interferometry The basic idea of interferometry is that the height of a point on Earth's surface can be reconstructed from the phase difference between two signals arriving at two antenna. This is because the phase difference is directly related to the difference in path lengths traversed by the signal between the point on the Earth surface and the two antennae. If the positions of the antennae are known accurately then the path difference can be used to infer the position of the target point on Earth's surface. The basic requirements for a repeat pass interferometric system (such as the use of ERS-1 or tandem ERS-1 / ERS-2) can be stated as: stable terrain backscatter (i.e. slowly changing) similar atmospheric conditions during acquisitions stable viewing geometry preservation of inherent phase information within the SAR processor Unfortunately, in practice, the accurate determination of the terrain height over the InSAR dataset is difficult. This is due to a number of reasons which arise at different points in the generation, processing and application of interferograms and result in one or more of the criteria listed above not being met. In order to categorise these effects it is necessary to know precisely how InSAR can be used to generate height information and to what uses this information can be put. There are four stages to the reconstruction of height information from the raw images: Coregistration of the complex SAR images: as the second image is acquired from a different viewing point to the first reference image, the data in the second image must be resampled so that the second image can be projected on to the first image Interferogram formation: this is calculated by multiplying the second image by the complex conjugate of the first image. The fact that the image data retains both amplitude and phase information means that the file size is somewhat larger than the more familiar intensity images. The interferogram is a method for illustrating the variation of phase difference over the image although there is an ambiguity of ñ2Np where N is an integer. Interferogramme are conventionally visualised using a Red- Green-Blue composite image where different information is assigned to each of the channels. One typical scheme is to assign the red channel to the coherence estimate (which can be calculated using a variety of methods), the green channel to the phase difference between pixels in the two images and the blue channel to the average intensity. Phase unwrapping: The problem of adding the correct number of multiples of 2p to the interferogramme in order to extract height information is referred to as phase unwrapping. There are a number of methods for attempting this stage of the processing including: the Goldstein branch cut method the fringe detection method of Lin et al knowledge injection DEM construction At each processing stage, there are various problems that must be overcome. Some of the problems are outlined below: Noise: the major sources of noise lead to problems mainly in the coregistration of the images and the phase unwrapping. Noise values lead to a loss of coherence and a degradation of the observed fringes. Atmospheric effects: local variations in atmospheric properties lead to differences in the path lengths between the two antenna positions and the target area giving rise to spurious phase variations which are superimposed on to the phase variations generated by the target area. Environmental effects: effects such as layover lead to discontinuities in the phase variations. In addition changes in environmental conditions (eg wind direction) alter the backscattering properties of the target areas between successive acquisitions leading to loss of coherence and subsequent difficulties in the production of the interferograms. In addition to the effects outlined above which give rise to degradation effects in the images and interferograms, there are several parameters which must be optimised for useful InSAR data acquisition. These include the time between acquisitions and the interferometric baseline: Temporal decorrelation: excessive time periods between successive acquisitions of SAR scenes can result in a reduction of coherence preventing the generation of interferograms due to a temporal variation in backscattering properties of the target area. The time scales vary depending on the nature of the target (e.g. for a glacier during the summer period when excessive melting may occur, successive scenes acquired one day apart may not exhibit sufficient coherence to generate interferograms. In other cases, acquisitions several years apart may allow the generation of high quality fringes. Baseline limitations: above a critical length of baseline (approximately 1100 m for ERS-1) there is a complete loss of coherence. The degree of this coherence significantly influences the accuracy of the phase and hence the height measurement. In practice, there are limitations on length of baseline for which useful interferograms can be calculated. For mapping, the optimal baseline length is between 50 m and 300 m. Shorter baselines can yield useful information regarding glacier properties but tend not to yield useful datasets for height estimation. The upper practical limit is around 600 m. The availability of satellite borne SAR data has allowed InSAR to develop at a considerable rate. Applications of InSAR InSAR techniques can provide useful information within many application fields. Depending on various factors (eg the area under study, the time between repeat acquisitions, the time of year etc) it is possible to extract very different categories of information. Some of the applications are mutually exclusive (ie when a dataset is suitable for one application it is unsuitable for another) whereas other applications can extract different signature information from the same dataset. This can cause additional problems as the signature of one type of phenomena contained within an interferogramme can be regarded as noise contaminating the signature of a different phenomenon. Examples are: DEM generation and land cover mapping: vegetation causes a strong temporal decorrelation between acquisition dates (due to changes in environmental conditions) preventing the extraction of reliable height information from the interferogramme and the subsequent construction of a DEM. On the other hand, vegetation can be categorised by the degree of decorrelation caused and thus enable the identification of different land cover types. Glacier movement and topographic mapping: separation of effects due to glacier movement induced decorrelation and topographic effects can be difficult but is a necessary step in the extraction of glacier information from the interferogrammes. In addition, components of the interferometric signal such as anomalous signal path lengths introduced by atmospheric effects are currently treated as pure noise. This is because there are currently no applications exploiting such information. At the present time there are five major applications of InSAR. These are: DEM generation: this involves the reconstruction of terrain heights from the unwrapped phase information derived from the InSAR dataset and has numerous applications including mobile telecommunications network planning, exploration geology and urban planning. An additional application is in the improved terrain correction of SAR imagery for applications in remote areas where cartographic data are out of date or unavailable. Land use classification and forest monitoring. Forest canopy height information can be extracted in suitable terrain if the coherence is sufficiently high. Different crop types can be identified based on their effects on the spatial variation of coherence within the InSAR dataset. In general, forested areas exhibit low levels of coherence (due to changes in wind conditions between acquisitions) allowing the identification f forest cover from other land cover classes. Geophysical hazard analysis (earthquakes, volcanoes, landslides and subsidence), prediction and quantification There are three principle application areas in geophysical hazard analysis: measurement of dislocation extent at the source of an earthquake measurement of small height variations due to the filling and drainage of magma chambers under volcanoes monitoring of subsidence resulting from extraction activities such as coal mining Each of these applications require a more advanced technique known as Differential Interferometry, in which very small land surface movements can be detected. The idea is to use an existing DEM or a stable (no movement) interferogramme to remove topographic effects by subtracting the terrain generated fringes from an interferogram. The resulting fringes are due to smaller motion effects. Differential Interferometry allows the measurement of movements on the scale of millimetres. Glacier motion measurement: InSAR data are used for the measurement of glacier motions and topography changes. This is important information for assessing glacier mass transport rates and changes in glacier volume which is, in turn, essential for the validation and improvement of hydrological models. In addition, such information may have significant implications for global climate change assessment. Hydrological modelling: there are two aspects to the use of InSAR data in hydrological applications: determination of ground cover and run off paths in arid regions in order to optimise run-off interception structures measurement of ground motion associated with the filling and drainage of underground reservoirs In addition to the five applications described above, there are several application areas which are currently the focus of attention regarding future applications of InSAR. These include: coastal zone and inter-tidal zone monitoring snow melt measurement These last two applications are at a less advanced stage due to particular difficulties in extracting the signal of interest from decorrelations arising due to variations in surface moisture levels. InSAR and the ERS Tandem operations The orbit maintenance and measurement strategy was such that the ERS platforms were unique in their capability to be exploited for the generation of interferometric SAR data sets. However, the ERS orbit configuration, designed before interferometry was considered as an operational technique, was not ideally suited to the production of interferometric datasets. In particular, the repeat cycle of 35 days for the major part of the ERS lifetime means that the level of coherence between successive SAR acquisitions was, in many cases, insufficient to allow the generation of interferograms. The launch of ERS-2 however, changed the situation drastically. With the potential to simultaneously operate two platforms in tandem, the time between acquisitions was reduced to ensure an adequate coherence between successive SAR scenes while maintaining each platform in an orbit configuration that ensures a maximum possible coverage of Earth's surface. The ERS Tandem Mission objectives were primarily focussed on the collection of SAR data pairs for exploitation in interferometry together with the synergistic use of instruments on the two platforms. ERS-1/ERS-2 SAR pairs with an offset of one day were acquired covering large parts of the global land surfaces. Close and efficient cooperation among all the ERS ground-segment entities enabled the collection of this unique data set which offered a chance to scientists and operational organisations to derive medium to high resolution DEMs for a variety of applications. The Tandem objectives were met by accurately adjusting the orbital positions of the two satellites. During ERS-2 Commissioning Phase and the Tandem Operations Phase the two satellites were maintained in the same orbital plane, ERS-2 following ERS-1 30 minutes later. This means that the same swath on ground was acquired by ERS-2 one day after ERS-1. In coordination with the global network of national and international receiving stations, a background acquisition plan was set up matching within the constraints of satellite resources the availability period of the station with specific orbit maintenance procedures. For example in the Polar Campaign period, the orbit was maintained to meet baseline requirements (cross track separation of 70-170 metres) at latitudes above 60° while orbit cross over points were at equatorial latitudes. During this period maximum acquisition was scheduled over the stations of O'Higgins, McMurdo, Syowa, Alaska, Prince Albert and Kiruna. In contrast, full coverages of South America (Cuiaba) were acquired in April/May, when the orbit maintenance was focused on meeting a 50-200 metres cross track separation at the equator. Loss of SAR tandem coverage due to late availability of certain receiving stations and conflicts caused by the completion of the ERS-2 WSC commissioning activities during the Tandem Phase could be compensated for by extremely precise orbit maintenance, The high frequency of in-plane manoeuvres especially towards the end of the tandem mission ensured that nearly every acquired data pair met the stringent specifications in terms of cross-track separation. In order to further strengthen the exploitation of the ERS Tandem Mission, an Announcement of Opportunity dedicated to the scientific exploitation of the data collected resulted in some 60 projects focussing on ERS InSAR techniques and complementary use of ERS-1 and ERS-2 instruments. Tandem acquisition status After nine months of operating the ERS-1 and ERS-2 spacecraft in tandem together with the ERS-2 commissioning phase, the objectives of the ERS Tandem Mission were successfully completed. The table below shows the acquisition status. Baseline range Number of frames pairs % of total Bperp < 50 m 22181 20 50 m < Bperp < 300 m 81619 73 30 0m < Bperp < 600 m 6221 6 600 m < Bperp 1028 1 Tandem acquisition statistics The data acquired during the Tandem phase with values of Bperp between 50 m and 300 m are of particular interest for InSAR applications. These are shown in greater detail in the table below. Baseline range Number of frames pairs % of total 50m < Bperp < 130 m 45681 41 130 m < Bperp < 215 m 26637 24 215 m < Bperp < 300 m 9301 8 Tandem acquisitions with baseline values between 50 m and 300 m Images A number of observations can be made regarding the Tandem acquisition status: The majority of land areas are covered. In particular (apart from Siberia) latitudes above 60º N and S are covered by at least one acquisition. For large areas of Antarctica, only one acquisition pair is available. The overlap between neighbouring tracks however, assures three acquisitions for all areas south of 63° which includes the entire Antarctic continent. For Greenland, there are two to three acquisitions over most areas of the island. The area north of 70° has three full coverages due to partial overlap between neighbouring tracks. In addition to the pairs of SAR scenes acquired for baseline values between 50 m and 300 m, a number of tandem acquisitions have also been made for baselines less than 50 m. While a separation of less than 50 m is normally too small for mapping purposes, it can allow the separation of glacier movement effects and static topographic effects within interferogrammes generated over Arctic and Antarctic regions. Acquisitions for which the baseline is less than 50 m are illustrated both in a mercator projection and a polar projection. Again, the colour coding is explained within each image caption. Available Resources Radar Interferometry Applications and Case Studies ERS-1 and ERS-2 Interferometry Baseline Listing ERS-1/2 earth coverage in tandem mode filtered by baseline (1995-1997)

  • Instrument - Imaging Radars, Scatterometers

    Instrument - Imaging Radars, Scatterometers

    SAR (ERS)

    Processor Releases It should be noted that for SAR, each product ordered is processed directly from the raw data, using the current ver...

  • Instrument - Spectrometers/Radiometers

    Instrument - Spectrometers/Radiometers

    GOME Products Information

    GOME Products This information is applicable to the GOME products available to users through the ESA GOME Online Dissemination System. In particular, the Level 2 version 5 dataset generated in 2012, and the data resulting from the GOME-Evolution project: Level 1 version 5.1 data and TCWV time-series. Level 1 version 5.1 dataset – released 2018 Level 2 GDP version 5.0 dataset – released 2012 TCWV Climate product – from Evolution project – released 2018 All GOME datasets span the period from June 1995 to July 2011. The GOME-Evolution TCWV Climate product covers the period from July 1995 to December 2015. Details on the datasets currently distributed are in the ERS-2 GOME Products availability Table GOME Level 1 version 5.1 The GOME Level 1 Data Processor (GDP) Version 5.1 was developed within the GOME Evolution and Outreach project (2014-2017) and was used to perform the first complete post-operational Level 0-to-1 full-mission reprocessing campaign with output products in NetCDF-4 format. The GOME Level 1b dataset version 5.1 provides fully calibrated Earthshine radiances, and it brings significant quality improvements with respect to the quality of the data for the revised calibration approach. Users of GOME Level 1 products are strongly recommended to migrate to this dataset. Note that no operational Level 2 processing was carried out from these data. GOME Level 1 version 5 Technical Documents: Algorithm Theoretical Baseline Document (ATBD) Product User Manual (PUM) Products Quality Readme File GOME Validation Report GOME Level 2 The GOME Level 2 Data Processor Version 5 (GDP 5 in short) was used to perform the latest post-operational Level 2 full mission reprocessing campaign, which was based on the old GOME Level 1 version 4 data. The Level 2 dataset (HDF-5 format) was released on 14 September 2012 and includes total column densities of ozone and nitrogen dioxide, and cloud parameters. GOME Level 2 version 5 Technical Documents: Products Quality Readme File Algorithm Theoretical Baseline Description (ATBD) Product User Manual GOME GDP 5 Validation Report Additional information can be found on the DLR / ATMOS website. GOME TCWV Climate product The ESA GOME-Evolution Climate water vapour product presents homogenized time-series of the global distribution of water vapour total columns (TCWV) spanning over more than two decades and based on measurements from the satellite instruments GOME, SCIAMACHY, and MetOp-A GOME. Details are available in Beirle et al., 2018. GOME TCWV Climate product Technical Documents: ESSD paper by S. Beirle et al. 2018 GOME TCWV Products Quality Readme File Danielczok, A. and Schröder, M. - GOME Evolution Climate product validation report, version 2, 2017 Grossi, M. - GOME Evolution Climate Product - Comparison results: time series, 2017 GOME TCWV Advanced AMF Algorithm (A3) product In the framework of the ESA GOME-Evolution project, an additional improved water vapour total columns (TCWV) product was developed by the Max-Planck-Institute for Chemistry (Mainz, Germany) adopting the Advanced AMF (A³) Algorithm. Validation of the resulting products showed the consistency of the global H2O VCD distribution with existing datasets, but also clearly indicated a strong dependence on cloud properties. Acceptable results were only obtained for medium cloud conditions. As the new product has not reached the expected maturity and further investigations are required, the resulting dataset is currently not open to the users. GOME TCWV Advanced AMF Algorithm (A3) product Technical Documents: Algorithm Theoretical Baseline Description (ATBD)

  • Instrument - Spectrometers/Radiometers

    Instrument - Spectrometers/Radiometers

    GOME CAL/VAL

    dark current and LED measurements (pixel-to-pixel gain)