Technical aspects of Envisat-ASAR geocoding capability at DLR

Based on experience with the geocoding systems for ERS-D-PAF (GEOS), the SIR-C/X-SAR (GEOS) and SRTM missions (GeMoS), geocoding functionality has been extended for Envisat ASAR data. The existing Envisat ASAR Geocoding System (EGEO) can handle all Level 1-b image products (IMS, APS, IMP, APP, IMM, APM, WSM and GM1). Complementary to geocoded products provided by ESA (IMG, APG) the geocoding procedure applied at the German Aerospace Center (DLR) makes use of a DEM to achieve higher geolocation accuracy. The resulting geocoded image is either defined as EEC (Enhanced Ellipsoid Corrected) or as ETC (Enhanced Terrain Corrected). These products mainly differ in the underlying DEM used for geocoding. The EEC utilizes GLOBE, while the ETC utilizes the “best” DEM available in the data base. This “best” DEM can be assembled from different DEM data sets (e.g. derived from SRTM, ERS, …). Further differences such as the interpolative (EEC) and rigorous (ETC) geocoding approach will also be outlined. Furthermore, an incidence angle mask can be generated. The necessary upgrades for geocoding ASAR stripline products (e.g. IMM, WSM) will be presented. Stripline products cover a large area along track, as they consist of concatenated stand-alone products (“slices”). Thus the updates of relevant parameters have to be taken into account

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided

Mitigation of atmospheric perturbations and solid Earth movements in a TerraSAR-X time-series

The TerraSAR-X (TSX) synthetic aperture radar (SAR) marks the recent emergence of a new generation of spaceborne radar sensors that can for the first time lay claim to localization accuracies in the sub-meter range. The TSX platform's extremely high orbital stability and the sensor's hardware timing accuracy combine to enable direct measurements of atmospheric refraction and solid Earth movements. By modeling these effects for individual TSX acquisitions, absolute pixel geolocation accuracy on the order of several centimeters can be achieved without need for even a single tiepoint. A 16-month time series of images was obtained over a fixed test site, making it possible to validate both an atmospheric refraction and a solid Earth tide model, while at the same time establishing the instrument's long-term stability. These related goals were achieved by placing trihedral corner reflectors (CRs) at the test site and estimating their phase centers with centimeter-level accuracy using differential GPS (DGPS). Oriented in pairs toward a given satellite track, the CRs could be seen as bright "points” in the images, providing a geometric reference set. SAR images from the high-resolution spotlight (HS) mode were obtained in alternating ascending and descending orbit configurations. The highest-resolution products were selected for their small sample dimensions, as positions can be more precisely determined. Based on the delivered product annotations, the CR image positions were predicted, and these predictions were compared with their measured image positions both before and after compensation for atmospheric refraction and systematic solid Earth deviations. It was possible to show that when the atmospheric distortion and Earth tides are taken into account, the TSX HS products have geolocation accuracies far exceeding the specified requirements. Furthermore, this accuracy was maintained for the duration of the 16-month test period. It could be demonstrated that with a correctly calibrated sensor, and after accounting for atmospheric and tidal effects, tiepoint-free geolocation is possible with TSX with an absolute product accuracy of about 5c

In-depth verification of Sentinel-1 and TerraSAR-X geolocation accuracy using the Australian Corner Reflector Array

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques—also called imaging geodesy—can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improve�ment of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy

Upgrade of foss date plug-in: Implementation of a new radargrammetric DSM generation capability

Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome "La Sapienza", and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery

The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions

International audienceIn 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30,000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1-hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community

Integration, Testing, And Analysis Of Multispectral Imager On Small Unmanned Aerial System For Skin Detection

Small Unmanned Aerial Systems (SUAS) have been utilized by the military, geological researchers, and first responders, to provide information about the environment in real time. Hyperspectral Imagery (HSI) provides high resolution data in the spatial and spectral dimension; all objects, including skin have unique spectral signatures. However, little research has been done to integrate HSI into SUAS due to their cost and form factor. Multispectral Imagery (MSI) has proven capable of dismount detection with several distinct wavelengths. This research proposes a spectral imaging system that can detect dismounts on SUAS. Also, factors that pertain to accurate dismount detection with an SUAS are explored. Dismount skin detection from an aerial platform also has an inherent difficulty compared to ground-based platforms. Computer vision registration, stereo camera calibration, and geolocation from autopilot telemetry are utilized to design a dismount detection platform with the Systems Engineering methodology. An average 5.112% difference in ROC AUC values that compared a line scan spectral imager to the prototype area scan imager was recorded. Results indicated that an SUAS-based Spectral Imagers are capable tools in dismount detection protocols. Deficiencies associated with the test expedient prototype are discussed and recommendations for further improvements are provided

New sensors benchmark report on Sentinel-2A

Geometric benchmarking for Sentinel-A2 sensor over Maussane test site for CAP purposesJRC.H.6-Digital Earth and Reference Dat