Simulating SAR geometric distortions and predicting Persistent Scatterer densities for ERS-1/2 and ENVISAT C-band SAR and InSAR applications: nationwide feasibility assessment to monitor the landmass of Great Britain with SAR imagery

We assess the feasibility of monitoring the landmass of Great Britain with satellite Synthetic Aperture Radar (SAR) imagery, by analysing ERS-1/2 SAR and ENVISAT IS2 Advanced SAR (ASAR) archive data availability, geometric distortions and land cover control on the success of (non-)interferometric analyses. Our assessment both addresses the scientific and operational question of whether a nationwide SAR-based monitoring of ground motion would succeed in Great Britain, and helps to understand controlling factors and possible solutions to overcome the limitations of undertaking SAR-based imaging of the landmass. This is the first time such a nationwide assessment is performed in preparation for acquisition and processing of SAR data in the United Kingdom, and any other country in the world. Analysis of the ERS-1/2 and ENVISAT archives reveals potential for multi-interferogram SAR Interferometry (InSAR) for the entirety of Britain using ERS-1/2 in descending mode, with 100% standard image frames showing at least 20 archive scenes available. ERS-1/2 ascending and both ENVISAT modes show potential for non-interferometric and single-pair InSAR for the vast majority of Britain, and multi-interferogram only for 13% to 38% of the available standard frames. Based on NEXTMap® Britain Digital Terrain Model (DTM) we simulate SAR layover, foreshortening and shadow to the ERS-1/2 and ENVISAT Lines-Of-Sight (LOS), and quantify changes of SAR distortions with variations in mode, LOS incidence angles and ground track angles, local terrain orientation, and the effect of scale due to the input DTM resolution. The simulation is extended to the ~ 230,000 km2 landmass, and shows limited control of local topography on the radar terrain visibility. According to the 50 m to 5 m DTM-based simulations, ~ 1.0–1.4% of Great Britain could potentially be affected by shadow and layover in each mode. Only ~ 0.02–0.04% overlapping between ascending and descending mode distortions is found, this indicating the negligible proportion of the landmass that cannot be monitored using either imaging mode. We calibrate the CORINE Land Cover 2006 (CLC2006) using Persistent Scatterer (PS) datasets available for London, Stoke-On-Trent, Newcastle and Bristol, to quantify land cover control on the PS distribution and characterise the CLC2006 classes in terms of the potential PS density they could provide. Despite predominance of rural land cover types, we predict potential for over 12.8 M monitoring targets for each acquisition mode using a set of image frames covering the entire landmass. We validate our assessment by processing with the Interferometric Point Target Analysis (IPTA) 55 ERS-1/2 SAR scenes depicting South Wales between 1992 and 1999. Although absolute differences between predicted and observed target density are revealed, relative densities and rankings among the various CLC2006 classes are found constant across the calibration and validation datasets. Rescaled predictions for Britain show potential for a total of 2.5 M monitoring targets across the landmass. We examine the use of the topographic and land cover feasibility maps for landslide studies in relation to the British Geological Survey's National Landslide Database and DiGMapGB mass movement layer. Building upon recent literature, we finally discuss future perspectives relating to the replication of our feasibility assessment to account for higher resolution SAR imagery, new Earth explorers (e.g., Sentinel-1) and improved processing techniques, showing potential to generate invaluable sources of information on land motions and geohazards in Great Britai

Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR)

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R-2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments

Construction Of Radar SAR Images From Digital Terrain Model And Geometric Corrections

International audienceWe propose in this paper an original method to correct the geometric distortions of a radar image. The comparison of satellite data, reveals specific problems. Data can be noisy, but especially the geometry of their acquisition requires corrections for comparaisons between them. In this paper we show how highly deformed radar images can be geometrically corrected and compared to map data coming from digital terrain models and also with data coming from SPOT satellite. Radar images used, are from the sensor airborne radar Varan, which is used for data acquisition campaign in the SouthEast of France. Applications include both structural geology, land cover or study of coastline. We propose a solution to rectify radar image in the geometry of a numerical terrain model. The method adopted here, is to produce a synthesis radar image by encoding all flight parameters of aircraft or satellite from a digital terrain model; radar image can then be compared to the synthetic image because points of landmarks can be clearly identified. Finally, we obtain a correspondence between the points of real radar image distorted, and those in the land or map

Integrating Vegetation Indices Models and Phenological Classification with Composite SAR and Optical Data for Cereal Yield Estimation in Finland (Part I)

Special Issue Microwave Remote Sensing.Abstract: During 1996–2006 the Ministry of Agriculture and Forestry in Finland, MTT Agrifood Research Finland and the Finnish Geodetic Institute carried out a joint remote sensing satellite research project. It evaluated the applicability of composite multispectral SAR and optical satellite data for cereal yield estimations in the annual crop inventory program. Three Vegetation Indices models (VGI, Infrared polynomial, NDVI and Composite multispetral SAR and NDVI) were validated to estimate cereal yield levels using solely optical and SAR satellite data (Composite Minimum Dataset). The average R2 for cereal yield (yb) was 0.627. The averaged composite SAR modeled grain yield level was 3,750 kg/ha (RMSE = 10.3%, 387 kg/ha) for high latitude spring cereals (4,018 kg/ha for spring wheat, 4,037 kg/ha for barley and 3,151 kg/ha for oats). Keywords: Composite multispectral modeling; SAR; classification; SatPhenClass algorithm; minimum dataset; cereal yield; phenology; LAI-bridge; CAP; IACS; FLPISPeer reviewe

Image fusion techniqes for remote sensing applications

Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts. The aim of this survey paper is to describe three typical applications of data fusion in remote sensing. The first study case considers the problem of the Synthetic Aperture Radar (SAR) Interferometry, where a pair of antennas are used to obtain an elevation map of the observed scene; the second one refers to the fusion of multisensor and multitemporal (Landsat Thematic Mapper and SAR) images of the same site acquired at different times, by using neural networks; the third one presents a processor to fuse multifrequency, multipolarization and mutiresolution SAR images, based on wavelet transform and multiscale Kalman filter. Each study case presents also results achieved by the proposed techniques applied to real data

The 1993-1994 Surge Of Bering Glacier, Alaska Observed With Satellite Synthetic Aperture Radar

Thesis (M.S.) University of Alaska Fairbanks, 1996Sequential synthetic aperture radar (SAR) images acquired by the First European Remote Sensing Satellite (ERS-1) were employed for observation of the 1993-'94 surge of Bering Glacier, Alaska. Evidence of accelerated motion became visible in late April 1993. Subsequently the surge front propagated down-glacier at a mean velocity of 90 m/day between 19 May and 25 August, reaching most of the 34 km perimeter of the terminus by shortly after 25 August. The calving terminus then advanced rapidly into proglacial Vitus Lake at a maximum rate, during 9 August to 18 October, of 19 m/day in its central area. The propagating surge front consisted of a distributed region of undulations and bulges on the glacier surface having heights, estimated from SAR data, of 40 to 110 m and widths varying from 0.7 to 1.5 km. The measurements were made using terrain-corrected, geocoded and coregistered images. <p