Abstract
High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.
Highlights
Commercial high-resolution synthetic aperture radar (SAR) satellites, such as TerraSAR-X [1] (developed by the German Space Center (DLR)), COSMO-SkyMed [2], and Radarsat-2 [3], have been widely used for significant applications, such as in the monitoring of natural hazards and disasters [4]: Satellite data are useful for acquiring the scale and center of damage in a huge disaster
In the case of TerraSAR-X, the motion of TerraSAR-X was controlled in a predefined tube of 250-m radius throughout the entire mission [31], making it possible to acquire a high-quality digital elevation model (DEM) by repeat-pass interferometry
A problem is that the interferograms contain errors caused by atmospheric disturbances (ADs); it was necessary to comprehensively understand these errors
Summary
Commercial high-resolution synthetic aperture radar (SAR) satellites, such as TerraSAR-X [1] (developed by the German Space Center (DLR)), COSMO-SkyMed [2] (developed by the Italian Space Agency), and Radarsat-2 [3] (developed by the Canadian Space Agency), have been widely used for significant applications, such as in the monitoring of natural hazards and disasters [4]: Satellite data are useful for acquiring the scale and center of damage in a huge disaster Images of both before and after such events, are used to acquire the damaged area in general. Temporal decorrelation in vegetation areas and atmospheric disturbances (ADs) exhibit inherent accuracy limitations [9,10]
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