Abstract
Persistent scatterer synthetic aperture radar interferometry (PSI) is a powerful remote sensing technique to detect and measure deformation of the Earth's crust - such as subsidence and landslides - with an accuracy of a few millimeters. Deformation is measured at specific points in a radar image called persistent scatterers (PS), which are characterized by long-term constant backscattering properties (high coherence) of the radar signal. Reliable PSI processing requires a stack of 15-50 SAR images and more, and processing is time-consuming (computational costs) and expensive (referring to both, costs for the SAR data and labor costs). Previous research for PS assessment used already acquired SAR data. This paper presents two new methods for predicting PS prior to the radar recording of the area of interest using freely available or low-cost land cover data, topographical maps and OpenStreetMap data. In the procedure, the distance between the assessed PS is calculated and classified regarding to the applicability for PSI processing. Additionally, the dispersion of the assessed PS within the site is analyzed. The results of the two assessment methods are validated using data of real PSI processing. Here, we show that the developed PS assessment techniques are fast and reliable tools to test the spatial applicability of PSI.
Original language | English |
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Pages (from-to) | 132-147 |
Number of pages | 16 |
Journal | ISPRS Journal of Photogrammetry and Remote Sensing |
Volume | 85 |
DOIs | |
State | Published - Nov 2013 |
Keywords
- GIS
- Persistent scatterer processing
- Prediction
- Radar
- SAR