Abstract
Radar scattering mechanisms over landslide areas were studied using representative full polarimetric parameters: Freeman–Durden decomposition, and eigenvalue–eigenvector decomposition. Full polarimetric ALOS (Advanced Land Observation Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) datasets were used to examine landslides caused by the 2008 Iwate-Miyagi Nairiku Earthquake in northern Japan. The Freeman–Durden decomposition indicates that areas affected by large-scale landslides show dominance of the surface scattering component in both ascending and descending orbit data. The polarimetric parameters of eigenvalue–eigenvector decomposition, such as entropy, anisotropy, and alpha angle, were also computed over the landslide areas. Unsupervised classification based on the H- plane explicitly distinguishes landslide areas from others such as forest, water, and snow-covered areas, but does not perform well for farmland. A landslide area is difficult to recognize from a single-polarization image, whereas it is clearly extracted on the full polarimetric data obtained after the earthquake. From these results, we conclude that 30-m resolution full polarimetric data are more useful than 10-m resolution single-polarization PALSAR data in classifying land coverage, and are better suited to detect landslide areas. Additional information, such as pre-landslide imagery, is needed to distinguish landslide areas from farmland or bare soil.
Highlights
SAR (Synthetic Aperture Radar) is capable of observing the Earth’s surface in all weather conditions, day and night
A landslide caused by the 1999 Chi-chi earthquake in Taiwan was recognized using L-band airborne SAR data acquired after the disaster, and the characteristics of radar scattering mechanism were examined
Watanabe et al [10] analyzed full polarimetric data obtained from ALOS (Advanced Land Observation Satellite) data after the earthquake, and showed that the landslide areas were well detected by combining the surface scattering and backscattering coefficients in VH polarization ( 0VH)
Summary
SAR (Synthetic Aperture Radar) is capable of observing the Earth’s surface in all weather conditions, day and night. A landslide caused by the 1999 Chi-chi earthquake in Taiwan was recognized using L-band airborne SAR data acquired after the disaster, and the characteristics of radar scattering mechanism were examined. Watanabe et al [10] analyzed full polarimetric data obtained from ALOS (Advanced Land Observation Satellite) data after the earthquake, and showed that the landslide areas were well detected by combining the surface scattering and backscattering coefficients in VH polarization ( 0VH). We adopted two representative full polarimetric decomposition models: a physically-based Freeman–Durden decomposition model, and a mathematically-strict eigenvalue–eigenvector decomposition model These models are applied to the landslide areas, and to whole scenes, including forest, water surface and snow-covered areas, and areas of farmland or bare soil. The comprehensive analysis results for landslide and neighboring areas are presented to clarify the radar scattering characteristics over the landslide areas by comparing other categories from the “actual” data, and to assist the identification of landslide areas from the pre- and post-event data
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