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.
The interferometric SAR coherence-change technique with coherence filter and polarization (HH and HV) has been used to detect the parts of buildings damaged by the 2015 Gorkha Earthquake. A survey of the building damage was conducted in every house to evaluate the detection accuracy in the Khokana and Sankhu urban areas in the Kathmandu Valley of Nepal. The damaged parts of the urban area were adequately detected using coherence-change (∆γ) values obtained before the earthquake (γ pre ) and during the inter-seismic stage of the earthquake (γ int ). The use of a coherence filter effectively increased overall accuracy by ~2.1 to 7.0 % with HH polarization. The incorporation of HV polarization marginally increased the accuracy (~0.9 to 1.2 %). It was confirmed that road damage due to liquefaction was also observed using the interferometric SAR coherence-change detection technique. The classification accuracy was lower (27.1-35.1 %) for areas that were damaged. However, higher accuracy (97.8-99.2 %) was achieved for areas that were damage-free, in ∆γ obtained from HH and HV polarization with a coherence filter. This helped to identify the damaged urban areas (using this technique) immediately after occurrence of an earthquake event.
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