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This paper reports prompt space-borne ALOS-2 SAR observation results of Hokkaido-Iburi-Tobu earthquake on 2018/09/06. Emphasis is placed on quick survey for disaster monitoring using fully polarimetric data. On 2018/09/08, ALOS-2 has acquired data over the disaster area. By comparison of the previous data (2017/08/26) before the earthquake, damaged areas by landslides are clearly detected. The analysis is based on the scattering power decomposition, which retrieves scattering mechanism change from bare soil surface caused by landslide and serves to identify the landslide location. The decomposition and anisotropy images are presented to show the effectiveness of fully polarimetric SAR sensing from space.

Polarimetric similarity is a parameter for measuring the similarity between two scattering mechanisms. In this paper, we propose a novel model-based target classification technique using a compensated polarimetric similarity parameter between two coherency matrices. In general, the ensemble average coherency matrix elements have magnitude imbalance, thus the contribution degree to the polarimetric similarity differs for each element. We illustrate how to compensate the contribution degree, and then the proposed method is tested on L-band fully polarimetric ALOS-2/ PALSAR-2 data sets by using 4 theoretical scattering models (surface scattering, double-bounce scattering, volume scattering, and 22.5°oriented dihedral scattering). The classification results show that the new compensation scheme serves to better classification.

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