Multi-frequency, multi-polarization airborne synthetic aperture radar (SAR) observations of sea ice in the southern Sea of Okhotsk were carried out in February 1999 in conjunction with RADARSAT SAR observations. The final goal of this study is to clarify the backscattering characteristics and to understand the scattering mechanisms of sea ice in the Sea of Okhotsk by using microwave multiparametric SAR. The airborne SAR (Pi-SAR) has two frequencies (X- and L-band) and multi-polarization (HH, VV, HV, VH) with 1.5 m (X-band) and 3.0 m (L-band) resolution. It was developed by the Communications Research Laboratory (X-band) and the National Space Development Agency of Japan (L-band). We show the frequency dependence and polarization properties of radar backscattering from sea ice. We find that it is possible to distinguish ice types by comparing backscattering from sea ice in the X- and L-bands. Investigation of the polarization characteristics at X-band was very useful for detecting the thin-ice area (e.g. nilas and gray ice).
The recognition of landslides and making their inventory map are considered to be urgent tasks not only for damage estimation but also for planning rescue and restoration activities.Owing to the capability of synthetic aperture radar (SAR) for day-and-night and all-weather imaging, various studies utilizing SAR data for landslide detection have been reported to date. Among the detection methods utilizing SAR data, those based on height differences accompanying landslides are attractive and should be further improved, since they can directly contribute to damage estimation through a volumetric estimation of landslides. In this context, we propose in this paper a landslide detection method utilizing height differences derived from pre-and post-event SAR digital elevation models (DEMs) combined with amplitude differences. The proposed method was applied to the landslides triggered by the 2016 Kumamoto earthquake. The application results demonstrate that SAR DEMs with a high altitudinal resolution can improve the detection ability and that the incorporation of the amplitude differences is effective for decreasing the number of false detections. Although the reliability of the proposed method is deemed moderate when evaluated on the basis of the kappa coefficients derived through an accuracy assessment, most of the outliers are correctly filtered out and large-and medium-scale landslides are detected. Therefore, the inventory maps derived from the proposed method are thought to be effective at the initial stage of planning rescue and restoration activities.
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