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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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              <text>Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle</text>
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              <text>Takashi Shibayama, Yoshio Yamaguchi, Hiroyoshi Yamada</text>
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              <text>This paper addresses the local incidence angle dependence of several polarimetric indices corresponding to landslides in forested areas. Landslide is deeply related to the loss of human lives and their property. Various kinds of remote sensing techniques, including aerial photography, high-resolution optical satellite imagery, LiDAR and SAR interferometry (InSAR), have been available for landslide investigations. SAR polarimetry is potentially an effective measure to investigate landslides because  fully-polarimetric SAR (PolSAR) data contain more information compared to conventional single- or dual-polarization SAR data. However, research on landslide recognition utilizing polarimetric SAR (PolSAR) is quite limited. Polarimetric properties of landslides have not been examined quantitatively so far. Accordingly, we examined the polarimetric scattering properties of landslides by an assessment of how the decomposed scattering power components and the polarimetric correlation coefficient change with the local incidence angle. In the assessment, PolSAR data acquired from different directions with both spaceborne and airborne SARs were utilized. It was found that the surface scattering power and the polarimetric correlation coefficient of landslides significantly decrease with the local incidence angle, while these indices of surrounding forest do not. This fact leads to establishing a method of effective detection of landslide area by polarimetric information.</text>
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              <text>2015</text>
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              <text>Synthetic Aperture Radar (SAR), polarimetry, power decomposition, co-polarization correlation coefficient, local incidence angle, landslide</text>
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              <text>DOI: 10.3390/rs71115424</text>
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              <text>Remote Sensing</text>
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              <text>MDPI AG</text>
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              <text>Science</text>
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              <text>EN</text>
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