Detecting Mountainous Landslides by SAR Polarimetry: A Comparative Study Using Pi-SAR-L2 and X-band SARs

Shimada, Masanobu; Kawano, Noriyuki; Ohki, Masato; Motooka, Takeshi; Wada, Yutaka

doi:10.2322/tastj.12.pn_9

Cited by 13 publications

(10 citation statements)

References 5 publications

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“…Note, however, that the observation geometry has not been taken into consideration in these papers. Additionally, the correlation coefficient between HH (horizontal transmitted and horizontal received) and VV (vertical transmitted and vertical received) polarizations and other polarimetric indices were focused on for landslide detection in Shimada et al [6]. They revealed that the magnitude of the HH-VV correlation coefficient showed high values at landslides and smooth surfaces.…”

Section: Introductionmentioning

confidence: 99%

Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle

2015

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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. OPEN ACCESSRemote Sens. 2015, 7 15425

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Section: Introductionmentioning

confidence: 99%

Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle

2015

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“…Thus, the applicability of the methods used in this study might be hindered if both the ascending and descending data pairs are not available. Besides the intensity and coherence, the use of SAR polarimetry, polarimetric decomposition and the synergetic use of optical and polarimetric SAR data are also showed effectiveness in landslide detection [6,[42][43][44]. As each method has advantages and shortcomings when selecting a method for landslide detection purpose, the priority must be given based on the availability of SAR data, geographic conditions of the target area, and the nature of the landslide.…”

Section: Discussionmentioning

confidence: 99%

Earthquake-Induced Landslide Mapping for the 2018 Hokkaido Eastern Iburi Earthquake Using PALSAR-2 Data

et al. 2019

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Timely information about landslides during or immediately after an event is an invaluable source for emergency response and management. Using an active sensor, synthetic aperture radar (SAR) can capture images of the earth’s surface regardless of weather conditions and may provide a solution to the problem of mapping landslides when clouds obstruct optical imaging. The 2018 Hokkaido Eastern Iburi earthquake (Mw 6.6) and its aftershocks not only caused major damage with severe loss of life and property but also induced many landslides across the area. To gain a better understanding of the landslides induced by this earthquake, we proposed a method of landslide mapping using pre- and post-event Advanced Land Observation Satellite 2 Phased Array L-band Synthetic Aperture Radar 2 (ALOS-2 PALSAR-2) images acquired from both descending and ascending orbits. Moreover, the accuracy of the classification results was verified by comparisons with high-resolution optical images, and ground truth data (provided by GSI, Japan). The detected landslides show a good match with the reference optical images by visual comparison. The quantitative comparison results showed that a combination of the descending and ascending intensity-based landslide classification had the best accuracy with an overall accuracy and kappa coefficient of 80.1% and 0.45, respectively.

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“…Landslides can also be mapped by the backscattered energy difference using SAR imagery before and after a landslide (Yamada et al, 2013;Konishi and Suga, 2018) or with polarimetry-based approaches (Rodriguez et al, 2002;Czuchlewski et al, 2003;Shimada et al, 2014;Shibayama et al, 2015;Plank et al, 2016). Several polarimetric decomposition methods have been developed for classifying land cover based on scattering mechanisms Pottier, 1996, 1997;Freeman and Durden, 1998).…”

Section: Landslide Mappingmentioning

confidence: 99%

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

et al. 2019

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Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward toward improved characterization of evolving hazards and risk across HMA.

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Detecting Mountainous Landslides by SAR Polarimetry: A Comparative Study Using Pi-SAR-L2 and X-band SARs

Cited by 13 publications

References 5 publications

Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle

Polarimetric Scattering Properties of Landslides in Forested Areas and the Dependence on the Local Incidence Angle

Earthquake-Induced Landslide Mapping for the 2018 Hokkaido Eastern Iburi Earthquake Using PALSAR-2 Data

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

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