Multicriteria analysis for landslide inventory mapping using PS-InSAR

Meghanadh, Devara; Tiwari, Ashutosh; Dwivedi, Ramji

doi:10.1109/tengarss48957.2019.8976054

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Fourth, calculate and visualize the value of surface deformation at each landslide location. The surface deformation value or LOS displacement value obtained from the interferogram is the result of measuring the movement between the radar antenna and a location on the earth's surface [15]. This value is represented by a size of 100 by 100 meter pixels resolution.…”

Section: Methods Of Sar Data Processingmentioning

confidence: 99%

“…DInSAR works by utilizing different phases of SAR images in the same area at different times [10]. The use of DInSAR for the detection and monitoring of ground motion includes the persistent scatterer Int J Elec & Comp Eng ISSN: 2088-8708  Landslide assessment using interferometric synthetic aperture radar in … (Dimas Bayu Ichsandya) 2615 interferometry synthetics aperture radar (PSInSAR) and small baseline area subset (SBAS) method [2], [11]- [15]. PSInSAR works using a single master interferogram to form persistent scatterer (PS) [16].…”

Section: Introductionmentioning

confidence: 99%

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Landslide assessment using interferometric synthetic aperture radar in Pacitan, East Java

Ichsandya

Dimyati

Shidiq

et al. 2022

IJECE

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<span>Landslides are a common type of disaster in Indonesia, especially in steep-slope areas. The landslide process can be well understood by measuring the surface deformation. Currently, there are no practical solutions for measuring surface deformation at landslide locations other than field surveys in the Pacitan Regency. We apply LiCSBAS, to identify surface deformation in several landslide locations in a specific non-urban area with mixed topographical features. LiCSBAS is a module that utilizes data from the project of looking inside the continent from space (LiCS), using the new small baseline area subset (NSBAS) method. This study utilizes the leaf area index (LAI) to validate the ability of LiCSBAS to detect surface deformation values at landslide locations. The study succeeded in identifying surface deformations at 100 landslide locations, with deformation values ranging from 15.1 to 10.9 millimeters per year. Most of the landslide locations are closely related to volcanic rocks and volcanic sediments on slopes of 30–35°. The NSBAS method in the LiCSBAS module can reduce gaps error in the sentinel-1 image network. However, the utilization of the C-band at a pixel size of 100 meters made surface deformation only well detectable in a large open landslide area.</span>

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Section: Methods Of Sar Data Processingmentioning

confidence: 99%