期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：3
页码：2614-2625
DOI：10.11591/ijece.v12i3.pp2614-2625
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：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.
