LANDSLIDE INVENTORY USING INSAR AND ANCILLARY DATASETS FOR SUSCEPTIBILITY IN WESTERN AREA, SIERRA LEONE

被引:0
|
作者
Kursah, Matthew Biniyam [1 ,2 ,4 ]
Wang, Yong [1 ,3 ,4 ]
机构
[1] UESTC, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Educ, Dept Geog Educ, Winneba, Ghana
[3] East Carolina Univ, Dept Geog Planning & Environm, Greenville, NC 27858 USA
[4] UESTC, Ctr Informat Geosci, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Interferometric SAR (InSAR); Landslide susceptibility; Regent landslide; SBAS;
D O I
10.1109/igarss.2019.8898702
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Producing a landslide susceptibility (LS) map using the statistical techniques such as the density ratio heavily relies on an existing inventory dataset. In the absence of the data in Western Area, Sierra Leone (Africa), the SBAS-InSAR technique was applied for detecting the ground deformation using multi temporal Sentinel-1 SAR datasets from July 2015 to August 2017. The derived slope displacements coupled with the geomorphological evidence in the ancillary data are used to map the possible landslides in the area. The density ratio technique was used to generate landslide parameter class values. The values are aggregated to create the LS map and the result validated using the degree of fit and the error index. This paper, therefore, highlights a method of creating the landslide inventory and susceptibility in areas where the inventory data are limited or even absent.
引用
收藏
页码:939 / 942
页数:4
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