Paper Info
Title
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection.
Abstract
Landslide identification is an increasingly important research topic in remote sensing and the study of natural hazards. It is essential for hazard prevention, mitigation, and vulnerability assessments. Despite great efforts over the past few years, its accuracy and efficiency can be further improved. Thus, this study combines the two most popular approaches: susceptibility analysis and change detection thresholding, to derive a landslide identification method employing novel identification criteria. Through a quantitative evaluation of the proposed method and masked change detection thresholding method, the proposed method exhibits improved accuracy to some extent. Our susceptibility-based change detection thresholding method has the following benefits: (1) it is a semi-automatic landslide identification method that effectively integrates a pixel-based approach with an object-oriented image analysis approach to achieve more precise landslide identification; (2) integration of the change detection result with the susceptibility analysis result represents a novel approach in the landslide identification research field.
Year
DOI
Venue
2018
10.3390/ijgi7100394
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
susceptibility analysis,change detection,landslide identification,remote sensing,geographical information systems (GIS),Landsat 8
Data mining,Change detection,Computer science,Vulnerability assessment,Pixel,Landslide,Thresholding,Identification criteria,Natural hazard
Journal
Volume
Issue
ISSN
7
10
2220-9964
Citations 
PageRank 
References 
1
0.37
11
Authors
7
Name
Order
Citations
PageRank
Alu Si110.37
Ji quan Zhang283.66
Siqin Tong310.37
Quan Lai410.37
Rui Wang513953.65
Na Li63723.63
Yongbin Bao772.35