Regional Landslide Identification Based on Susceptibility Analysis and Change Detection
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 improve...
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doaj-6ff28b765e1041bda4a9c5bc0225c18d2020-11-25T02:24:44ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-09-0171039410.3390/ijgi7100394ijgi7100394Regional Landslide Identification Based on Susceptibility Analysis and Change DetectionAlu Si0Jiquan Zhang1Siqin Tong2Quan Lai3Rui Wang4Na Li5Yongbin Bao6School of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaKey Laboratory for Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun 130024, ChinaSchool of Environment, Northeast Normal University, Changchun 130024, ChinaKey Laboratory for Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun 130024, ChinaLandslide 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.http://www.mdpi.com/2220-9964/7/10/394susceptibility analysischange detectionlandslide identificationremote sensinggeographical information systems (GIS)Landsat 8 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alu Si Jiquan Zhang Siqin Tong Quan Lai Rui Wang Na Li Yongbin Bao |
spellingShingle |
Alu Si Jiquan Zhang Siqin Tong Quan Lai Rui Wang Na Li Yongbin Bao Regional Landslide Identification Based on Susceptibility Analysis and Change Detection ISPRS International Journal of Geo-Information susceptibility analysis change detection landslide identification remote sensing geographical information systems (GIS) Landsat 8 |
author_facet |
Alu Si Jiquan Zhang Siqin Tong Quan Lai Rui Wang Na Li Yongbin Bao |
author_sort |
Alu Si |
title |
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection |
title_short |
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection |
title_full |
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection |
title_fullStr |
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection |
title_full_unstemmed |
Regional Landslide Identification Based on Susceptibility Analysis and Change Detection |
title_sort |
regional landslide identification based on susceptibility analysis and change detection |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2018-09-01 |
description |
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. |
topic |
susceptibility analysis change detection landslide identification remote sensing geographical information systems (GIS) Landsat 8 |
url |
http://www.mdpi.com/2220-9964/7/10/394 |
work_keys_str_mv |
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