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Article

Regional Landslide Identification Based on Susceptibility Analysis and Change Detection

by 1,2, 1,2,*, 1, 1, 2, 1 and 2
1
School of Environment, Northeast Normal University, Changchun 130024, China
2
Key Laboratory for Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun 130024, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(10), 394; https://doi.org/10.3390/ijgi7100394
Received: 12 July 2018 / Revised: 25 September 2018 / Accepted: 26 September 2018 / Published: 29 September 2018
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. View Full-Text
Keywords: susceptibility analysis; change detection; landslide identification; remote sensing; geographical information systems (GIS); Landsat 8 susceptibility analysis; change detection; landslide identification; remote sensing; geographical information systems (GIS); Landsat 8
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MDPI and ACS Style

Si, A.; Zhang, J.; Tong, S.; Lai, Q.; Wang, R.; Li, N.; Bao, Y. Regional Landslide Identification Based on Susceptibility Analysis and Change Detection. ISPRS Int. J. Geo-Inf. 2018, 7, 394. https://doi.org/10.3390/ijgi7100394

AMA Style

Si A, Zhang J, Tong S, Lai Q, Wang R, Li N, Bao Y. Regional Landslide Identification Based on Susceptibility Analysis and Change Detection. ISPRS International Journal of Geo-Information. 2018; 7(10):394. https://doi.org/10.3390/ijgi7100394

Chicago/Turabian Style

Si, Alu, Jiquan Zhang, Siqin Tong, Quan Lai, Rui Wang, Na Li, and Yongbin Bao. 2018. "Regional Landslide Identification Based on Susceptibility Analysis and Change Detection" ISPRS International Journal of Geo-Information 7, no. 10: 394. https://doi.org/10.3390/ijgi7100394

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