RESEARCH ARTICLE


The Correlation of Spatial Distribution Between Surface Deformation and Landslides by SBAS-InSAR and Spatial Analysis in Longnan Region, China



Xue Yating, Meng Xingmin*, Guo Peng, Li Kai, Chen Guan
Key Laboratory of West China's Environmental Systems, Lanzhou University, Gansu, China.


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Creative Commons License
© 2015 Yating et al;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Key Laboratory of West China's Environmental Systems, Lanzhou University, Gansu, China; Tel: +86 13659478056; E-mail: xmmeng@lzu.edu.cn


Abstract

We use interferometric synthetic aperture radar (InSAR) time-series analysis of Envisat ASAR data to reveal the correlation of distribution between surface deformation and landslides in western China. The results of SBAS-InSAR revealed that the velocity of surface deformation is between -18.6mm/year to 26.8mm/year. The landslides data which we extracted from SPOT 5 image and investigated in field were correlated with altitude, lithology, slope, degree, land-use, fault, NDVI and distance to river. We found that the landslides mainly distribute on 13°~41° slope degree, 1200m~2000m altitude, the strong human activity, the poor vegetation covered, near the river and fault, underlain medium thickness limestone and thin-layered siltstone and mud stone. Using the landslides distribution features, landslides will be identified from the results of surface deformation and landslides susceptibility will be assessed. This method can help local government rapidly monitor landslides and assess landslides susceptibility on large scale.

Keywords: SBAS-InSAR, landslides, surface deformation, spatial analysis.