Relationships between landslide types and topographic attributes in a loess catchment, China View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-12

AUTHORS

Fanyu Zhang, Wenwu Chen, Gao Liu, Shouyun Liang, Chao Kang, Faguo He

ABSTRACT

Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of shallow landslides triggered by rainfall. As a result, these landslides influence the evolution of local surface topography. In this research, an area of 2.6 km2 loess catchment in the Huachi County was selected as the study area locating in the Chinese Loess Plateau. The landslides inventory and landslide types were mapped using global position system (GPS) and field mapping. The landslide inventory shows that these shallow landslides involve different movement types including slide, creep and fall. Meanwhile, main topographic attributes were generated based on a high resolution digital terrain model (5 m × 5 m), including aspect, slope shape, elevation, slope angle and contributing area. These maps were overlaid with the spatial distributions of total landslides and each type of landslides in a geographic information system (GIS), respectively, to assess their spatial frequency distributions and relative failure potentials related to these selected topographic attributes. The spatial analysis results revealed that there is a close relation between the topographic attributes of the post-landsliding local surface and the types of landslide movement. Meanwhile, the types of landslide movement have some obvious differences in local topographic attributes, which can influence the relative failure potential of different types of landslides. These results have practical significance to mitigate natural hazard and understand geomorphologic process in thick loess area. More... »

PAGES

742-751

Journal

TITLE

Journal of Mountain Science

ISSUE

6

VOLUME

9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11629-012-2377-7

DOI

http://dx.doi.org/10.1007/s11629-012-2377-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025026425


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