EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Characterising landslide processes using limited data: case study on East Sikkim, India

Renée Heijenk1, Bruce Malamud1, Claire Dashwood2, Joanne Wood3, Christian Arnhardt2, and Helen Reeves2
Renée Heijenk et al.
  • 1King's College London, Geography, London, United Kingdom of Great Britain and Northern Ireland (
  • 2British Geological Survey, Engineering Geology, Keyworth, United Kingdom
  • 3University of Exeter, Centre for Geography and Environmental Science, Exeter, United Kingdom

Landslide domains are a useful tool for characterising and subdividing a region into homogenous units reflecting the style of landsliding, which is controlled by the environmental characteristics (e.g. geology, relief). Landslide domains can provide a framework for the application of landslide knowledge obtained from a data-rich area across areas within the domain that are less data rich but have similar environmental characteristics. We have constructed landslide domains for East Sikkim using a landslide inventory, geology, relief and expert-based knowledge of landslide processes in the region. First, we catalogued landslide processes in East Sikkim using peer-reviewed literature, supplementing this with the mapping of over 450 translational landslides and debris flows in Google Earth through visual analysis utilising process knowledge from the catalogue. Several dozens of old landslides were mapped with stereographic analysis of four Cartosat-1 stereo pairs (90 km2) captured in March and December of 2011. Morphometric maps were constructed from Aster GDEM. Finally, the driving environmental characteristics for each process have been determined via statistical analyses to inform expert-driven construction of the landslide domains. We find that landslide domains explain landslide processes in East Sikkim well, but they may be limited by the amount of data that is available. The construction of landslide domains is flexible and can be applied to many different areas. Future work includes the testing of large-scale regions and inclusion into susceptibility models, where we hope that they will facilitate the construction of more accurate and representative susceptibility maps.

How to cite: Heijenk, R., Malamud, B., Dashwood, C., Wood, J., Arnhardt, C., and Reeves, H.: Characterising landslide processes using limited data: case study on East Sikkim, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18520,, 2020

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