Date of Award
2023
Document Type
Open Access Dissertation
Degree Name
Doctor of Philosophy in Geological Engineering (PhD)
Administrative Home Department
Department of Geological and Mining Engineering and Sciences
Advisor 1
Thomas Oommen
Committee Member 1
Snehamoy Chatterjee
Committee Member 2
Sajin Kumar K.S.
Committee Member 3
Greg Waite
Abstract
The Landslide Early Warning System (LEWS) is a non-structural approach to mitigate landslide risk by alerting vulnerable communities at an early stage. This study aimed to develop a regional LEWS for rain-induced shallow landslides in Idukki, a mountainous district in India with sparse rainfall data. The landslide model consists of a rainfall component and a slope stability component. Satellite precipitation data can be used in data-sparse regions, but they must be calibrated because they tend to underestimate rainfall. To improve the accuracy of satellite data, this study used a geostatistics-based multi-criteria approach to identify optimal locations to install new rain gauges, thus enhancing the rain gauge network's monitoring capability. A rainfall threshold was developed for Idukki, accounting for intra-seasonal variations in rainfall patterns and extreme rainfall events. The slope stability component of the model is limited by the lack of high-resolution soil properties, which are time-consuming and impractical to acquire using conventional methods. To overcome this limitation, this research proposed developing empirical relationships between sub-surface resistivity and soil properties, providing a regional-scale high-resolution soil property dataset for slope susceptibility assessment. Finally, a cloud-based LEWS was developed using Google Earth Engine, combining the rainfall threshold and high-resolution slope stability models, with the advantage of readily available near real-time data, processing power, user accessibility, and the opportunity for future updates.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Chakrapani Lekha, Vishnu, "Developing a regional scale landslide early warning system in a data-sparse region using remote sensing, geostatistics, and Google Earth Engine", Open Access Dissertation, Michigan Technological University, 2023.