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<p>The incidence of landslides in the&#xa0;Himalayan region is a matter of global concern, as they often result in catastrophic consequences. Recurrent landslides cause huge societal, environmental, and economic losses. There are several causative factors behind the initiation of landslides but in recent years,&#xa0;anthropogenic activities and&#xa0;alteration in rainfall patterns due to climate change may play key roles for the initiation of landslides. This study focuses ona special category of landslide at Pangthang, East Sikkim,&#xa0;and identifies it as an unusual&#xa0;shallow landslide, as this landslide occurred in a topographically stable area and landslide&#xa0;inventory indicates that this region has not previously experienced any landslides. The objective of this study is to identify the dominating factors behind&#xa0;this landslide. The job was initiated with the field visit subsequently geotechnical investigation and topographical survey have been carried out. Thirty years rainfall data has been collected and analysed. Thematic layers corresponding to various causative factors like Rainfall (RF), Built-up Index (BUI), Normalized Difference Vegetation Index (NDVI),&#xa0;Soil (So), Geology (Gl), Distance to Road (DR), Distance to Stream (DS), Elevation (El), Slope (Sl), Seismic Magnitude Zone (SMZ), Curvature (Cu), Aspect (As), Lineament Density (LD), and&#xa0;Topographic Wetness Index (TWI) have been prepared through Geospatial Technology.&#xa0;Understanding the significance of&#xa0;different landslide affecting elements to initiate a landslide is really challenging. To achieve the objective Multi-Criteria Decision Making (MCDM) Method, Fuzzy Analytical Hierarchy Process (FAHP), has been used.&#xa0;According to the findings of this study, an area that once seemed stable can experience landslides as a result of climate change and&#xa0;anthropogenic activities. A significant degree of robustness in the results has been established by sensitivity analysis.</p>

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Impact of Climate Change and Anthropogenic Activities on Shallow Landslide Initiation in Pangthang, East Sikkim: A Geospatial Technology and FAHP-Based Approach

  • 期刊论文

  • 发表日期：

    2025年7月24日

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  • Joyita Golder,
  • Jayanta Das,
  • Gupinath Bhandari

摘要

The incidence of landslides in the Himalayan region is a matter of global concern, as they often result in catastrophic consequences. Recurrent landslides cause huge societal, environmental, and economic losses. There are several causative factors behind the initiation of landslides but in recent years, anthropogenic activities and alteration in rainfall patterns due to climate change may play key roles for the initiation of landslides. This study focuses ona special category of landslide at Pangthang, East Sikkim, and identifies it as an unusual shallow landslide, as this landslide occurred in a topographically stable area and landslide inventory indicates that this region has not previously experienced any landslides. The objective of this study is to identify the dominating factors behind this landslide. The job was initiated with the field visit subsequently geotechnical investigation and topographical survey have been carried out. Thirty years rainfall data has been collected and analysed. Thematic layers corresponding to various causative factors like Rainfall (RF), Built-up Index (BUI), Normalized Difference Vegetation Index (NDVI), Soil (So), Geology (Gl), Distance to Road (DR), Distance to Stream (DS), Elevation (El), Slope (Sl), Seismic Magnitude Zone (SMZ), Curvature (Cu), Aspect (As), Lineament Density (LD), and Topographic Wetness Index (TWI) have been prepared through Geospatial Technology. Understanding the significance of different landslide affecting elements to initiate a landslide is really challenging. To achieve the objective Multi-Criteria Decision Making (MCDM) Method, Fuzzy Analytical Hierarchy Process (FAHP), has been used. According to the findings of this study, an area that once seemed stable can experience landslides as a result of climate change and anthropogenic activities. A significant degree of robustness in the results has been established by sensitivity analysis.