The Chamoli Earthquake (1999): Transitioning from Point-Based to Polygon-Based Landslide Inventory in Uttarakhand

The geologically recent Himalayas, characterized by fragile slopes and active tectonics, are inherently susceptible to natural hazards, including frequent earthquakes and associated secondary hazards. Northwest Indian states like Jammu & Kashmir, Ladakh, Himachal Pradesh, and Uttarakhand experience these events with varying intensities, posing significant risks to infrastructure and livelihoods. Among these hazards are earthquakes-induced landslides (EIL), which often modify the landscapes and affect communities. While the existing inventory of EIL provides valuable insights, limitations require further refinement. For instance, the point-based inventory by Barnard et al. (2001) for the Chamoli region mapped 56 EIL within the 226 sq. km. of the region from the epicentre. The lack of landslide geometry in the inventory restricts detailed analysis and hampers robust landslide modelling and risk assessment. To bridge this gap, this study presents an approach to transition from the conventional point-based inventory to a more comprehensive polygon-based inventory for EILs triggered by the 1999 Chamoli earthquake (Mw 6.8). Utilizing pre- and post-event Landsat-5 imagery, the study employs multi-spectral analysis techniques like Pseudo Colour Transform (PCT), Normalized Difference Vegetation Index (NDVI), and image differencing. By integrating these analyses with visual interpretation (shape of the landslide), the study accurately delineates the spatial extent and geometry of EILs in the Chamoli and Rudraprayag districts of Uttarakhand, India. By providing detailed information and spatial distribution of landslides, this approach allows for enhanced risk assessment. Future research will utilize high-resolution (5m) IRS-1C/1D panchromatic imagery to (1) identify smaller-scale landslides, (2) monitor land-use/land-cover changes within existing landslide zones for a five-year period, and (3) analyze the resulting landscape dynamics in the aftermath of the Chamoli earthquake. This analysis will shed light on the intricate relationship between land-use modifications and post-seismic landscape evolution.