Geomorphic characterization by integrating automated approaches for sustainable land use planning in the earthquake-prone Himalayan region of Uttarakhand, India

This study leverages two cutting-edge automated landform classification approaches—Topographic Position Index (LCTPI) and Geomorphon (LCGm)—to map and categorize landforms in Uttarakhand, a strategically vital region in the Himalayas frequently impacted by natural hazards. Situated at the subduction boundary of the Indian and Eurasian tectonic plates, Uttarakhand's complex landscape demands innovative approaches for sustainable land use planning. Our analysis links classified landforms to critical factors such as slope, geology, soil types, land use land cover (LULC) patterns, fault density, and regional seismicity. Results reveal that high ridges, deep valleys (LCTPI), and slopes (LCGm), predominantly covered by trees and rangelands, are associated with lithosols and dystric cambisols soil types from the Precambrian period. In contrast, flat areas, shoulders, footslopes, U-shaped valleys, open slopes, and mild slope ridges, mainly used for agriculture and urban development, exhibit lower seismic activity. Notably, shallow earthquakes are more frequent in deep valleys and high ridges, which have low to moderate fault density and are majorly occupied by trees and rangelands. This research offers a robust framework for geomorphic characterization that can be adapted to other regions, despite the inherent limitations of automated studies, such as DEM resolution and neighbourhood cell size. Our approach supports sustainable land use planning, biodiversity preservation, natural resource management, and disaster risk reduction, ultimately fostering resilient futures in the built environment. This study emphasizes the necessity of integrating geomorphic insights into the planning process to mitigate natural hazards and enhance environmental sustainability in the Himalayan region by providing actionable insights for land use planners and policymakers.