Debris flows, a type of landslides, are not nowadays limited only to the periodic devastation of the geologically fragile Himalaya but also ubiquitous in weathered Deccan Volcanic Province of the cratonic south Indian peninsula. Comprehensive assessment of landslide hazard, pertinently, requires process-based modeling using simulation methods. Development of precipitation triggered debris flow simulation models of real events are still at a young stage in India, albeit, especially in tectonically less disturbed regions. A highly objective simulation technique has therefore been envisaged herein to model the debris flow run-out happened in Malin. This takes cues from a high- resolution DEM and other ancillary ground data including geotechnical and frictional parameters. The algorithm is based on Voellmy frictional (dry and turbulent frictional coefficients, μ and ξ respectively) parameters of debris flow with pre-defined release area identified on high-resolution satellite images like LISS-IV and Cartosat-1. The model provides critical quantitative information on flow 1) Velocity, 2) Height, 3) Momentum, and 4) Pressure along the entrainment path. The simulated velocity of about 16 m/s at mid-way the slide plummeted to 6.2 m/s at the base with intermittently increased and decreased values. The simulated maximum height was 3.9 m which gradually declined to 1.5 m near the bottom. The results can be beneficial in engineering intervention like the construction of check dams to digest the initial thrust of the flow and other remedial measures designed for vulnerable slope protection.

Advanced techniques using high resolution hyperspectral remote sensing data has recently evolved as an emerging tool with potential to aid mineral exploration. In this study, pertinently, five mosaicked scenes of Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral data of southeastern parts of the Aravalli Fold belt in Jahazpur area, Rajasthan, were processed. The exposed Proterozoic rocks in this area is of immense economic and scientific interest because of richness of poly-metallic mineral resources and their unique metallogenesis. Analysis of high resolution multispectral satellite image reveals that there are many prominent lineaments which acted as potential conduits of hydrothermal fluid emanation, some of which resulted in altering the country rock. This study takes cues from studying those altered minerals to enrich our knowledge base on mineralized zones. In this imaging spectroscopic study we have identified different hydrothermally altered minerals consisting of hydroxyl, carbonate and iron-bearing species. Spectral signatures (image based) of minerals such as Kaosmec, Talc, Kaolinite, Dolomite, and Montmorillonite were derived in SWIR (Short wave infrared) region while Iron bearing minerals such as Goethite and Limonite were identified in the VNIR (Visible and Near Infrared) region of electromagnetic spectrum. Validation of the target minerals was done by subsequent ground truthing and X-ray diffractogram (XRD) analysis. The altered end members were further mapped by Spectral Angle Mapper (SAM) and Adaptive Coherence Estimator (ACE) techniques to detect target minerals. Accuracy assessment was reported to be 86.82% and 77.75% for SAM and ACE respectively. This study confirms that the AVIRIS-NG hyperspectral data provides better solution for identification of endmember minerals.