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Earth observation driven flood hazard and vulnerability assessment of industrial buildings in Assam using a probabilistic physics-based framework

Shemin T. John
July 8, 2026
Published Date

Research Abstract & Technology Focus

Rapid industrial expansion and increasing climate variability have intensified flood risks to industrial infrastructure across South and South-East Asia, necessitating integrated approaches that combine hazard characterization with vulnerability assessment. This study presents an earth observation driven flood hazard and vulnerability assessment framework for industrial warehouse buildings in Assam, India, by integrating geospatial flood hazard mapping with a probabilistic physics-based damage modelling approach. Flood hazard conditions are characterized using Sentinel-1 SAR–based inundation mapping, digital elevation data, and terrain and surface indicators including NDVI, NDWI, slope, elevation, and topographic position index to develop a normalized flood hazard index representing spatial flood susceptibility. The hazard information is subsequently coupled with a Monte Carlo–based vulnerability framework to evaluate flood-induced damage to fenestration components of a representative steel portal-frame industrial building under varying inundation depths, flow velocities, and flow directions, considering both hydrodynamic loading alone and combined hydrodynamic–hydrostatic loading conditions. Results indicate that hydrodynamic loading alone leads to gradual damage progression with maximum fenestration damage levels of approximately 63–76% even at 5.0 m inundation depth. The developed framework demonstrates how physics-based vulnerability modelling can be integrated with earth observation-driven flood risk evaluation for industrial infrastructure in flood-prone regions of South and South-East Asia.
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What is the core focus of the research titled 'Earth observation driven flood hazard and vulnerability assessment of industrial buildings in Assam using a probabilistic physics-based framework'?

This literature focuses on: Rapid industrial expansion and increasing climate variability have intensified flood risks to industrial infrastructure across South and South-East Asia, necessitating integrated approaches that combine hazard characterization with vulnerability a...

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Yes, highly correlated activity was mapped. An entry titled 'Comparative Analysis of Flood Estimation using Log-Pearson Type III and Gumbel Max Models in the Cauvery River, India' discusses this: Flooding is one of the most destructive global disasters in scale, geographical extent, property and life loss, and population displacement. The Ca...

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