Authors - A. Viji Amutha Mary, Ram Swagath B, Ruthresh E, S Jancy, B. Shamreen Ahamed Abstract - As one of the most damaging natural risks, earthquakes require quick situational consciousness for emergency response as well as control. Usual impact assessment methods use larger on field surveys conducted after a disaster, which delays decision making and results in a poor comprehension of damaged zones. An automated analysis pipeline processes high resolution imagery from satellites and land based seismic data to extract land use change patterns, information on terrain change in shape and signs of structural damage. An XGBoost model is then used to classify the extracted spatial features, estimate severe levels and produce dynamic earthquake risk maps. During seismic emergencies, the system supports resource distribution and rescue planning by enabling quicker and more accurate estimation of open areas. The suggested hybrid model greatly outperforms traditional disaster assessment techniques in terms of accuracy, processing speed or scalability, according to experimental evaluation, underscoring its potential to transform preventive earthquake disaster management as well as prepare strategies.
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