Geo-Spatial Data Analysis for Disaster Impact Forecasting

Author(s)	Mr. Rupesh Shesherao Waghmare, Dr. B. A. Sonkamble
Country	India
Abstract	This paper explores the application of geo-spatial data analysis in forecasting the impact of natural disasters, focusing on floods and earthquakes. By integrating satellite imagery, geographic information systems (GIS), and machine learning models, the study proposes a framework for predicting disaster-affected areas and estimating potential damages. The methodology leverages high-resolution spatial data and temporal analysis to enhance preparedness and mitigation strategies. A case study on flood forecasting in a hypothetical urban region demonstrates the model accuracy, achieving an F1-score of 0.85. The findings underscore the importance of geo-spatial technologies in disaster management, offering actionable insights for policymakers and emergency responders.
Keywords	Geo-Spatial Data, Disaster Forecasting, Machine Learning, GIS, Satellite Imagery, Flood Prediction, Earthquake Impact, Spatial Analysis.
Field	Engineering
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-19
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.44274

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