Deforestation(Fire Classification)

This project focuses on classifying different types of fire events in India using MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data from 2021 to 2023 through machine learning techniques. The objective is to accurately detect and differentiate between forest fires, agricultural burning, volcanic activity, static land sources, and offshore thermal anomalies based on satellite-derived parameters like brightness temperature, fire radiative power (FRP), and confidence levels. The workflow involves preprocessing and merging MODIS datasets, selecting important features using statistical tests and ensemble methods, and building classification models such as Logistic Regression, K-Nearest Neighbors (KNN), Random Forest, and XGBoost. The trained models are evaluated using accuracy scores, classification reports, and confusion matrices to assess their effectiveness in predicting fire types. This project aims to support disaster response, environmental monitoring, and resource management efforts by providing a scalable solution for automated fire classification, with future scope for real-time data integration and advanced geospatial visualizations.