Satellite Data-Based Logistic Regression and Neural Network Modeling for Wildfire Prediction

As the frequency and severity of wildfires continue to increase worldwide, the need for rapid and reliable wildfire detection and prediction technologies has become increasingly crucial. In this study, satellite data were utilized to predict wildfire occurrences, and the predictive performances of logistic regression and artificial neural network models were compared and analyzed. Land surface temperature (LST), normalized difference vegetation index (NDVI), and thermal anomalies (TA) were selec