Improving Fire Risk Estimation through Investigating Fire Intensity, Moisture and Temperature Anomalies

The accuracy of FDI's are largely dependent on their input variables and advancements in remote sensing are yet to be utilized to improve accuracy and scalability. This study aims to address this through the use of remotely sensed data of soil moisutre, fire radiative power, temperature and precipitation. In doing so, combining risk with likely fire intensity.