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Remote sensing has been widely used in active forest fire detection; however there are some limitations in the operational contextual algorithms.
These algorithms are greatly affected by clouds and different land cover types such as land and water with inherent temperatures.
This book, therefore, provides a new multi-temporal threshold algorithm for near real-time forest fire detection using geostationary satellites, supplemental to the existing algorithms.
This algorithm is based on temperature in IR3.9 channel and the difference between IR3.9 and IR10.8 channels.
The multi-temporal threshold algorithm proved to have higher fire detection rate (50%) as compared to MSG FIR-G (3.7%) when ground data from Portugal was used for validation.
This superiority was also confirmed over Southern Africa when MODIS fire product was used for validation.
This analysis shows the possibility of manipulating the temporal domain of geostationary satellites in monitoring highly temporal environmental phenomenon.
This algorithm could be especially useful to professionals in forest fire management, or anyone else who may be interested in applying geostationary satellites in environmental monitoring.
Tawanda Manyangadze, MSc: Studied a Master of Science degree in Geo-Information Science and Earth Observation for Environmental Modelling and Management at University of Southampton, ITC, Lund University, and Warsaw University.
Researcher/Consultant in the Department of Sustainable Environment & Development (DSED) at Saveteck Solutions., Zimbabwe.
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