“Forest fires have the potential to increase the amount of carbon in the atmosphere which is one of the greenhouse gases responsible for global warming. Climate change may also lead to increased outbreak of forest fires due to increased dryness conditions especially in tropical Africa. This indicates the need for improved methods for detection, monitoring and management of forest fires so as to protect the fragile ecosystems. Remote sensing has been widely used in active forest fire detection; however there are some limitations in operational
contextual algorithms as they are greatly affected by clouds and different land cover types such as land and water with inherent temperatures that may be included in the 3 x 3 kernel or matrix used in estimating the possibility of fire in the centre pixel. Therefore this working paper
evaluates the accuracy of the multi-temporal threshold algorithm in Zimbabwe based on the hypothesis that both multi-temporal threshold algorithm and contextual algorithm (MSG fire product) have equal performance on forest fire detection.”
