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IDENTIFYING ACTIVE FIRE IN SOUTHWESTERN NIGERIA WITH MODIS DATA AND GEOGRAPHICAL INFORMATION SYSTEMS
Author(s) -
Ebenezer Yemi Ogunbadewa
Publication year - 2015
Publication title -
geodesy and cartography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 11
eISSN - 2029-6991
pISSN - 2029-7009
DOI - 10.3846/20296991.2015.1056502
Subject(s) - principal component analysis , geography , moderate resolution imaging spectroradiometer , swamp , environmental science , forest ecology , ecosystem , forestry , remote sensing , satellite , ecology , artificial intelligence , computer science , engineering , biology , aerospace engineering
The potentials of active fire product derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board of Terra and Aqua spacecrafts were examined for fire detection in a variety of ecosystems in the south western Nigeria. Fire information were obtained from the archived time series MODIS active fire datasets for 10 years (January 2002 to December 2011) and was superimposed on the map of ecosystem types (Intensively cultivated farmlands, woodlands, highland forest, freshwater swamp forest, tree crop plantation, forest plantation, mangrove forest and forest reserves) of the study area. MODIS active fire data were used to investigate the annual trends, geographical spread of fire occurrence and Principal Component Analysis (PCA) was used to identify the degree of fire events in each of ecosystems. The results show that MODIS active fire data imported into the Geographical Information Systems (GIS) data format and analyzed with PCA revealed that highland forest, forest plantation and intensively cultivated farmlands were heavily loaded on the first principal component and accounted for 87.56% variance in the original data. The second principal component accounting for 4.72% is heavily loaded with freshwater swamp forest, forest reserves and tree crop plantation while the regression coefficient of the component score matrix of the first principal component related to the original variables distinguished intensively cultivated farmlands and highland forest as the major source of ecosystems fire in the study area. It is concluded that MODIS active fire data together with PCA can provide a well coordinated near real time information that will be valuable for early warning, monitoring, mitigation and intervention against active fire disaster and catastrophic biomass burning plus a supportive guide for post fire assessment and recovery.

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