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Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data

Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data

John Isaac Molefe
Copyright: © 2019 |Pages: 15
ISBN13: 9781522580546|ISBN10: 1522580549|EISBN13: 9781522580553
DOI: 10.4018/978-1-5225-8054-6.ch043
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MLA

Molefe, John Isaac. "Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data." Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 1034-1048. https://doi.org/10.4018/978-1-5225-8054-6.ch043

APA

Molefe, J. I. (2019). Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data. In I. Management Association (Ed.), Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications (pp. 1034-1048). IGI Global. https://doi.org/10.4018/978-1-5225-8054-6.ch043

Chicago

Molefe, John Isaac. "Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data." In Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1034-1048. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8054-6.ch043

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Abstract

Despite its role and relevance in environmental management at all scales the use of fire has been contentious. The absence of information on fire parameters compounds the situation. This study derives fire parameter information for Botswana by analyzing MODIS fire data for (2001-2012), using conditional statements, and cluster mapping in ArcGIS. The study also related the fire information to other variables to examine how they interact with fire. The results of the study indicates that over the 12 year period the burned area has exhibited an upward trend. It has also shown that most of the fire in the country occur over the late dry season when the fires are potentially destructive. A south-north transect of fire frequency is observed, accompanied by an inverse relationship between frequency and intensity. Of all the factors, rainfall (0.638) and biomass(NDVI) (0.355) were the most significant contributors to the fire activity. The study demonstrated the utility of the MODIS fire data in characterizing the fire regime of the country and thus contribute to the policy process.

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