Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/5621
Title: Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data
Authors: Pedzisai Kowe
Upenyu Naume Mupfiga
Onisimo Mutanga
Timothy Dube
Department of Geography, Environmental Sustainability and Resilience Building, Midlands State University, Gweru 9055, Zimbabwe
Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa
Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa
nstitute of Water Studies, Department of Earth Sciences, The University of the Western Cape, Private Bag X17, Bellville 7535, South Africa
Keywords: active fire occurrence
fire intensity
fire radiative power
spatial clustering
hot spots
cold spots
spatial data
climate change
Issue Date: 25-Nov-2022
Publisher: Multidisciplinary Digital Publishing Institute
Abstract: This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire occurrence data. In order to investigate the spatial pattern of fire intensity, MODIS-derived fire radiative power (FRP) was utilized. A local indicator of spatial autocorrelation method, the Getis-Ord (Gi*) spatial statistic, was applied to show the spatial distribution of high and low fire intensity clusters. Analysis of the relationship between topographic variables, vegetation type, agroecological zones and fire intensity was done. According to the study’s findings, the majority (44%) of active fires detected in the study area in 2019 were of low-intensity (cold spots), and the majority (49.3%) of them occurred in shrubland. High-intensity fires (22%) primarily occurred in the study area’s eastern and western regions. The study findings demonstrate the utility of spatial statistics methods in conjunction with satellite fire data in detecting clusters of high and low-intensity fires (hot spots and cold spots).
URI: https://cris.library.msu.ac.zw//handle/11408/5621
Appears in Collections:Research Papers

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