ABSTRACT
This study reports our attempt to tease up the drivers of wildland fire as well as wildland fire hotspots for the Zimbabwean component of the Kavango Zambezi Transfrontier Conservation Area (KAZA-TFCA). We used the Getis-Ord (Gi*) to identify wildland fire hotspots as well as MaxEnt to identify the drivers of the wildland fire in the KAZA-TFCA. The MaxEnt model used presence-only data of wildland fires from the Fire Information for Resource Management System (FIRMS) against four environmental variables i.e. air temperature, elevation, human footprint represented by human population density and vegetation condition represented by Normalized Difference Vegetation Index (NDVI). Our MaxEnt model was successful (AUC = 0.78) in predicting wildland fires in the study area. Mean air temperature had the highest contribution to the model (61.3%) followed by elevation (26.3%), human population density (9.8%) and NDVI (2.5%). The overall spatial model showed that the north east as well as areas within 1 km from park boundaries were more susceptible to wildland fires than their surroundings. Getis-Ord (Gi*) analysis showed that fire hotspots occur in northeast, adjacent but outside Hwange National Park and, the entire Chizarira and Matusadona National Parks. These results provide baseline information for wildland fire management in the KAZA-TFCA.
Geo-location information
The study was conducted for the Zimbabwean Component of the Kavango-Zambezi Transfrontier Conservation Area (KAZA TFCA).
Author Contribution
KM and THM conceptualized the study. KM and HN helped with data processing and modelling. KM and PT helped in the writing of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.