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Fig 1.

Location of Zimbabwe (c) the study area. The top insert (a) shows the location of Zimbabwe in Africa, and the bottom insert (b) shows the neighbouring countries of Zimbabwe in Southern Africa. (Shapefile data source: Department of Geography Geospatial Sciences and Earth Observation, University of Zimbabwe, 2022).

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Fig 2.

The 2020 European Space Agency (ESA) land cover data developed from Sentinel-2 imagery for Zimbabwe.

(Data source: ESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf).

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Table 1.

Reclassification of the ESA vegetation classes into classes used in this paper.

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Table 2.

General Description of the different vegetation types in Zimbabwe.

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Table 3.

Variables used in for determining key climatic drivers of wildfire in different vegetation types.

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Fig 3.

Temporal changes in burned areas across Zimbabwe from the year 2001 to 2020.

A positive trend in burned area is observed from 2001 up to 2011 while a negative trend is observed thereafter.

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Fig 4.

Notable decrease in burned areas in Zimbabwe between the decades 2001–2010 and 2011 to 2021.

(Data source: Roteta, E., et al. (2019) Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa. https://doi.org/10.1016/j.rse.2018.12.011).

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Fig 5.

Monthly changes in average burned area in Zimbabwe between 2001 and 2020 to show the peak and low periods of fire extent.

(Data source: European Space Agency MODIS fire product).

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Fig 6.

Spatial and temporal variation in wildfire frequency from January 2001 to December 2020.

(Data source: Roteta, E., et al. (2019) Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa. https://doi.org/10.1016/j.rse.2018.12.011).

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Fig 7.

Districts in Zimbabwe affected by fires (every year for at 10-year period or more—in red) from 2001 to 2020.

(Data source: Roteta, E., et al. (2019) Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa. https://doi.org/10.1016/j.rse.2018.12.011).

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Table 4.

Vegetation classes, total area occupied and the respective fire frequency within each vegetation type.

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Table 5.

Percentage of area versus fire frequency from 2001 to 2020 in Zimbabwe.

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Table 6.

Climatic variables explaining variations in burned area with variables in bold being significant.

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Fig 8.

Relationship between mean annual rainfall over the preceding four years and total burned area across Zimbabwe between 2001 and 2020.

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