Fire monitoring in savanna ecosystems using MODIS data: a case study of Kruger National Park, South Africa

Abstract

The heterogeneity of savanna ecosystems is guaranteed by disturbance events like fires, droughts, floods and browsing and grazing by herbivores. For conservation areas with limited space to preserve biodiversity, fire monitoring is crucial. Long periods of satellite remotely sensed data provide an alternative solution to estimate the distribution of different vegetation types and fire-affected patches over time. This study focusses on the application of MODIS data to detect, identify and delineate fire-affected areas in Kruger National Park (KNP), South Africa, for the period 2001–2003. Fire scars on KNP’s savanna were identified using threshold and supervised classification methods on moderate-resolution imaging spectroradiometer (MODIS) with 500-m resolution and 32-day global composites using a combination of band 1 (red), 2 (NIR, near infrared), 4 (green) and 6 (SWIR, short wave infrared). On identified fire scars, the spectral indexes of albedo, normalised difference infrared index (NDII) and normalised difference vegetation index (NDVI) were extracted. The following four broad habitat types were used for this analysis: riparian woodland, dense woodland, mixed woodland and open-tree savanna. The values of albedo, NDII and NDVI during the dry season (June to October) for different years are lower on fire-affected patches. Mixed woodland is the largest habitat burned with 21%, 43% and 2% of the KNP area affected by fire in 2001, 2002 and 2003, respectively. Riparian woodland is the least affected by fire. The supervised classification method has a greater accuracy for fire scars detection in KNP savannas during the dry season. We conclude that MODIS data can be used successfully for fire monitoring in savanna ecosystems.