Koedoe: African Protected Area Conservation and Science (Dec 2021)

The first sub-meter resolution digital elevation model of the Kruger National Park, South Africa

  • Kai Heckel,
  • Marcel Urban,
  • Jean-Sébastien Bouffard,
  • Jussi Baade,
  • Peter Boucher,
  • Andrew Davies,
  • Evan G. Hockridge,
  • Wolfgang Lück,
  • Jonas Ziemer,
  • Izak Smit,
  • Bernhard Jacobs,
  • Mark Norris-Rogers,
  • Christiane Schmullius

DOI
https://doi.org/10.4102/koedoe.v63i1.1679
Journal volume & issue
Vol. 63, no. 1
pp. e1 – e13

Abstract

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The use of digital elevation models has proven to be crucial in numerous studies related to savanna ecosystem research. However, the insufficient spatial resolution of the chosen input data is often considered to be a limiting factor when conducting local to regional scale ecosystem analysis. The elevation models and orthorectified imagery created in this study represent the first wall-to-wall digital elevation data sets produced for the Kruger National Park (KNP), South Africa, at very high spatial resolution. Using colour-infrared (CIR) aerial imagery from the archives of the Chief Directorate: National Geo-spatial Information (CDNGI), Department of Agriculture, Land Reform and Rural Development (DALRRD) aerial acquisition programme, we created digital surface models (DSMs), digital terrain models (DTMs) and CIR orthomosaics covering the entire KNP with a nominal ground sampling distance of 0.25 m. Elevation information was derived using state-of-the-art stereo matching algorithms that utilised semi-global matching (SGM) as a cost aggregation function throughout the image pairing, using the Enterprise software from CATALYST. The final products were validated against reference products, and showed excellent agreement with R² values of 0.99. Further, the validation of the DTM and DSM revealed median absolute vertical height error (LE90) across all sites of 1.02 m and 2.58 m, respectively. The orthomosaics were validated with in situ ground control points (GCPs) exhibiting a horizontal Circular Probable Error (CPE) of 1.37 m. The data resulting from this work will be distributed freely with the aim of fostering more scientific studies in the African science community and beyond. Conservation implications: Accurate information about terrain and surface height are crucial inputs to a variety of scientific analysis, which are essential in protected areas, such as flood prediction or fire hazard estimation. Elevation data sets and orthomosaics in very high resolution can therefore serve as a crucial tool to improve park management and foster positive implications on conservation efforts.

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