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The 2013-2014 vegetation structure map of Hwange National Park, Zimbabwe, produced using free satellite images and software

Arraut E.M., Loveridge A.J., Chamaille-Jammes S., Valls-Fox H., Macdonald D.W.. 2018. Koedoe, 60 (1) : 10 p..

DOI: 10.4102/koedoe.v60i1.1497

Vegetation mapping of protected areas is a cornerstone of conservation worldwide. Established in 1928 and covering over 1.4 million hectares, Hwange National Park (HNP) is the largest natural reserve in Zimbabwe. In 1993, the sole comprehensive map of its vegetation to date was produced and since then it has been used in numerous research and conservation endeavours. Over the last two decades, however, the park's vegetation changed, safari areas and forest reserves were created at its edge and high-positional accuracy data on a suite of species were collected. To tend to contemporary mapping needs, in this article, we present the 2013–2014 vegetation structure map of HNP and its surroundings. It was produced by supervised classification of Landsat-8 Operational Land Imager (OLI) images, indices derived from these and the Landsat Tree Cover Continuous Field product. Its accuracy was assessed statistically using samples collected from high-resolution satellite imagery and basic ancillary field data. Of its total pixels, 83.2% were correctly classified. Mean omission and commission error were, respectively, 0.82 (0.74–0.90) and 0.82 (0.72–0.89), and this similarity held on a per class basis, indicating reliable area estimates. It was produced using only freely available imagery and software. Conservation implications: In addition to providing researchers and conservationists working within and around HNP with an updated vegetation map, aiming at an even broader audience, we provide a step-by-step approach for using modern freely available imagery and software for cost-effectively mapping HNP in future or other protected savannas across Africa.

Mots-clés : parc national; indice de végétation; biodiversité; gestion de la faune et de la flore sauvages; télédétection; imagerie; écologie; logiciel; cartographie des fonctions de la forêt; zimbabwe

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