Comparison of Satellite Platform for Mapping the Distribution of Mauritius Thorn (<i>Caesalpinia decapetala</i>) and River Red Gum (<i>Eucalyptus camaldulensis</i>) in the Vhembe Biosphere Reserve

Abstract

Mapping and tracking invasive alien plant species (IAPS) and their invasiveness can be achieved using remote sensing (RS) and geographic information systems (GIS). Continuous monitoring using RS, GIS and modelling are fundamental tools for informing invasion and management strategies. Using systematic comparisons, we look at three remote sensing imagery platforms and how accurately they can be classified within the Vhembe biosphere reserve, Limpopo Province, South Africa. Supervised classification of National Geospatial Information Colour Digital Aerial Imagery, DigitalGlobe Worldview 2 and CNES SPOT 6 was performed. The Spectral Angle Mapper (SAM) algorithm was used to identify the best satellite for species-level classification. The accuracy of the classifications produced an overall accuracy (OA) of 71% with a Kappa coefficient (KC) of 0.76 for CDA photographs, an OA of 81% and a KC of 0.80 for Worldview 2, and an OA of 89% with a KC of 0.86 for SPOT 6 imagery. Therefore, SPOT 6 imagery came out as the most suitable for species-level classification. The classification results from the SPOT 6 imagery were used as input data for further species distribution modelling of Mauritius Thorn and River Red Gum in the VBR.

Keywords

• classification
• remote sensing
• GIS
• producer accuracy
• user accuracy
• overall accuracy