Spectral mapping of savanna tree species at canopy level, with focus on tall trees, using an integrated CAO Hyperspectral & LiDAR sensor approach

Abstract

The detection and mapping of tree/plant species in the savanna ecosystem can provide numerous benefits for the managerial authorities. This includes the accurate mapping of the spatial distribution of economically viable trees which are a key source of food production and fuel wood for the local populace and communities. Economically viable tree species can thus be sustainably monitored while the pest species can be targeted and removed. The aim of this study was to identify spectrally and map 5 tall savanna tree species in the Greater Kruger National Park region using a decision tree approach. It was found that remote sensing is the best possible tool for discriminating and mapping the individual canopies of the different tree species of interest. The method proposed is in its prototype phase but its refinement and implementation over a larger sample of tree species is planned for the near future.