Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system

Moses Azong Cho, Renaud Mathieu, Gregory P. Asner, Laven Naidoo, Jan van Aardt, Abel Ramoelo, Pravesh Debba, Konrad Wessels, Russell Main, Izak P.J. Smit, Barend Erasmus

Research output: Contribution to journalArticlepeer-review

139 Scopus citations

Abstract

Mapping savanna tree species is of broad interest for savanna ecology and rural resource inventory. We investigated the utility of (i) the Carnegie Airborne Observatory (CAO) hyperspectral data, and WorldView-2 and Quickbird multispectral spectral data and (ii) a combined spectral. +. tree height dataset (derived from the CAO LiDAR system) for mapping seven common savanna tree species or genera in the Sabi Sands Reserve and communal lands adjacent to Kruger National Park, South Africa. We convolved the 72 spectral bands of the CAO imagery to eight and four multispectral channels available in the WorldView-2 and Quickbird satellite sensors, respectively. A combination of the simulated WorldView-2 data and LiDAR tree height imagery was also assessed for species classification. First, the simulated WorldView-2 imagery provided a higher classification accuracy (77% ± 3.1 (mean ± standard deviation)) when compared to the simulated Quickbird (65% ± 1.9) and CAO (65% ± 1.2) data. Secondly, the combined spectral. +. height dataset provided a slightly higher overall classification accuracy (79% ± 1.8) when compared to the WorldView-2 spectral only dataset. The difference was however, statistically significant (p<0.001; one-way analysis of variance for 30 bootstrapped replicates (n=100) of the independent validation dataset). Higher classification accuracies were observed for trees with large crowns such as S. birrea, S. africana and A. nigrescens as compared to trees with small crowns. Species composition and diversity maps of trees with large crowns were consistent with established knowledge in the area. For example, the results showed higher tree diversity (number of different species per ha) in the Sabi Sands game reserve than in the communal areas. This study highlights the feasibility of remote sensing of tree species at the landscape scale in African savannas and the potential applicability of WorldView-2 sensor in mapping savanna tree species with a large crown.

Original languageEnglish (US)
Pages (from-to)214-226
Number of pages13
JournalRemote Sensing of Environment
Volume125
DOIs
StatePublished - Oct 2012
Externally publishedYes

Keywords

  • Carnegie Airborne Observatory
  • Hyperspectral remote sensing
  • Land use
  • LiDAR WorldView-2
  • Savanna tree species

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

Fingerprint

Dive into the research topics of 'Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system'. Together they form a unique fingerprint.

Cite this