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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3291

Title: Species discrimination of African savannah trees at leaf level using hyperspectral remote sensing
Authors: Majeke, B
Cho, MA
Debba, P
Mathieu, R
Ramoelo, A
Keywords: Hyperspectral
Remote sensing
Kruger National Park
African savannah
Species discrimination
Hyperspectral remote sensing
6th EARSeL SIG IS Workshop
Issue Date: Mar-2009
Citation: Majeke, B, Cho, MA, Debba, P, Mathieu, R and Ramoelo, A. 2008. Species discrimination of African savannah trees at leaf level using hyperspectral remote sensing. 6th EARSeL SIG IS Workshop, Tel Aviv University, Tel Aviv, Israel; March 16-19, 2009, pp 1
Abstract: The management of the Kruger National Park, South Africa has expressed the need to find cost-effective and rapid means to assess species diversity in the park. Remote sensing is viewed as a cost-effective alternative to intensive field sampling. This study was carried out to assess the utility of hyperspectral remote sensing in discriminating the dominant species in the southern part of the park. The spectral reflectances of seven common tree species (Combretum apiculatum, Combretum hereroense, Combretum zeyheri, Gymnosporia buxifolia, Gymnosporia senegalenses, Lonchocarpus capassa, Terminalia sericea) were measured using the ASD spectrometer (Analytical Spectral Radiometer (ASD) (350-2500 nm)). Ten (10) leaf reflectances were collected for each tree species. Four different similarity measures, namely, spectral correlation measure (SCM), spectral angle mapper (SAM), Spectral information divergence (SID) and a combination of SAM and SID (with either sin or tan) were used to measure the similarities amongst species. Two statistical approaches were used to determine the performance of the various similarity measures, namely, relative spectral discriminatory probability (RSDPB) and relative spectral discriminatory power (RSDPW). These similarity and discriminability measures were applied to the whole spectrum, visible range, near infrared (NIR) range and short wave infra red (SWIR) range to determine which method show great similarities/ dissimilarities amongst species and in which range
Description: 6th EARSeL SIG IS Workshop, Tel Aviv University, Tel Aviv, Israel; March 16-19, 2009
URI: http://hdl.handle.net/10204/3291
Appears in Collections:Environmental and resource economics
Logistics and quantitative methods
General science, engineering & technology

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