Evaluating the effects of leaf characteristics on spectral signatures of savannah woody species on remotely sensed imagery

Abstract

Woody species on savannahs provide nutrition to wildlife and livestock ungulates. Understanding of leaf reflectance would benefit the application of remote sensing in analysis of these rangelands. This study sought to establish the influence of the leaf characteristics of size (leaf form) and chlorophyll content on the spectral reflectance characteristics of a sample of savannah woody species is investigated, and the applicability of these leaf characteristics in the context of abilities to remotely sense the state of the woody species using optical remotely sensed imagery. Two species that represented narrow leaf and broad leaf savannah woody species we studied: Acacia tortilis and Ziziphus mucronata, respectively. Forty seven woody individuals representing these species were sampled in northwestern South Africa. Chlorophyll content, leaf area index (LAI) and spectral reflectance were determined in the field using a chlorophyll metre, a canopy analyser and spectroradiometer, respectively. A SPOT 6 NAOMI image acquired at a time of year when grass reflectance was excluded from the spectral signature of non-senescent vegetation was used. The image data were converted to reflectance (%), and the reflectance of the field-sampled trees correlated with the in-situ data. The results showed that the woody species differed significantly in their chlorophyll content and green reflectance, but only the NIR reflectance broad leaf species correlated strongly with a leaf characteristic, LAI. From the results it can be concluded that leaf area index (LAI) is the more reliable leaf characteristic for analysing the characteristics of savannahs in terms of leaf content.