Scientific Paper

Estimating the leaf area index (LAI) of black wattle from Landsat ETM+ satellite imagery

Published in: The Southern African Forestry Journal
Volume 201, issue 1, 2004, pages: 3–12
DOI: 10.1080/20702620.2004.10431769
Author(s): S.T. GhebremicaelSchool of Applied Environmental Sciences, Faculty of Science and Agriculture, South Africa, C.W. Smith, South Africa, F.B. AhmedSchool of Applied Environmental Sciences, Faculty of Science and Agriculture, South Africa

Abstract

Remote sensing techniques have the potential to provide resource managers with a rapid and economical method of acquiring information related to forest productivity and water use. This study evaluated the utility ofLandsat ETM +satellite imagery to predict canopy attributes ofBlack Wattle (Acacia mearnsii). The study encompassed ground-based measurements ofleaf area index (LAI) and plant area index (PAl) using destructive sampling and LI-COR LAI-2000 plant canopy analyzer, respectively. Vegetation indices (VIs) were estimated from Landsat ETM +images covering four study sites of pure stands of A. mearnsii located in the KwaZulu-Natal Midlands. The indices included: normalized difference vegetation index (NDVI), ratio vegetation index (RVI), transformed vegetation index (TVI) and vegetation index 3 (VI3). Relationships between the various vegetation indices, SLA, actual LAI and PAl values were tested using correlation and regression analyses.

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