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. Ghebremicael School of Applied Environmental Sciences, Faculty of Science and Agriculture, South Africa , C.W. Smith , South Africa , F.B. Ahmed School of Applied Environmental Sciences, Faculty of Science and Agriculture, South Africa

Keywords: Remote sensing , Acacia mearnsii , Leaf area index , 3-PG , 3-PGS , process-based models

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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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