Predicting forest structural attributes using ancillary data and ASTER satellite data

This study assessed the suitability of both visible and shortwave infrared ASTER data and vegetation indices for estimating forest structural attributes of Eucalyptus species in the southern KwaZulu Natal, South Africa. The empirical relationships between forest structural attributes and ASTER data were derived using stepwise multiple regression analysis; Modified Soil Adjusted Vegetation Index (MSVI) and band 3 were selected for analysis as it showed best relationships with forest structural attributes. The ancillary data such as age and site index were also included in the analysis. Although the results of this study have indicated statistically significant relationships between the forest structural attributes and the ASTER data in the plantation forests stands with adjusted R-values for volume, basal area (BA), stem per hectare (SPHA), and tree height of 0.51, 0.67, 0.65, and 0.52, respectively, but these results are not suitable for operational purpose in a forest company. However, the structural forest attribute predictions were markedly improved after incorporating age and site index as predictor variable. Rvalues for the stands increased by 42%, 20.2%, 16.8%, and 42.2% for volume, basal area, SPHA, and tree height, respectively. These results imply that ASTER satellite data alone are not applicable to forest structural attribute estimation; however, ASTER data can provide useful information if it is used in conjunction with age and site index data for forest structural attribute estimation in plantation forests. 2009 Elsevier B.V. All rights reserved. * Corresponding author at: University of KwaZulu Natal, School of Environmental Sciences, King George V Avenue, Glenwood, Durban 4041, South Africa. Tel.: +27 72 744 9253; fax: +27 31 261 1216. E-mail address: [email protected] (M.T. Gebreslasie).