Vegetation indices for the leaf area index estimation in clonal plantations of Eucalyptus saligna Smith

Abstract

The relationship between the ground Leaf area index (LAI_g) from clonal plantations of Eucalyptus saligna Smith and three different vegetation indices (VI): Normalized Difference Vegetation Index (NDVI), Simple Ratio Index (SRI) and Soil Adjusted Vegetation Index (SAVI) was evaluated in order to select the best IV to estimate the IAF by remote sensing (LAI_RS), and obtaining the spatial distribution of LAI in the stands. LAI_g was measured using LAI-2000 and its behavior was examined at different ages. The vegetation indices were obtained from a Landsat 8/OLI through the arithmetic of the bands 4 and 5. The linear regression analysis was used to adjust the model LAIRS (LAIRSi= β₀ + β₁ . IV_i + ε_i), and the criteria for selecting the best equation were the statistics R²_aj%, Syx% and residual analysis. The results showed that the best vegetation index to estimate IAF_SR was SRI (LAI_RS =-5.6159 + 0.9716 . SRI ), resulting R²_adj%=67.0 and S_yx=12.5%. The results of all adjusted models tended towards overestimation of LAI in values lower than two and underestimation in values above 3.5 (NDVI e SRI) and above three for SAVI. The equations for different ages produced no improvement in LAI_RS.

Keywords:
Regression analysis; Simple Ratio Index (SRI); LAI-2000; Landsat 8/OLI