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Eucalyptus Leaf Area Index Estimated by Vegetation Indices Using Landsat-5 TM Images

ABSTRACT

The objective of the present study was to fit regression models to the measured leaf area in eucalyptus forests and vegetation indices derived from Landsat-5 TM images. The study was carried out in commercial plantations located in the basin of the Doce River, Minas Gerais state, between 2008 and 2011. Leaf area was measured in the field, non-destructively, with the LAI-2000 device. The following indices were used: Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Simple Ratio (SR). The best model was adjusted from the NDVI, with a correlation coefficient of 0.73 and root mean square error of 0.37 m² m–2 (19%). We conclude that the leaf area index can be estimated by the regression models fit to the vegetation indices derived from the Landsat - 5 TM images.

Keywords:
remote sensing; statistics; planted forest

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