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Abstract
ABSTRACT This study aimed to increase satellite-derived Normalized Difference Vegetation Index (NDVI) sensitivity to biophysical parameters changes with aid of a forest age-based adjustment factor. This factor is defined as a ratio between stand age and age of rotation, which value multiplied by Landsat-5/TM-derived NDVI generated the so-called adjusted index NDVI_a. Soil Adjusted Vegetation Index (SAVI) was also calculated. The relationship between these vegetation indices (VI) with Eucalyptus and Pinus stands’ wood volume was investigated. The adjustment factor caused an increase in NDVI dynamic range values, since older stands tended to be assigned with highest NDVI values, while younger ones tended to be forced to assume lower NDVI values. As a result, direct and significant relationship between NDVI_a and wood volume could be maintained for wider ranges of wood volume. However, it was observed that NDVI_a was only statistically superior to NDVI and SAVI when a detailed age dataset is available. It is conclude that, the stand age has potential to improve NDVI sensitivity to biophysical parameters allowing that quantitative estimates could be made since young to adult stands.
Highlights
Planted forests represent the main wood supply source for production chains of important industries such as pulp and paper, reconstituted panels, furniture, charcoal metallurgy, energy and solid wood products (Câmara Setorial de Silvicultura, 2009), which boost the generation of goods, taxes, employment and incomes (Abraf, 2011), reducing pressure over native forest remaining (Rezende et al, 2013)
This study aimed to increase satellite-derived Normalized Difference Vegetation Index (NDVI) sensitivity to biophysical parameters changes with aid of a forest age-based adjustment factor. This factor is defined as a ratio between stand age and age of rotation, which value multiplied by Landsat-5/TM-derived NDVI generated the so-called adjusted index NDVI_a
The analysis of biophysical variables against spectral ones starts with pairs of data coming from NDVI and Pinus wood volume, Figure 2a
Summary
Planted forests represent the main wood supply source for production chains of important industries such as pulp and paper, reconstituted panels, furniture, charcoal metallurgy, energy and solid wood products (Câmara Setorial de Silvicultura, 2009), which boost the generation of goods, taxes, employment and incomes (Abraf, 2011), reducing pressure over native forest remaining (Rezende et al, 2013) All these benefits rely upon a well-managed plantation capable of producing high quality trees at the end of rotation. Quantitative assessment of vegetation using remote sensing techniques has been commonly done through the use of the so-called vegetation indices (VIs) (Ponzoni and Shimabukuro, 1998) Their performances have constraints and many efforts have been done in developing new VIs aiming to optimize them for applications such as vegetation monitoring and biophysical parameters estimates (Huete et al, 2002)
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