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Proceedings Paper

Estimating biophysical properties of eucalyptus plantations using optical remote sensing techniques
Author(s): Joao Vianei Soares; Alexandre Candido Xavier; Auro Campi de Almeida; Corina da Costa Freitas
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Paper Abstract

The feasibility of the inversion of optical remote sensing products to measure critical biophysical properties of Eucalyptus Forests at regional scales is investigated here. The biophysical variables used were leaf area Index, LAI, Diameter at Breast Height, DBH, Height and Age of Eucalyptus stands pertaining to a combination of different genetic materials (E. urophylla x E. grandis hybrids) and propagating systems (seeds or cuttings) and management system (planting and coppicing). The field sampling was done daily during 3 months, from April to June 1997, and covered 130 stands of minimum sizes of 9 hectares, within an Eucalyptus farming area of about 800 km2, centered at 19 degrees South, 42 degrees West, Brazil. The stands ranged from 12 to 84 months old. The measurements of LAI were done using two pairs of LAI-2000 (LICOR) under conditions of diffuse light. The Normalized Difference Vegetation Index, NDVI, and the Soil Adjusted Vegetation Index, SAVI, were derived from a LANDSAT-TM image acquired on June 5, 1997. Furthermore, a mixture model technique was applied to derive three new parameters: fraction of green vegetation, FGV, fraction of shadow, FSH, and fraction of soil, FS. Regression analysis were done between biophysical variables and remote sensing products. Linear correlation with coefficients of determination, R2, as high as 0.8 were found between LAI versus FGV and LAI versus SAVI, on all genetic materials. In general, SAVI was shown to give better estimates of LAI than NDVI, which is explained by the openings in the canopy as the Eucalyptus grow older. The correlation with the other biophysical variables (Height and DBH) were also shown to be significant, although the R2 ranged from 0.4 to 0.6. The correlation between FGV and SAVI was higher than 90% such that they can be used to estimate Eucalyptus biophysical parameters with the same statistical significance.

Paper Details

Date Published: 11 December 1998
PDF: 10 pages
Proc. SPIE 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology, (11 December 1998); doi: 10.1117/12.332752
Show Author Affiliations
Joao Vianei Soares, Instituto Nacional de Pesquisas Espaciais (Brazil)
Alexandre Candido Xavier, Instituto Nacional de Pesquisas Espaciais (Brazil)
Auro Campi de Almeida, Aracruz Celulose SA (Brazil)
Corina da Costa Freitas, Instituto Nacional de Pesquisas Espaciais (Brazil)

Published in SPIE Proceedings Vol. 3499:
Remote Sensing for Agriculture, Ecosystems, and Hydrology
Edwin T. Engman, Editor(s)

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