Biomass, harvestable area, and forest structure estimated from commercial timber inventories and remotely sensed imagery in southern Amazonia

The purpose of this study was to determine if spatially-explicit commercial timber inventories (CTI) could be used in conjunction with satellite imagery to improve timber assessments and forest biomass estimates in Amazonia. As part of a CTI, all commercial trees ≥45 cm DBH were measured and georeferenced in 3500 ha of a logging concession in NW Mato Grosso, Brazil. Using a stream network derived from the ASTER-based 30 m digital elevation model (DEM), a procedure was developed to predict areas excluded from logging based on reduced impact logging (RIL) criteria. Some timber species were associated with convergent landscape positions (i.e., higher TI values). There were significant differences in timber density and aboveground biomass (AGB) in upland (6.0 stems ha−1, 33 Mg ha−1) versus lowland (5.4 stems ha−1, 29 Mg ha−1) areas. Upland and lowland, and timber and non-timber areas could be distinguished through single and principal component analysis of LANDSAT bands. Assuming a 50 m stream buffer, areas protected from logging ranged from 7% (third order streams and above) to 28% (first order and above) of the total area. There was a strong positive relationship between AGB based on the scientific inventory of all trees and from the commercial timber, indicating that the CTI could be used in conjunction with limited additional sampling to predict total AGB (276 Mg ha−1). The methods developed in this study could be useful for facilitating commercial inventory practices, understanding the relationship of tree species distribution to landscape features, and improving the novel use of CTIs to estimate AGB.

Bibliographic Details

Main Authors:	66763 Feldpausch, Ted R. Cornell University. Department of Earth and Atmospheric Sciences, 92331 McDonald, Andrew J. (autor/a) Cornell University. Department orf Earth and Atmospheric Sciences, 103549 Passos, Carlos A.M. (autor/a) Universidade Federal de Mato Grosso. Departamento de Engenharia Florestal, 85865 Lehmann, Johannes (autor/a) Cornell University. Department of Crop and Soil Sciences, 110772 Riha, Susan J. (autor/a) Cornell University. Department of Earth and Atmospheric Sciences
Format:	Texto biblioteca
Language:	eng
Published:	Amsterdam Elsevier 2006
Subjects:	BIOMASA, BOSQUE NATIVO, MADERA, COMERCIALIZACION, INVENTARIOS FORESTALES, IMAGENES POR SATELITE, TELEDETECCION, ARBOLES MADERABLES, CORTA, DEFORESTACION, ALOMETRIA, MODELOS MATEMATICOS, BIOMASA AEREA, ECUACIONES ALOMETRICAS, TALA SELECTIVA, LANDSAT, ASTER, AMAZONIA, BIOMASS, PRIMARY FORESTS, WOOD, COMMERCIALIZATION, FOREST INVENTORIES, REMOTE SENSING, TIMBER TREES, DEFORESTATION, ALLOMETRY, MATHEMATICAL MODELS, SELECTIVE LOGGING, GIS,
Online Access:	http://orton.catie.ac.cr/repdoc/A11174i/8473A11174i.pdf
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