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Title: Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon
Authors: Bispo, Polyanna da Conceição
Dos Santos, João Roberto
Valeriano, Márcio de Morisson
Graça, Paulo Maurício Lima de Alencastro
Balzter, Heiko
França, Helena
Bispo, Pitágoras da Conceição
First Published: 18-Apr-2016
Publisher: Public Library of Science
Citation: PLoS One, 2016, 11 (4), pp. e0152009
Abstract: Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajós National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m²/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r² = 0.32 for CO, r² = 0.26 for H and r² = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty.
DOI Link: 10.1371/journal.pone.0152009
eISSN: 1932-6203
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright: © 2016 Bispo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Geography

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