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Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon.

Bispo Pda C, Dos Santos JR, Valeriano Mde M, Graça PM, Balzter H, França H, Bispo Pda C - PLoS ONE (2016)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Ciência e Tecnologia Ambiental, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil.

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.

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Maps of estimated BA and CO for Tapajós National Forest.
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pone.0152009.g003: Maps of estimated BA and CO for Tapajós National Forest.

Mentions: Model validation with 9 independent sample plots showed an RMSE of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO relative to the average values. The coefficients of determination from the analyses between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. Because the coefficient of determination of the modelled H with 30 samples was low and that one generated with the independent observations to this structural variable was not significant, we considered the obtained model inadequate for estimation of this variable. Following validation, the models for BA and CO were applied, and maps for these two variables were generated for TNF (Fig 3).


Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon.

Bispo Pda C, Dos Santos JR, Valeriano Mde M, Graça PM, Balzter H, França H, Bispo Pda C - PLoS ONE (2016)

Maps of estimated BA and CO for Tapajós National Forest.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835096&req=5

pone.0152009.g003: Maps of estimated BA and CO for Tapajós National Forest.
Mentions: Model validation with 9 independent sample plots showed an RMSE of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO relative to the average values. The coefficients of determination from the analyses between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. Because the coefficient of determination of the modelled H with 30 samples was low and that one generated with the independent observations to this structural variable was not significant, we considered the obtained model inadequate for estimation of this variable. Following validation, the models for BA and CO were applied, and maps for these two variables were generated for TNF (Fig 3).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Ciência e Tecnologia Ambiental, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil.

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.

Show MeSH
Related in: MedlinePlus