Resumo

TORRES-VIVAR, Juan Esteban et al. Inventory and mapping of a pine forest under timber management using data obtained with a SPOT 6 sensor. Rev. mex. de cienc. forestales [online]. 2017, vol.8, n.39, pp.25-44. ISSN 2007-1132.

The purpose of the present research was to quantify and map the forest density, basal area (BA), total biomass (Bt), crown cover (CC), volume (Vol) and leaf area index (LAI) variables in a Pinus patula forest under timber management. Initially, the existing correlations between the spectral data derived from the SPOT-6 satellite sensor and field inventory data were identified. The analysis included the use of multiple linear regression models, ratio and regression estimators, and the traditional inventory approach (with field data only), for comparative purpose. The highest correlations for BA, Bt, CC and Vol were obtained using the near infrared strip; the values were 0.74, -0.77, -0.50 and -0.77, respectively, while the LAI had the highest correlation with the green strip, having a value of -0.65. The best adjustments were obtained for the regression models predicting the BA, Bt and Vol variables, a R2 adj of 0.66 for each variable, and mean square root error (MSRE) values of 5.82 m2 ha-1, 32 Mg ha-1 and 62.3 m3 ha-1 respectively. Inventory estimations were undertaken using the ratio and regression estimators’ method, being within the range of the confidence interval of the random sampling. The regression estimator registered the following precision values: 4.8 % (BA), 6.7 % (Bt), 5.8 % (CC), 6.6 % (Vol), 6.9 % (LAI). This type of sampling turned out to be the most conservative of all that were carried out.

Palavras-chave : Total biomass; leaf area index; forest inventory; spatial modeling; Pinus patula Schiede ex Schltdl. & Cham.; density variables.

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