Resumo

TORRES-ROJAS, Gustavo; ROMERO-SANCHEZ, Martín Enrique; VELASCO-BAUTISTA, Efraín  e  GONZALEZ-HERNANDEZ, Antonio. Forest parameter estimation in conifer forests using remote sensing techniques. Rev. mex. de cienc. forestales [online]. 2016, vol.7, n.36, pp.7-24. ISSN 2007-1132.

The main objective was to evaluate the capacity of two satellite platforms: SPOT and Quickbird® in order to estimate the forest parameters of interest in an area under management, located between the borders of the State of Mexico and Michoacán. The accuracy of the estimation was compared with field data. The estimated parameters were total height, normal diameter and aboveground carbon. Various vegetation indices were estimated and used as predictive variables, and Pearson’s (r) correlation test was utilized to determine the degree of association between the data obtained in field and the different variables derived from the satellite images. Response variables showing a high correlation with the predictive variable and a low correlation between each other were selected in order to estimate each of the parameters using regression models. These were validated using the root mean square error (RMSE) and the relative RMSE of the estimations against the data measured in field. The results showed significant negative correlations (SPOT = -0.60, -0.75; Quickbird = -0.58, -0.80). The regression analysis showed good adjustments in all cases (R2 = 0.59-0.91). For the validation of the models (RMSE), the lowest values in diameter and height -5.15 cm and 2.50 m, respectively- were obtained in the case of the SPOT 5 HRG image, while the lowest value in the Quickbird image was for aboveground carbon (0.77 Mg C).

Palavras-chave : Forest attributes; forest management; Quickbird; regression; remote sensing; SPOT.