Operational wide-area stem volume estimation based on airborne laser scanning and national forest inventory data - Hollaus, Markus; Dorigo, W.; Wagner, W.; Schadauer, K.; Höfle, Bernhard; Maier, B. (International journal of remote sensing, 2009)
This paper evaluates the performance of a recently developed approach for wide-area stem volume estimations based on airborne laser scanning (ALS) and national forest inventory (NFI) data in the case where data recorded under operational conditions are used as input. This entails that neither ALS data nor NFI samples were collected and optimized for the current study. The approach was tested for the Austrian state of Vorarlberg, which covers an area of 2601 km2 and encloses about 970 km2 of forest land. ALS data with point densities varying between 1 and 4 points m−2 were acquired in the framework of a commercial state-wide terrain mapping project during several winter- and summer-flight campaigns. The stem volume model was calibrated with all NFI data available for Vorarlberg, whereas additional local forest inventory data were used for independent validation. Moreover, several relevant operational issues were addressed in this study, such as the determination of the optimum area used to calculate the reference laser metrics input to the model, the effect of gridding point cloud data to speed up processing, and the stratification of input data into coniferous and deciduous sample plots. Without tree species stratification and based on the 3D laser heights model, calibration provided a maximum R2 of 0.79 and a standard deviation (SD) of residuals derived from cross-validation of 107.4 m3 ha−1 (31.5%). Calibrating the model only with coniferous samples increased the achieved R2 to 0.81 and decreased SD to 104.8 m3 ha−1 (29.7%). As only eight NFI sample plots were available for deciduous forest a robust calibration of a separate model could not be obtained. Calibrating the model with a rasterized canopy height model (CHM) instead of using the 3D laser heights just led to a slight decrease in accuracy (R2 = 0.75, SD = 120.9 m3 ha−1 (35.5%) without forest-type stratification and R2 = 0.78 and SD = 117.2 m3 ha−1 (33.1%) for the coniferous stem volume model). Finally, the stem volume model calibrated with CHM data was adopted to generate a stem volume map of the entire State of Vorarlberg. Validation of this map with the additional local forest inventory data confirmed the accuracies (R2 = 0.75; SD = 135.6 m3 ha−1 (32.3%)) that were derived during calibration of the stem volume model based on the NFI data. The models and methods presented in this study are used operationally for forest and environment policy purposes and practical applications in Austria.