Moreover, new high-ALS spatial and spectral resolution sensors, algorithms, and computing capacity permit the coverage of large areas, providing accurate information concerning dasometric variables. ALS technology is being used at different scales, and there have been studies at individual tree, plot, or stand levels allowing forest inventories and monitoring at different spatial resolutions. Detailed three-dimensional information regarding the structure of forests is especially useful for forest management inventories (e.g., mean tree height, basal area, and stem volume), logistics of forest planning, forest fire prevention, structural monitoring, or forest health, among others. ALS technology has been fully validated as a more accurate and less expensive alternative to classic forest inventory. In this respect, remote sensing, which is carried out by freely accessing different spatial and temporal resolution satellite images, along with airborne laser scanning (ALS) technology, is leading to a change in forest inventory. Three-dimensional (3D) data obtained from remote sensing in the forestry sector is already a reality that is gradually replacing the traditional tools used in forest inventory. Hence, field efforts can be greatly decreased while achieving better prediction accuracies. Our results showed that the precision of forest inventories based on ALS data can be adjusted depending on tree density to optimize the selected approach (ABA and ITC), thus reducing the inventory costs. At high densities, ABA performed better for all the attributes except for height (6.5% MAPE in N, 8.7% in G, and 8.9% in V). There was no significant difference in precision regarding the volume and basal area (G) estimations at medium densities, although ITC obtained better results for density and dominant height (Ho). The ITC models performed better than the ABA models at low tree densities for all forest inventory attributes (15% MAPE in tree density-N-and 11% in volume-V). A plantation of 500 ha of Pinus radiata (400–600 trees ha −1) in Chile was selected a forest inventory was conducted using the ABA and ITC methods and the accuracy of both methods was analyzed. The objective of this study was to compare the prediction errors of forest inventory attributes in the functioning of ABA and ITC approaches. These two methodologies use different information processing and field data collection approaches thus, it is important to have a selection criterion for the method to be used based on the expected results and admissible errors. Several approaches have been employed to estimate forest parameters using ALS data, such as the Area-Based Approach (ABA) and Individual Tree Crown (ITC). Airborne laser scanning (ALS) technology is fully implemented in forest resource assessment processes, providing highly accurate and spatially continuous results throughout the area of interest, thus reducing inventory costs when compared with traditional sampling inventories.
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