Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightThus, the Turkish FI system could benefit from this novel technology, which in turn supports the implementation ofsound forest management and planning.
📌 3 Maddede Bu Makale
Abstract
Forest inventory (FI) is the most challenging stage of forest management and planning process. Therefore, in situ surveys areoften reinforced by modern remote sensing (RS) methods for collecting forestry-related data more efficiently. This study tests a stateof-the-artdata collection method for practical use in the Turkish FI system for the first time. To this end, forest sampling plots wereconventionally measured to collect dendrometric data from 437 trees in Artvin and Saçınka Forest Enterprises. Then, each plot wasscanned using a handheld mobile laser scanning (HMLS) instrument. Finally, HMLS data were compared against ground measurementsvia basic FI measures. Based on statistical tests, no apparent differences were found between the two datasets at the plot level (P 0.97; P < 0.01). Residual analysis showed thatboth positive and negative errors had a homogeneous distribution, except for plot 8 where tree stems were in irregular shapes due toanthropogenic pressures. When all plots’ data were aggregated, average values for the number of trees, basal area, and timber volumewere estimated as 535 trees/ha–1, 49.6 m2/ha–1, and 499.7 m3/ha–1, respectively. Furthermore, secondary measures such as the numberof saplings and slope were successfully retrieved using HMLS method. The highest overestimation was in timber volume with less than10% difference at the landscape level. The differences were attributed to poor data quality of conventional measurements, as well asmarginal site conditions in some plots. We concluded that the HMLS method met the accuracy standards for most FI measures, exceptfor stand height. Thus, the Turkish FI system could benefit from this novel technology, which in turn supports the implementation ofsound forest management and planning.