Forest Growth

In the study, different algorithms and methods are developed for growth estimation. Three different types of variables were extracted from the point clouds representing each tree/plot using different methods; they were the difference between the highest laser hits, the difference between the digital surface models (DSMs) of the tree crown and the differences between the 85th, 90th and 95th percentiles of the height histograms corresponding to the crown. Best correspondence with the field measurements for individual trees was achieved with an R2 value of 0.68 and a RMSE of 43 cm. The results indicate that it is possible to measure the growth of an individual tree with multi-temporal laser surveys. At plot level analyses, the best result was obtained based on individual tree identification and matching. An improved tree-to-tree matching technique was used for linking the same tree identified from different acquisitions. The method is based on minimizing the distances between treetops in the N-dimensional data space.

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forest growth
laser scanning
remote sensing
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