Abstract
The present study introduces a method to identify tree stems from terrestrial laser scanning (TLS) data. We focused on forest environments of diverse and layered structure, which were technically characterized by strong occlusion effects with regards to laser scanning. The number and distribution of tree stems are important information for the management of protective forests against natural hazards, for forest inventory, and for ecological studies. Our approach builds upon a three-dimensional (3D) voxel grid transformation of the original point cloud data, followed by two major steps of processing. Firstly, a series of morphological operations removed leaves and branches and left only potential stem segments. Secondly, the stem segments of each tree were combined by a multipart workflow, which uses shape and neighborhood criteria. At the same time, erroneous fragments and noise were removed from the dataset. As a result, each object in the voxel grid was represented by a single connected component referring to one specific tree stem. Testing the method on nine spatially independent plots provided detection rates of 97% for the number and location of stems from mature trees with a diameter >= 12 cm and 84% for smaller trees with a minimum of 130 cm total tree height. In summary, we obtained a dataset covering the number and locations of the stems from both mature and understory trees, while not aiming at a precise reconstruction of the stem shape.
Highlights
Ground based remote sensing techniques, like terrestrial laser scanning (TLS), are often advantageous for structures that are difficult to observe from a bird’s eye perspective
A stem was counted as a match if the reference position was within its cross section of the detected stem, or, if it could be clearly assigned to a close-by reference position while excluding any alternative possibility
This study presented an advanced approach for tree stem detection based on 3D image analysis techniques
Summary
Ground based remote sensing techniques, like terrestrial laser scanning (TLS), are often advantageous for structures that are difficult to observe from a bird’s eye perspective. For layered forests with a strong understory, vegetation objects, such as tree stems, can be better observed by TLS compared to airborne laser scanning (ALS). Due to the different perspective of TLS and the closer distance to the objects, higher point densities and higher levels of detail can be achieved. Hilker et al [1] explained why ALS is largely insensitive for below canopy vegetation objects and investigated differences in return distribution between ALS and TLS data. White et al [3]
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