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Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands

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posted on 27.03.2017, 13:53 by Chloe Barnes, Heiko Balzter, Kirsten Barrett, James Eddy, Sam Milner, Juan C. Suarez
Airborne laser scanning (ALS) can be utilised to derive canopy height models (CHMs) for individual tree crown (ITC) delineation. In the case of forest areas subject to defoliation and dieback as a result of disease, increased irregularities across the canopy can add complications to the segmentation of ITCs. Research has yet to address this issue in order to suggest appropriate techniques to apply under conditions of forest stands that are infected by phytopathogens. This study aimed to find the best method of ITC delineation for larch canopies affected by defoliation as a result of a Phytophthora ramorum infection. Sample plots from two study sites in Wales, United Kingdom, were selected for ITC segmentation assessment across a range of infection levels and stand characteristics. The performance of two segmentation algorithms (marker-controlled watershed and region growing) were tested for a series of CHMs generated by a standard normalised digital surface model and a pit-free algorithm, across a range of spatial resolutions (0.15 m, 0.25 m and 0.5 m). The results show that the application of a pit-free CHM generation method produced improved segmentation accuracies in moderately and heavily infected larch forest, compared to the standard CHM. The success of ITC delineations was also influenced by CHM resolution. Across all plots the CHMs with a 0.25 m pixel size performed consistently well. However, lower and higher CHM resolutions also provided improved delineation accuracies in plots dominated by larger and smaller canopies respectively. The selected segmentation method also influenced the success of ITC delineations, with the marker-controlled watershed algorithm generating significantly more accurate results than the region growing algorithm (p < 0.10). The results demonstrate that ITCs in forest stands infected with Phytophthora ramorum can be successfully delineated from ALS when a pit-free algorithm is applied to CHM generation.



Remote Sensing, 2017, 9 (3), pp. 231

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/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Geography/GIS and Remote Sensing


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