2 March 2016 Simple approach to improving the extraction of canopy metrics from airborne laser scanning data for tropical forests
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Abstract
We aim to improve the predictive mapping of stem volume with airborne laser scanning (ALS) data acquired in Laos by adapting the area-based approach (ABA) to a tropical context. Separating laser returns of bushes from main stories with a cut-off threshold is a step very important to the ABA. The adaptation focused here on applying global and plot-adaptive cut-off thresholds to improve the extraction of canopy metrics. In order to select the optimal global cut-off threshold for removing understory bushes and ground objects, a sensitivity analysis of the modeling efficacy to the global cut-off threshold was conducted in the range from 0 to 5 m at 0.1-m intervals. To account for structural variation between plots, a simple plot-adaptive method was proposed for adjusting the threshold of each specific plot. The results showed that the optimal global cut-off threshold, which implicitly assumed the forest structure being homogeneous for all plots was 3.6 m. A model based on the plot-adaptive cut-off thresholds achieved better accuracy (RMSE 28%) than did the optimal global threshold-based model (RMSE 30%). It is concluded that the ALS-based canopy metrics extracted using the plot-adaptive method describe the structural heterogeneity of tropical forests adequately, whereas the global thresholding method is contingent on the forest structure being simple.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Zhengyang Hou, Zhengyang Hou, Qing Xu, Qing Xu, Chao Zhang, Chao Zhang, Matti Maltamo, Matti Maltamo, Timo Tokola, Timo Tokola, } "Simple approach to improving the extraction of canopy metrics from airborne laser scanning data for tropical forests," Journal of Applied Remote Sensing 10(1), 016019 (2 March 2016). https://doi.org/10.1117/1.JRS.10.016019 . Submission:
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