Paper
6 August 2018 A voxel-based model of LiDAR point cloud for estimating forest canopy closure
Author Affiliations +
Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 107730Q (2018) https://doi.org/10.1117/12.2326122
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus
Abstract
Within UNFCCC framework, forest monitoring should be capable of detecting emissions from not only deforestation, but also from forest degradation. In fact, determinants of deforestation are relatively more detectable using remotely sensed data than determinants of forest degradation. Forest canopy closure is one important determinant of forest degradation. In this case, loss on forest canopy closure indicates forest degradation. As part of our activities in developing methodology for estimating forest canopy closure, this paper describes our methods on estimating forest canopy closure based on ALS LiDAR point cloud through the development of a three dimensionally explicit voxel-based model of forest canopy using an open-source modelling platform of NetLogo 3D 5.3.1. Window area in South Sumatra, Indonesia was selected as the study site. Estimated canopy closure resulted by our model was compared with the results from commercial software (i.e. LiDAR360). The results of this study suggest that using a simple voxel-based model with 2 parameters within open source platform; it is possible to estimate forest canopy closure based on ALS LiDAR point cloud at relatively small deviation (around 25.04%), as compared to similar commercial software, which algorithm is usually hidden. However, validating the model with ground measured data on canopy closure should be carried out.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Desi Suyamto, Lilik Prasetyo, and Yudi Setiawan "A voxel-based model of LiDAR point cloud for estimating forest canopy closure", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730Q (6 August 2018); https://doi.org/10.1117/12.2326122
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KEYWORDS
Data modeling

Clouds

LIDAR

3D modeling

Algorithm development

Detection and tracking algorithms

Modeling

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