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Extraction of Mangrove Biophysical Parameters Using Airborne LiDAR

Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
International Digital Earth Applied Science Research Center, Chubu University, 1200, Matsumoto-Cho, Kasugai, Aichi 487-8501, Japan
Department of Survey Engineering, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand
Department of Geography, Faculty of Social Science, Kasetsart University, 50 Ngam Wong Wan Road, Ladyaow, Chatuchak, Bangkok 10900, Thailand
Author to whom correspondence should be addressed.
Remote Sens. 2013, 5(4), 1787-1808;
Received: 22 February 2013 / Revised: 1 April 2013 / Accepted: 3 April 2013 / Published: 12 April 2013
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Tree parameter determinations using airborne Light Detection and Ranging (LiDAR) have been conducted in many forest types, including coniferous, boreal, and deciduous. However, there are only a few scientific articles discussing the application of LiDAR to mangrove biophysical parameter extraction at an individual tree level. The main objective of this study was to investigate the potential of using LiDAR data to estimate the biophysical parameters of mangrove trees at an individual tree scale. The Variable Window Filtering (VWF) and Inverse Watershed Segmentation (IWS) methods were investigated by comparing their performance in individual tree detection and in deriving tree position, crown diameter, and tree height using the LiDAR-derived Canopy Height Model (CHM). The results demonstrated that each method performed well in mangrove forests with a low percentage of crown overlap conditions. The VWF method yielded a slightly higher accuracy for mangrove parameter extractions from LiDAR data compared with the IWS method. This is because the VWF method uses an adaptive circular filtering window size based on an allometric relationship. As a result of the VWF method, the position measurements of individual tree indicated a mean distance error value of 1.10 m. The individual tree detection showed a kappa coefficient of agreement (K) value of 0.78. The estimation of crown diameter produced a coefficient of determination (R2) value of 0.75, a Root Mean Square Error of the Estimate (RMSE) value of 1.65 m, and a Relative Error (RE) value of 19.7%. Tree height determination from LiDAR yielded an R2 value of 0.80, an RMSE value of 1.42 m, and an RE value of 19.2%. However, there are some limitations in the mangrove parameters derived from LiDAR. The results indicated that an increase in the percentage of crown overlap (COL) results in an accuracy decrease of the mangrove parameters extracted from the LiDAR-derived CHM, particularly for crown measurements. In this study, the accuracy of LiDAR-derived biophysical parameters in mangrove forests using the VWF and IWS methods is lower than in coniferous, boreal, pine, and deciduous forests. An adaptive allometric equation that is specific for the level of tree density and percentage of crown overlap is a solution for improving the predictive accuracy of the VWF method. View Full-Text
Keywords: LiDAR; mangrove; canopy height model; tree height; crown diameter; tree density; crown overlap LiDAR; mangrove; canopy height model; tree height; crown diameter; tree density; crown overlap
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Wannasiri, W.; Nagai, M.; Honda, K.; Santitamnont, P.; Miphokasap, P. Extraction of Mangrove Biophysical Parameters Using Airborne LiDAR. Remote Sens. 2013, 5, 1787-1808.

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