Finer Resolution Estimation and Mapping of Mangrove Biomass Using UAV LiDAR and WorldView-2 Data

编号 030021705

推送时间 20191216

研究领域 森林经理 

年份 2019 

类型 期刊 

语种 英语

标题 Finer Resolution Estimation and Mapping of Mangrove Biomass Using UAV LiDAR and WorldView-2 Data

来源期刊 FORESTS

期 第217期

发表时间 20191004

关键词 AGB estimation and mapping;  mangroves;  UAV?LiDAR;  WorldView-2; 

摘要 To estimate mangrove biomass at finer resolution, such as at an individual tree or clump level, there is a crucial need for elaborate management of mangrove?forest?in a local area. However, there are few studies estimating mangrove biomass at finer resolution partly due to the limitation of remote sensing data. Using WorldView-2 imagery,?unmanned?aerial?vehicle?(UAV) light detection and ranging (LiDAR) data, and field survey datasets, we proposed a novel method for the estimation of mangrove aboveground biomass (AGB) at individual tree level, i.e., individual tree-based inference method. The performance of the individual tree-based inference method was compared with the grid-based random?forest?model method, which directly links the field samples with the?UAV?LiDAR metrics. We discussed the feasibility of the individual tree-based inference method and the influence of diameter at breast height (DBH) on individual segmentation accuracy. The results indicated that (1) The overall classification accuracy of six mangrove species at individual tree level was 86.08%. (2) The position and number matching accuracies of individual tree segmentation were 87.43% and 51.11%, respectively. The number matching accuracy of individual tree segmentation was relatively satisfying within 8 cm <= DBH <= 30 cm. (3) The individual tree-based inference method produced lower accuracy than the grid-based RF model method with R-2 of 0.49 vs. 0.67 and RMSE of 48.42 Mg ha(-1) vs. 38.95 Mg ha(-1). However, the individual tree-based inference method can show more detail of spatial distribution of mangrove AGB. The resultant AGB maps of this method are more beneficial to the fine and differentiated management of mangrove forests.

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