Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data
Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data
复制标题
DOI：
10.1016/j.rse.2017.03.017
复制
发表时间：
2017-06-01
影响因子：
13.5
通讯作者：
Qie, Lan
中科院分区：
文献类型：
--
作者：
Coomes, David A.;Dalponte, Michele;Qie, Lan
热带森林是全球碳循环的一个关键组成部分，绘制其碳密度图对于了解人类对气候的影响和基于生态系统服务的森林保护付款至关重要。离散返回机载激光扫描（ALS）越来越被认为是一种高质量的热带森林碳测绘技术，因为它可以生成森林结构的3D点云，从中可以估计地上碳密度（ACD）。当涉及到从ALS数据估计ACD时，基于区域的模型是最先进的，但是丢弃ALS点云中包含的树级信息。本文比较了基于面积和树为中心的模型，估计ACD在低地古老的森林在沙巴，马来西亚。这些森林由于其巨大的高度而具有挑战性。我们比较了（a）由Asner和Mascaro（2014）开发的基于区域的模型的性能，迄今为止主要用于新热带地区，（B）以树为中心的方法，该方法使用新算法（itcSegment）在ALS冠层高度模型中定位树木，测量它们的高度和树冠宽度，并从这些维度计算生物量。我们发现Asner和Mascaro的模型需要区域校准，反映了东南亚森林的独特结构。我们还发现森林断面积与ALS测量的林窗比例密切相关，并利用这一发现来改进Asner和Mascaro的模型。最后，我们证明了我们的以树为中心的方法在估计ACD方面不如性能最好的基于区域的模型准确（RMSE 18% vs 13%）。以树为中心的建模很有吸引力，因为它是基于对单个树木的生物量进行求和，但在算法能够可靠地检测林下树木并从树冠尺寸精确估计生物量之前，基于区域的建模仍将是首选方法。(C)2017作者爱思唯尔公司出版
Tropical forests are a key component of the global carbon cycle, and mapping their carbon density is essential for understanding human influences on climate and for ecosystem-service-based payments for forest protection. Discrete-return airborne laser scanning (ALS) is increasingly recognised as a high-quality technology for mapping tropical forest carbon, because it generates 3D point clouds of forest structure from which aboveground carbon density (ACD) can be estimated. Area-based models are state of the art when it comes to estimating ACD from ALS data, but discard tree-level information contained within the ALS point cloud. This paper compares area based and tree-centric models for estimating ACD in lowland old-growth forests in Sabah, Malaysia. These forests are challenging to map because of their immense height. We compare the performance of (a) an area-based model developed by Asner and Mascaro (2014), and used primarily in the neotropics hitherto, with (b) a tree-centric approach that uses a new algorithm (itcSegment) to locate trees within the ALS canopy height model, measures their heights and crown widths, and calculates biomass from these dimensions. We find that Asner and Mascaro's model needed regional calibration, reflecting the distinctive structure of Southeast Asian forests. We also discover that forest basal area is closely related to canopy gap fraction measured by ALS, and use this finding to refine Asner and Mascaro's model. Finally, we show that our tree-centric approach is less accurate at estimating ACD than the best-performing area-based model (RMSE 18% vs 13%). Tree-centric modelling is appealing because it is based on summing the biomass of individual trees, but until algorithms can detect understory trees reliably and estimate biomass from crown dimensions precisely, areas-based modelling will remain the method of choice. (C) 2017 The Authors. Published by Elsevier Inc.