Mapping selective logging impacts in Borneo with GPS and airborne lidar
Mapping selective logging impacts in Borneo with GPS and airborne lidar
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DOI：
10.1016/j.foreco.2016.01.020
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发表时间：
2016-04-01
影响因子：
3.7
通讯作者：
Cormier, Tina
中科院分区：
文献类型：
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作者：
Ellis, Peter;Griscom, Bronson;Cormier, Tina
减少影响伐木（RIL）是生物多样性保护和碳封存的一种有前景的管理策略，但激励机制因监测方法不足而受到阻碍。我们在选择性采伐的热带森林中绘制了 937 公顷的伐木基础设施，以提供可扩展的方法来衡量离散管理实践（拖运、集材和砍伐）的影响。我们使用激光雷达衍生的扰动模型绘制了印度尼西亚东加里曼丹五个工业特许区的六块龙脑香科森林选择性采伐后 26 个月内的所有滑道和运输道路的地图。伐木影响的激光雷达地图（220 公顷）与地面地图（总计 217 公顷，RMS 误差为 6 公顷或 3%）非常吻合，但滑道位置只有 59% 的时间一致。由于森林快速再生，激光雷达得出的运输道路总面积比现场测量的道路面积小 31%；收获后一年内激光雷达收集的一致性更高。根据激光雷达高度剖面的傅里叶变换生成的碳密度图估计滑移和砍伐生物量损失在地面测量值的 1-5% 范围内。激光雷达产生的集材和牵引影响区域仅覆盖了允许收获面积的 69%；其余地区没有显示出伐木干扰的迹象，现有的生物物理数据也无法解释它们的位置。这些结果强调需要对测井基础设施进行更广泛的测绘，以捕获滑道密度和迄今为止未检测到的无影响区域的空间变化。虽然地面 GPS 被建议作为大规模基础设施测绘最经济实惠的方法，但航空激光雷达是远程量化热带森林伐木影响程度的有效工具。 (C) 2016 年作者。由 Elsevier B.V. 出版
Reduced-impact logging (RIL) is a promising management strategy for biodiversity conservation and carbon sequestration, but incentive mechanisms are hindered by inadequate monitoring methods. We mapped 937 ha of logging infrastructure in a selectively harvested tropical forest to inform a scalable approach to measuring the impacts of discrete management practices (hauling, skidding, and felling). We used a lidar-derived disturbance model to map all skid trails and haul roads within 26 months of the selective harvest of six blocks of dipterocarp forest in five industrial concessions in East Kalimantan, Indonesia. Lidar maps of logging impacts (220 ha) agreed well with ground-based maps (total of 217 ha, RMS error of 6 ha or 3%), but skid trail positions agreed only 59% of the time. Due to rapid forest regeneration, total lidar-derived haul road area was 31% smaller than road area measured in the field; agreement was higher for lidar collections within a year of the harvest. Maps of carbon density generated from Fourier transforms of lidar height profiles estimated skidding and felling biomass losses to within 1-5% of ground-based measurements. Lidar-derived skidding and hauling impact zones covered only 69% of the permitted harvest area; the remaining areas showed no signs of logging disturbance, and available biophysical data did not explain their location. These results emphasize the need for more extensive mapping of logging infrastructure to capture spatial variability in skid trail density and hitherto undetected no-impact zones. While a ground-based GPS is recommended as the most affordable method for wide-scale infrastructure mapping, aerial lidar is an effective tool for remotely quantifying the extent of logging impacts in tropical forests. (C) 2016 The Authors. Published by Elsevier B.V.