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Detection of coarse woody debris using airborne light detection and ranging (LiDAR)

机译:使用空机光检测和测距(LIDAR)检测粗木质碎片

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Coarse woody debris (CWD) is an essential component of forest ecosystems that provides habitat for diverse species, functions in water and nutrient cycling, and can be a potential surface fuel in wildfires. CWD detection and mapping would enhance forestry and wildlife research and management but passive remote sensing technologies cannot provide information on features beneath forest canopy, while field-based CWD inventories are not practical for mapping CWD over large areas. Airborne light detecting and ranging (LiDAR) is a remote sensing technology that provides detailed information on three-dimensional vegetation structure that could overcome limitations of passive remote sensing technologies and field-based inventories. Our objectives were to evaluate whether airborne LiDAR could be used to detect individual pieces of CWD. We measured 1679 pieces of CWD at 144 field plots from 2015 to 2016. We acquired high-density (similar to 24 first returns/m(2)) LiDAR data in 2014, filtered out canopy and sub-canopy returns using a height threshold based on field measurements of CWD, and used height-filtered data to determine which field-measured pieces of CWD were visible in the resulting point cloud. CWD pieces that were detected constituted 50% of plot CWD volume, and there was a strong, positive correlation between total plot CWD volume and volume of detected pieces (r = 0.96). Overall, we detected 23% of the individual pieces of CWD we measured. Large pieces of CWD were most likely to be detected, with the majority of pieces &= 30 cm diameter or &= 13.9 m long detected. Canopy density, shrub density, and forest type did not influence detection probability. CWD detection rates increased from 1 pulses/m(2) to 16 pulses/m(2), and CWD detection rate was constant from 16 pulses/m(2) to 24 pulses/m(2). Our results demonstrate that airborne LiDAR can be used to detect CWD. LiDAR-based detection and mapping of CWD will be most useful for applications that focus on larger and longer pieces of CWD or applications focused on total CWD volume.
机译:粗木质碎片(CWD)是森林生态系统的重要组成部分,为各种物种提供栖息地,水和营养循环的功能,并且可以是野火中的潜在表面燃料。 CWD检测和映射将增强林业和野生动物研究和管理,但被动遥感技术无法提供森林冠层下面的特征信息,而基于领域的CWD库存对于在大区域上映射CWD并不实用。空中灯检测和测距(LIDAR)是一种遥感技术,提供有关三维植被结构的详细信息,可以克服被动遥感技术和基于现场库存的限制。我们的目标是评估机载LIDAR是否可以用于检测单个CWD的各个碎片。我们从2015到2016年测量了1679件CWD。我们在2014年获得了高密度(类似于24个第一个返回/ M(2))LIDAR数据,通过基于高度阈值滤除了遮篷和子天篷返回关于CWD的现场测量,并使用高度滤波的数据来确定所得点云中可见的现场测量的CWD片段。检测到的CWD片构成50%的曲线CWD体积,并且在总曲线CWD体积和检测到的碎片的体积之间存在强烈,正相关(R = 0.96)。总体而言,我们检测到我们测量的23%的CWD。大部分碎片& = 30厘米直径或& = 13.9米长的大部分CWD。冠层密度,灌木密度和森林类型没有影响检测概率。 CWD检测速率从1个脉冲/ m(2)增加到16个脉冲/ m(2),并且CWD检测速率从16个脉冲/ m(2)到24脉冲/ m(2)恒定。我们的结果表明,机载LIDAR可用于检测CWD。基于LIDAR的CWD检测和映射对于专注于较大且较长较长的CWD或专注于总CWD体积的应用的应用,CWD最有用。

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