Questioning voxel grids: Semi-continuous sampling of leaf area density using airborne waveform lidar in boreal and hemiboreal conifer and broadleaved forests

IF 5.6 1区 农林科学 Q1 AGRONOMY Agricultural and Forest Meteorology Pub Date : 2024-09-11 DOI:10.1016/j.agrformet.2024.110218
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引用次数: 0

Abstract

Plant area density measurements provide spatially explicit information about the density and distribution of canopy elements. This information is needed for modeling of the forest radiation regime, climate and for other ecological applications. Terrestrial laser scanning (TLS) provides detailed information about canopy structure, but it cannot be used for monitoring large areas. Airborne laser scanning (ALS) uses similar methods to measure plant area density, but due to the larger beam footprints, the scale at which this information can be obtained is coarser than with TLS. The volumetric nature of the ALS measurement poses unique geometric challenges to plant area measurement methods, as assuming an infinitesimal beam size may lead to large errors. Further, the use of voxel grids with ALS measurements may increase errors in plant area measurements, as these grids require discrete spatial allocation of information.

In this study, we apply a spatial weighting technique to ray-traced measurements of plant area from ALS data. This spatial weighting scheme allows continuous allocation of trajectory information of ALS pulses, avoiding discontinuity introduced by voxel grids.

Our data consisted of high density ALS waveform data (over 40 points/m2) in 33 plots across two study sites in Finland and Estonia. We compared the plant area index (PAI) obtained through this new measurement method to PAI measurements from hemispheric photography (HP) and TLS, and to ALS with a voxel grid. We found PAI, measured at agrid spacing of 0.6 m, correspond best to HP and TLS measurements. Occlusion severely biased PAI at 0.2 m spacing. With increasing grid spacing, PAI estimates become increasingly biased because of clumping effects at small scales. Continuously sampled PAI measurements corresponded closer to reference values than voxel-based PAIs, indicating that a spatially weighted approach avoids bias from partitioning the volumetric ALS beams into voxels.

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质疑体素网格:利用机载波形激光雷达对北方和半北方针叶林和阔叶林的叶面积密度进行半连续采样
植物面积密度测量可提供有关树冠要素密度和分布的空间信息。森林辐射系统建模、气候建模和其他生态应用都需要这些信息。地面激光扫描(TLS)可提供有关树冠结构的详细信息,但不能用于大面积监测。机载激光扫描(ALS)使用类似的方法来测量植物面积密度,但由于光束足迹较大,可获得的信息尺度比地面激光扫描更粗。ALS 测量的体积性质给植物面积测量方法带来了独特的几何挑战,因为假设光束尺寸无限小可能会导致较大误差。此外,在 ALS 测量中使用体素网格可能会增加植物面积测量的误差,因为这些网格需要离散的空间信息分配。我们的数据包括芬兰和爱沙尼亚两个研究地点 33 块地的高密度 ALS 波形数据(超过 40 个点/平方米)。我们将通过这种新测量方法获得的植物面积指数(PAI)与半球摄影(HP)和 TLS 的 PAI 测量值以及采用象素网格的 ALS 测量值进行了比较。我们发现,以 0.6 米的栅格间距测量的 PAI 与 HP 和 TLS 的测量结果最为吻合。在 0.2 米间距时,闭塞严重偏离 PAI。随着网格间距的增加,由于小尺度上的团聚效应,PAI 估计值的偏差越来越大。与基于体素的 PAI 相比,连续采样的 PAI 测量值更接近参考值,这表明空间加权方法可以避免将 ALS 波束的体积分割成体素所造成的偏差。
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来源期刊
CiteScore
10.30
自引率
9.70%
发文量
415
审稿时长
69 days
期刊介绍: Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.
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