3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction
3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction
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DOI：
10.1016/j.isprsjprs.2015.10.001
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发表时间：
2015-12-01
影响因子：
12.7
通讯作者：
Niemann, K. Olaf
中科院分区：
文献类型：
--
作者：
Zhu, Xi;Wang, Tiejun;Niemann, K. Olaf
叶片含水量在农业和林业管理中起着重要的作用。它可以用来评估干旱条件和野火的敏感性。地面激光扫描仪（TB）数据已被广泛用于森林环境中的几何生物物理参数检索。最近的研究还表明，使用辐射信息（后向散射强度）估计LWC的潜力。然而，后向散射强度数据的有用性受到叶片表面特性和入射角效应的限制。为了探索使用激光雷达强度数据来评估LWC的想法，我们归一化了短波红外TLS数据（1550 nm）（角度效应和叶片表面特性）。一个反射率模型描述了漫反射和镜面反射，以消除强镜面后向散射强度在垂直角度。从8种阔叶植物中采集了具有不同表面特性的叶片，用于模拟LWC与后向散射强度之间的关系。参考反射器（来自Labsphere，Inc.的Spectralon）用于建立查找表以补偿入射角效应。结果表明，在去除镜面反射影响前，垂直方向背向散射强度与LWC无显著相关性（R-2 = 0.01，P > 0.05）。在去除镜面反射影响后，出现了显著的相关性（R-2 = 0.74，P < 0.05）。测量的LWC和TLS推导的LWC之间的一致性表明，在校正入射角效应后，RMSE显著降低（均方根误差，从0.008 g/cm（2）到0.003 g/cm（2））。我们表明，它是可能的，使用TLS估计LWC为选定的阔叶植物的R-2为0.76（显着性水平α = 0.05）在叶水平。对叶片表面和内部结构的进一步研究将有助于改善植被生理生态学研究中的三维LWC制图。(C)2015年国际摄影测量与遥感学会（International Society for Photogrammetry and Remote Sensing，Inc.）（摄影测量和遥感学会）。Elsevier B. V.出版，保留所有权利。
Leaf water content (LWC) plays an important role in agriculture and forestry management. It can be used to assess drought conditions and wildfire susceptibility. Terrestrial laser scanner (TB) data have been widely used in forested environments for retrieving geometrically-based biophysical parameters. Recent studies have also shown the potential of using radiometric information (backscatter intensity) for estimating LWC. However, the usefulness of backscatter intensity data has been limited by leaf surface characteristics, and incidence angle effects. To explore the idea of using LiDAR intensity data to assess LWC we normalized (for both angular effects and leaf surface properties) shortwave infrared TLS data (1550 nm). A reflectance model describing both diffuse and specular reflectance was applied to remove strong specular backscatter intensity at a perpendicular angle. Leaves with different surface properties were collected from eight broadleaf plant species for modeling the relationship between LWC and backscatter intensity. Reference reflectors (Spectralon from Labsphere, Inc.) were used to build a lookup table to compensate for incidence angle effects. Results showed that before removing the specular influences, there was no significant correlation (R-2 = 0.01, P > 0.05) between the backscatter intensity at a perpendicular angle and LWC. After the removal of the specular influences, a significant correlation emerged (R-2 = 0.74, P < 0.05). The agreement between measured and TLS-derived LWC demonstrated a significant reduction of RMSE (root mean square error, from 0.008 to 0.003 g/cm(2)) after correcting for the incidence angle effect. We show that it is possible to use TLS to estimate LWC for selected broad-leaved plants with an R-2 of 0.76 (significance level alpha = 0.05) at leaf level. Further investigations of leaf surface and internal structure will likely result in improvements of 3D LWC mapping for studying physiology and ecology in vegetation. (C) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.