Estimating the overstory and understory vertical extents and their leaf area index in intensively managed loblolly pine (Pinus taeda L.) plantations using airborne laser scanning,Remote Sensing of Environment

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Estimating the overstory and understory vertical extents and their leaf area index in intensively managed loblolly pine (Pinus taeda L.) plantations using airborne laser scanning
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.rse.2020.112250
Matthew J. Sumnall , Andrew Trlica , David R. Carter , Rachel L. Cook , Morgan L. Schulte , Otávio C. Campoe , Rafael A. Rubilar , Randolph H. Wynne , Valerie A. Thomas

Abstract Data from four discrete-return airborne laser scanning (ALS) acquisitions and three different sensor types across seven experimentally varied loblolly pine (Pinus taeda L.) plantations were used to test published and novel methodologies in quantifying forest structural attributes within stands, including height to live crown (HTLC; i.e. the lowest vertical canopy extent) of the canopy and the contributions to total plot-level leaf area from understory and overstory canopy vegetation. These ALS data were compared to in situ field measurements to develop ALS-based predictive models of these attributes. The correlation between field- and ALS-modeled HTLC data was strong, with an R2 of 0.79 (p

中文翻译：

使用机载激光扫描估算集约化管理的火炬松（Pinus taeda L.）人工林的上层和下层垂直范围及其叶面积指数

摘要来自七个不同实验的火炬松 (Pinus taeda L.) 种植园的四个离散返回机载激光扫描 (ALS) 采集和三种不同传感器类型的数据用于测试已发表的和新颖的方法来量化林分内的森林结构属性，包括高度活冠（HTLC；即最低的垂直冠层范围）以及林下和上层冠层植被对地块级总叶面积的贡献。将这些 ALS 数据与原位现场测量进行比较，以开发这些属性的基于 ALS 的预测模型。现场和 ALS 建模的 HTLC 数据之间的相关性很强，R2 为 0.79（p

更新日期：2021-03-01

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