森林叶面积指数(LAI)连续观测:LAI-NOS 的验证、应用和改进

IF 2.4 2区 农林科学 Q1 FORESTRY Forests Pub Date : 2024-05-16 DOI:10.3390/f15050868
Zhentao Gao, Yunping Chen, Zhengjian Zhang, Tianxin Duan, Juncheng Chen, Ainong Li
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引用次数: 0

摘要

叶面积指数(LAI)是反映植被生长状况的核心参数之一。在评估生态系统能量交换的动态变化和植被对气候变化的响应指标时,对叶面积指数的连续长期观测是关键。人工 LAI 测量中的非标准操作所带来的误差阻碍了对该参数的进一步研究利用。长期的自动 LAI 观测网络有助于减少人工测量的误差。为了进一步检验自动 LAI 观测仪器在森林环境中的适用性,本研究在中国王朗山生态遥感综合观测站开展了 LAI-NOS (LAI 自动网络观测系统)的对比验证研究,将其与 LAI-2200 植物冠层分析仪(LI-COR, Lincoln, NE, USA)、LAI-probe 手持式仪器和鱼眼镜头数码相机(DHP 法)的测量结果进行了比较。摒弃了原有的 "最平滑窗口 "法,采用了新的 "日出-日落 "法来提取日 LAI-NOS LAI,并使用相应的置信度来筛选数据。数据分析结果如下:LAI-NOS 具有较高的数据稳定性。连续两天之间自动获取的每日数据偏差较小,相关性显著。LAI-NOS 的单角/多角度 LAI 测量结果与 LAI-2200 (R2 = 0.512/R2 = 0.652)、LAI-探针(R2 = 0.692/R2 = 0.619)和 DHP 方法(R2 = 0.501/R2 = 0.394)具有良好的相关性。与原始方法相比,改进方法获得的日 LAI 都显示出相同的植被生长趋势。然而,改进方法的离散度较小。这项研究证实了自动观测仪器在山地森林中的稳定性和准确性,显示了自动测量仪器在长期地面观测 LAI 方面的明显优势。
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Continuous Leaf Area Index (LAI) Observation in Forests: Validation, Application, and Improvement of LAI-NOS
The leaf area index (LAI) is one of the core parameters reflecting the growth status of vegetation. The continuous long-term observation of the LAI is key when assessing the dynamic changes in the energy exchange of ecosystems and the vegetation’s response indicators to climate change. The errors brought about by non-standard operations in manual LAI measurements hinder the further research utilization of this parameter. The long-term automatic LAI observation network is helpful in reducing errors from manual measurements. To further test the applicability of automatic LAI observation instruments in forest environments, this study carried out comparative validation research of the LAI-NOS (LAI automatic network observation system) at the Wanglang Mountain Ecological Remote Sensing Comprehensive Observation Station, China, comparing it with the results measured by the LAI-2200 Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA), the LAI-probe handheld instrument, and a fisheye lens digital camera (DHP method). Instead of using the original “smoothest window” method, a new method, the “sunrise–sunset” method, is used to extract daily LAI-NOS LAI, and the corresponding confidence level is used to filter the data. The results of the data analysis indicate the following: LAI-NOS has a high data stability. The automatically acquired daily data between two consecutive days has a small deviation and significant correlations. Single-angle/multi-angle LAI measurement results of the LAI-NOS have good correlations with the LAI-2200 (R2 = 0.512/R2 = 0.652), the LAI-probe (R2 = 0.692/R2 = 0.619), and the DHP method (R2 = 0.501/R2 = 0.394). The daily LAI obtained from the improved method, when compared to the original method, both show the same vegetation growth trend. However, the improved method has a smaller dispersion. This study confirms the stability and accuracy of automatic observation instruments in mountainous forests, demonstrating the distinct advantages of automatic measurement instruments in the long-term ground observation of LAIs.
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来源期刊
Forests
Forests FORESTRY-
CiteScore
4.40
自引率
17.20%
发文量
1823
审稿时长
19.02 days
期刊介绍: Forests (ISSN 1999-4907) is an international and cross-disciplinary scholarly journal of forestry and forest ecology. It publishes research papers, short communications and review papers. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.
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