Indirect Measurement of Forest Leaf Area Index Using Path Length Distribution Model and Multispectral Canopy Imager
Indirect Measurement of Forest Leaf Area Index Using Path Length Distribution Model and Multispectral Canopy Imager
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利用路径长度分布模型和多光谱冠层成像仪间接测量森林叶面积指数
DOI：
10.1109/jstars.2016.2569469
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发表时间：
2016-06
影响因子：
5.5
通讯作者：
Mu Xihan
中科院分区：
文献类型：
--
作者：
Hu Ronghai;Luo Jinghui;Yan Guangjian;Zou Jie;Mu Xihan
林冠和木质成分的空间异质性是限制间接叶面积指数（LAI）测量精度的两个因素，但由于商业仪器的限制，它们尚未得到充分考虑。本研究首次将路径长度分布模型与多光谱冠层成像仪相结合，提高了间接LAI测量的精度。在阔叶林和针叶林中进行了间接和直接的原位测量。结果表明：在4个样地，冠层内的空间异质性低估了LAI 16 ~ 25%，而木本成分高估了LAI 14 ~ 28%。这两个因素表现出相反的效果，这可能会产生误导，从而可能使每个因素的效果的量化和验证复杂化。忽略木质成分低估了森林的空间异质性或丛化程度。在间接LAI测量中，同时考虑冠层和木本成分的非随机性是必要的。
Spatial heterogeneity within canopies and woody components are two factors that limit the accuracy of indirect leaf area index (LAI) measurements, but they have not been fully considered because of the limitations of commercial instruments. This study combined the path length distribution model and multispectral canopy imager for the first time to improve the accuracy of indirect LAI measurements. Indirect and direct in situ measurements were conducted in broadleaf and coniferous forests. Results show that spatial heterogeneity within canopies underestimates the LAI by 16-25%, whereas woody components overestimate LAI by 14-28% in four forest sites. These two factors exhibit opposing effects, which may be misleading and may thus complicate the quantification and validation of the effect of each factor. Ignoring woody components underestimates the degree of spatial heterogeneity or clumping in forests. Considering both nonrandomness within canopies and woody components is necessary in indirect LAI measurements.
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影响因子：
13.5
作者：
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影响因子：
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DOI：
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发表时间：
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期刊：
AGRICULTURAL METEOROLOGY
影响因子：
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作者：
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通讯作者：
NILSON, T