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COMPARISON OF THREE INDIRECT FIELD MEASURING METHODS FOR FOREST CANOPY LEAF AREA INDEX ESTIMATION

机译:三种间接现场测量方法对森林冠层叶片区指数估计的比较

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The Effective Plant Area Index (PAIe) of forest canopy is an important parameter in the canopy reflectance modeling and validation. PAIe can be transformed to leaf area index (LAI) with clumping index. But it is still very difficult to obtain its ground truth value by in situ measurement. In this study, we measured PAIe of 3 typical wood land sites in China by means of three indirect optical techniques: plant canopy analyzer LAI-2000, TRAC, and Digital Fisheye Camera. The 5 measured stands include Qinghai spruce, peach, poplar, willow and silver chain. In this paper, the forest canopy PAIe measured by those three instruments is compared firstly. Then our new approach is how to use the three measured data to get the better PAIe estimation with less overall error. The method of minimizing overall error is adopted to produce PAIe of the sample plots in our study sites, which has less overall error comparing with the PAIe measured by each individual instrument. This approach is also validated by using computer simulated wide-angle viewing pictures when true LAI/PAIe values are given.
机译:森林冠层的有效植物区指数(PAIE)是树冠反射率建模和验证中的重要参数。 Paie可以用丛集指数转变为叶面积指数(LAI)。但通过原位测量仍然非常困难地获得其基础值。在这项研究中,我们通过三种间接光学技术测量了中国的3个典型木土地位点:植物冠层分析仪LAI-2000,TRAC和数字鱼眼相机。 5个测量的立场包括青海云杉,桃子,杨树,柳树和银链。本文首先比较了这三种仪器测量的森林冠层PAIE。然后我们的新方法是如何使用三个测量数据来获得更好的PAIE估计,总体错误较少。采用最小化总体误差的方法来在我们的研究站点中生产样品地块的PAIE,其与每个单独仪器测量的PAIE相比的总体误差较差。当给出真正的LAI / PAIE值时,还通过使用计算机模拟广角观察图片验证该方法。

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