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行播是我国作物耕种的重要形式,行播作物BRDF模型的建立是描述冠层二向性反射特征以及进一步估算农田生态参数的基础.由于宏观结构特征差异,以往研究往往将行播作物视为连续植被和离散植被之间的过渡性植被,将垄作为主要的几何特征用几何光学方法分别计算冠层光照面与阴影面、背景光照面与阴影面在传感器视场中的面积比例(四分量),并通过线性加权求得行播作物对太阳辐射的一次反射辐射亮度的近似解析表达式,但是鉴于四分量随太阳-目标-传感器三者几何关系的改变而改变,造成计算公式过于复杂,加大了生态参数反演的难度.本文从植被冠层微观结构入手,将行播作物视为叶片在冠层尺度上发生群聚的结果,用尼尔逊参数将均匀连续植被、小尺度群聚连续植被以及行播作物联系起来,从理论上推导尼尔逊参数的近似表达式,并利用几何光学模型思想,将叶片作为计算四分量(即光照与阴影叶片以及光照与阴影背景)的出发点,首先建立均匀连续植被的BRDF模型,然后逐步推广到行播作物的一体化BRDF模型.把描述叶片在空间分布上发生群聚现象的尼尔逊参数()引入到BRDF表达式中有重要意义.为了验证行播作物一体化BRDF模型,利用“黑河遥感联合实验(WATER)”于2008年5月30日和7月1日在黑河流域地面采集的行播作物冠层BRDF数据作为验证数据集与模拟结果进行了对比,结果表明本文提出的行播作物BRDF一体化模型能够较准确的描述行播作物冠层反射的非各向同性性质,表述更合理简便,亦利于参数反演,总之,离散植被和连续植被之间没有不可逾越的鸿沟,充分认识到它们之间的共性与个性有利于BRDF建模;同时也再次证明几何光学四分量模型抓住了所有植被类型二向性反射的基本动因,适用于不同植被类型.
Row propagation is an important form of crop cultivation in China. The establishment of BRDF model for row sowing crops is the basis for describing canopy dichroism reflection characteristics and further estimation of ecological parameters of farmland. Because of the differences in macro-structure characteristics, past studies often regard row sowing as Continuous vegetation and discrete vegetation between the transitional vegetation, the ridge as the main geometric features Geometric optical method were used to calculate the canopy light and shadow surface, the background light and shadow area in the sensor field of view area ratio (four components ), And obtains the approximate analytic expression of the primary reflected radiation brightness of the line sowing crop by linear weighting. However, given the change of the four components with the change of the geometrical relationship of the sun-target-sensor, the calculation formula is too complicated, Which increases the difficulty of inversion of ecological parameters.In this paper, the microcosmic structure of vegetation canopy is taken as a starting point, and row planting crops are considered as the result of the clustering of the leaves on the canopy scale. Nielsen parameters are used to divide the vegetation with uniform continuous vegetation, Polycontinuous vegetation and line sowing crops, the approximate expression of the Nelson parameter is derived theoretically, and the use of geometric optical model , The leaves were used as the starting point to calculate the four components (light and shaded leaves and light and shaded background). Firstly, the BRDF model of uniform continuous vegetation was established and then extended to the integrated BRDF model of sowed crops. The introduction of the Nelson parameter () on the occurrence of clustering is of great importance to the BRDF expression. In order to validate the BRDF model for line cropping, we used the “Black River Remote Sensing Joint Experiment” (WATER) on May 30, 2008 Day and July 1 in the Heihe River Basin were collected as validation data set of BRDF data and compared with simulation results. The results show that the BRDF integrated model proposed in this paper can describe the sowing crop more accurately In general, there is no insurmountable gap between the discrete vegetation and the continuous vegetation, and it is fully recognized that the commonality and individuality between them is in favor of the BRDF At the same time, it proves again that the four-component model of geometrical optics captures the basic motivation of the bivariate reflection of all vegetation types and is suitable for different vegetation types.