Abstract Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

中文翻译：

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叶面积指数和结团指数数据协同 地球观测产品使用光子重碰撞概率理论

摘要 丛生指数 (CI) 是相对于叶子在空间中随机分布的叶子聚集的量度。CI 可以帮助估计给定叶面积指数 (LAI) 值的阳光照射和阴影叶片的分数。CI 和 LAI 都可以从来自传感器（例如中分辨率成像光谱仪 (MODIS)）的全球地球观测数据中获得。在这里，基于 MODIS 的 CI 和 MODIS LAI 产品之间的协同作用使用光谱不变量理论，也称为光子重新碰撞概率（“p 理论”）以及原始 LAI-2000/2200 植物冠层分析仪进行检查来自分布在一系列植物功能类型的 75 个站点的数据。p 理论描述了光子在树冠中拦截元素的概率（p 值），将与另一个顶篷元素重新碰撞而不是逃离顶篷。我们表明，基于经验的 CI 地图可以与 MODIS LAI 产品集成。我们的结果表明，仅从地球观测数据中推导出任何位置的近似 p 值是可行的。这种近似与光子碰撞概率概念的未来应用相关，用于使用地球观测数据对植被进行全球和局部监测。