Abstract Declining near-infrared (NIR) surface reflectance between early and late summer, here termed greendown, is a common, yet poorly understood phenomena in remote sensing time series of temperate deciduous forests. As revealed by phenology analysis of Landsat satellite data, there are strong spatial patterns in the rate of greendown across temperate deciduous forest landscapes, and analyzing these patterns could help advance our understanding of surface reflectance drivers. Within an oak-hickory (Quercus spp. – Carya spp.) forest landscape in western Maryland, USA, we tested how spatial patterns in greendown related to potential drivers at the landscape-, tree crown- and leaf-levels. We found that 50% of the spatial variability in greendown was explained by landscape variables, with greendown particularly higher in locations with higher maximum greenness, more southerly aspects, or locations with greater abundance of white oak (Quercus alba). The importance of species composition as a driver of greendown was supported at the tree crown level, where, relative to three other tree species, white oak exhibited the most consistent trend toward more vertical leaf angles later in the season. At the leaf level, NIR reflectance decreased in productive sites where %N increased, and δ13C decreased, through the season. However, among all sites, there were no consistent seasonal trends in foliar NIR reflectance, and we found no correlation among leaf-level NIR reflectance and satellite-observed greendown. Collectively, these results suggest that the spatial variability of greendown in this oak-hickory forest is most strongly controlled by an interaction of topographic and species compositional drivers operating at the landscape and tree crown levels. We found spatial analysis of greendown to be a useful approach to explore landscape-, tree crown-, and leaf-level controls on surface reflectance, and thereby help translate land surface phenology data into predictions of ecosystem structure and functioning.

中文翻译：

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橡木-山核桃林景观中绿化空间变异的驱动因素

摘要 夏初和夏末近红外 (NIR) 表面反射率下降，这里称为绿化，是温带落叶林遥感时间序列中常见但知之甚少的现象。正如 Landsat 卫星数据的物候分析所揭示的那样，温带落叶林景观的绿化率存在很强的空间模式，分析这些模式有助于加深我们对表面反射驱动因素的理解。在美国马里兰州西部的橡树山核桃 (Quercus spp. – Carya spp.) 森林景观中，我们测试了绿化中的空间模式如何与景观、树冠和叶级别的潜在驱动因素相关。我们发现绿化中 50% 的空间变异是由景观变量解释的，在最大绿度更高、更偏南的地方或白橡木（Quercus alba）丰富的地方，绿化率特别高。树冠水平支持物种组成作为绿化驱动因素的重要性，其中，相对于其他三种树种，白橡木在本季后期表现出最一致的叶角垂直趋势。在叶子水平，在整个季节，NIR 反射率在 %N 增加和 δ13C 减少的生产地点下降。然而，在所有站点中，叶面 NIR 反射率没有一致的季节性趋势，我们发现叶级 NIR 反射率与卫星观测绿化之间没有相关性。总的来说，这些结果表明，这片橡树-山核桃林中绿化的空间变异性受到在景观和树冠水平上运行的地形和物种组成驱动因素的相互作用的最强烈控制。我们发现绿化的空间分析是探索景观、树冠和叶级对地表反射率控制的有用方法，从而有助于将地表物候数据转化为生态系统结构和功能的预测。