Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).

中文翻译：

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从上方绘制生物多样性图：融合激光雷达和高光谱遥感能否预测温带森林的分类、功能和系统发育树的多样性？

快速的全球变化正在影响树种的多样性以及森林的基本生态系统功能和服务。因此，了解和预测树种多样性如何在森林生物群系内部和之间的空间分布至关重要。几十年来，卫星遥感平台一直用于绘制森林结构和功能图，但由于其相对粗糙的空间分辨率和在实地观察生物多样性不同维度的尺度复杂性，其监测变化的能力受到限制。最近，利用无源高光谱分辨率（即高光谱）和有源激光雷达数据的机载遥感平台已经投入使用，提供了一个机会，可以解开从野外观测到更大规模的生物多样性模式在空间和时间上的变化。迄今为止，大多数研究都集中在单个站点和/或一种传感器类型上；在这里，我们询问来自国家生态观测站网络的机载观测平台 (NEON AOP) 的多种传感器类型如何在 NEON 场图尺度（即 40 m × 40 m）的单个生物群落中的多个站点上执行。