Abstract Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. We designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with

中文翻译：

---

用于同时测量太阳诱导的叶绿素荧光和高光谱反射率的无人机系统 (UAS)，以改善作物监测

摘要 基于无人机系统（UAS）的遥感可以为精准管理提供高时空分辨率的作物监测。现有的作物监测 UAS 主要使用传统技术，如多光谱宽带植被指数 (VI) 来跟踪冠层结构/生物量。最近开发的轻量级高光谱传感器可以通过补充信号跟踪作物生理和性能，例如太阳诱导的叶绿素荧光 (SIF) 和可从高光谱反射率导出的光化学反射率指数 (PRI)。然而，很少有现有的 UAS 能够获得高质量的 SIF 和高光谱反射率。我们设计了一种新型 UAS，它同时捕获远红色 SIF 和高光谱反射率，使用单个分叉光纤和电动臂来测量下流和上流辐照度。UAS 在 (1) 具有空间变化的作物产量潜力的异质玉米田和 (2) 在不同营养处理下的一组大豆和玉米地块上进行了测试。我们的 UAS 可以在中低风 (2–3 m/s) 下保持稳定