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EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

机译:ECOSPEC:高度配备的基于塔的高光谱和热红外自动遥感系统用于调查植物对环境变化的反应

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摘要

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350–2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.
机译:尽管在区域和全球范围内预测生态系统功能和气候的先进能力,但对水和碳通量的局部变化和大规模现象之间的关系很少。为了使本地级生态系统的数据集合能够支持此类调查,我们开发了一种高度配备的遥感系统,该系统具有高光谱辐射计(350-2500nm)和一个紧凑塔中的五个光学和红外传感器。其自定义软件控制传感器和系统组件的移动的顺序和时序,并在塔周围的12个位置收集测量。使用该系统收集的数据被处理以去除从数据计算的太阳角效应,以及从数据计算的光谱植被指数(即,归一化差异植被指数(NDVI),归一化差异水指数(NDWI),光化学反射率指数(PRI),将水分应激指数(MSI)与光化学活性辐射(FPAR)和冠层温度的分数进行比较。结果表明,NDVI,NDWI和PRI与FPAR密切相关; MSI与昼夜规模的冠层温度相关联。这些相关性表明,这种类型的近表面遥感系统将补充现有的观察者,以验证卫星遥感观测,并将局部和大规模现象连接,以提高我们预测生态系统功能和气候的能力。该系统还与学习作物生长,检测疾病和害虫进行精密农业,并比较品种的特征。

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