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生态光谱仪:高度装备的基于塔架的高光谱和热红外自动遥感系统,用于研究植物对环境变化的响应。

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

作者信息

Hamada Yuki, Cook David, Bales Donald

机构信息

Argonne National Laboratory, Lemont, IL 60439, USA.

出版信息

Sensors (Basel). 2020 Sep 23;20(19):5463. doi: 10.3390/s20195463.

DOI:10.3390/s20195463
PMID:32977652
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7582789/
Abstract

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.

摘要

尽管在区域和全球尺度上预测生态系统功能和气候的能力已经很先进,但对于局部水和碳通量变化与大规模现象之间的关系却知之甚少。为了能够收集局部尺度生态系统功能的数据以支持此类研究,我们开发了EcoSpec系统,这是一种装备精良的遥感系统,在一个紧凑的塔架中安装了一台高光谱辐射计(350 - 2500纳米)以及五个光学和红外传感器。其定制软件控制传感器和系统组件的移动顺序和时间,并在塔架周围的12个位置进行测量。对使用该系统收集的数据进行处理以消除太阳角度效应,并将从数据中计算出的光谱植被指数(即归一化差异植被指数(NDVI)、归一化差异水指数(NDWI)、光化学反射指数(PRI)和水分胁迫指数(MSI))与光合有效辐射比例(fPAR)和冠层温度进行比较。结果表明,NDVI、NDWI和PRI与fPAR密切相关;MSI在日尺度上与冠层温度相关。这些相关性表明,这种近地表遥感系统将补充现有的观测站,以验证卫星遥感观测,并将局部和大规模现象联系起来,提高我们预测生态系统功能和气候的能力。该系统对于精准农业研究作物生长、检测病虫害以及比较品种性状也具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/fd692303f690/sensors-20-05463-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/f22c0903cd48/sensors-20-05463-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/977da6106bcb/sensors-20-05463-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/de45ae5a4f9b/sensors-20-05463-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/258842062134/sensors-20-05463-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/7d49445df633/sensors-20-05463-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/fd692303f690/sensors-20-05463-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/f22c0903cd48/sensors-20-05463-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/977da6106bcb/sensors-20-05463-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/de45ae5a4f9b/sensors-20-05463-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/258842062134/sensors-20-05463-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/7d49445df633/sensors-20-05463-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9f3/7582789/fd692303f690/sensors-20-05463-g006.jpg

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