近实时卫星检测和监测水生藻类和蓝藻:如何将叶绿素 a 指数和水质采样相结合应用于得克萨斯州北部水库

IF 1.4 4区 地球科学 Q4 ENVIRONMENTAL SCIENCES
Victoria Stengel, Jessica M. Trevino, Tyler V. King, Scott D. Ducar, Stephen A. Hundt, Konrad C. Hafen, Christopher J. Churchill
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引用次数: 0

摘要

摘要水生藻类和蓝藻会损害水质,对人类和动物健康构成风险。为了确定水质状况并校准卫星对叶绿素-a 浓度的检测和估算,在哨兵-2 号卫星飞越水域的同时收集了若干现场水质指标,包括叶绿素-a、藻蓝蛋白、浊度、Secchi 深度、浮游植物分类和高光谱反射率。通过比较卫星图像和实地观测的叶绿素-a 浓度,评估了多种卫星叶绿素-a 检测指数的性能。使用 ACOLITE 大气校正法实施了 17 种叶绿素-a 光谱指数;使用 Sen2Cor 和 MAIN 大气校正法选出性能最佳的指数进行进一步评估。在所有水库取样点中,摩西三波段光谱指数与实地测量的叶绿素-a 浓度线性一致性最强(R2 = 0.70)。与开阔水域取样点相比,摩西三波段光谱指数与进水口取样点的叶绿素-a 实地测量值的线性一致性更好,因为进水口取样点的近水面水生叶绿素-a 浓度更高,整体叶绿素-a 高光谱反射信号更强。叶绿素-a 浓度估算值被应用于一个云计算遥感平台,该平台专为区域尺度遥感分析而设计,用于绘制主要位于德克萨斯州北部的 10 个研究水库的水生叶绿素-a 时空模式图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near real-time satellite detection and monitoring of aquatic algae and cyanobacteria: how a combination of chlorophyll-a indices and water-quality sampling was applied to north Texas reservoirs
Abstract. Aquatic algae and cyanobacteria can impair water-quality and pose risks to human and animal health. Several metrics of in-situ water-quality, including chlorophyll-a, phycocyanin, turbidity, Secchi depth, phytoplankton taxonomy, and hyperspectral reflectance, were collected in coordination with Sentinel-2 satellite overpasses to ascertain water-quality conditions and calibrate satellite detection and estimation of chlorophyll-a concentration. The performance of multiple satellite chlorophyll-a detection indices was evaluated by comparing satellite imagery to field observations of chlorophyll-a concentrations. Seventeen chlorophyll-a spectral indices were implemented using the ACOLITE atmosphere correction; the top performing indices were selected for further evaluation using the Sen2Cor and MAIN atmosphere corrections. The Moses three-band spectral index delivered the strongest linear agreement with field measurements of chlorophyll-a concentration across all reservoir sampling sites (R2  =  0.70). Compared to open-water sites, the Moses three-band spectral index delivered better linear agreement with chlorophyll-a field measurements at inlet sites where there was a greater abundance of near surface aquatic chlorophyll-a concentrations, and the overall chlorophyll-a hyperspectral reflectance signal was stronger. Chlorophyll-a concentration estimates were implemented in a cloud-computation remote sensing platform designed for regional scale remote sensing analysis to map spatiotemporal patterns of aquatic chlorophyll-a across 10 study reservoirs located primarily in north Texas.
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来源期刊
Journal of Applied Remote Sensing
Journal of Applied Remote Sensing 环境科学-成像科学与照相技术
CiteScore
3.40
自引率
11.80%
发文量
194
审稿时长
3 months
期刊介绍: The Journal of Applied Remote Sensing is a peer-reviewed journal that optimizes the communication of concepts, information, and progress among the remote sensing community.
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