为潮汐和河口系统开发统一遥感和水质数据的 EstuarySAT 数据库。

IF 3 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Water Pub Date : 2024-09-25 DOI:10.3390/w16192721
Steven A Rego, Naomi E Detenbeck, Xiao Shen
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引用次数: 0

摘要

研究人员和环境管理人员需要跨度长的大型数据集,以准确评估淡水和河口水域当前和历史的水质状况。利用遥感数据,我们可以同时勘测许多水体,并更频繁地评估水质状况。将现有和历史水质数据与遥感图像结合到一个统一的数据库中,可使研究人员改进遥感算法,提高对造成水华的机制的认识。我们报告了水质数据库 "EstuarySAT "的开发情况,该数据库结合了来自哨兵-2 多光谱仪器(MSI)遥感平台的数据和整个美国沿海地区的水质数据。Estuary SAT 建立在 AquaSat 创建者开发的现有数据库和一套方法的基础上,AquaSat 的关注区域主要是美国较大的淡水湖。遵循相同的基本方法,EstuarySAT 使用开源工具:R v.3.24+(统计软件)、Python(动态编程环境)和谷歌地球引擎 (GEE),为较小的沿海河口和淡水潮汐河流系统开发了一个水质数据和遥感图像组合数据库 (EstuarySAT)。Estuary SAT 填补了淡水和河口水体之间存在的数据空白。与 AquaSat 使用的 Landsat 平台(30 米像素分辨率)相比,Sentinel-2 的空间分辨率更高(10 米像素图像分辨率),因此我们能够对较小的系统进行评估。此外,哨兵-2 号卫星的重访(过站)频率更高,每 5 到 10 天一次,而大地遥感卫星 7 号每 17 天一次。EstuarySAT 包含来自 23 个单独水质数据源的公开水质数据,时间跨度为 1984-2021 年,并与 Sentinel-2 2015-2021 年的图像进行空间匹配。EstuarySAT 目前包含分布在美国沿海的 299,851 个匹配观测数据。EstuarySAT 的主要重点是收集叶绿素数据,但也包含其他辅助水质数据,包括温度、盐度、pH 值、溶解氧、溶解有机碳和浊度(如有)。与其他用于开发预测性叶绿素算法的海洋颜色数据库相比,该沿岸数据库包含的光谱剖面 更典型地反映了以 CDOM 为主导的系统。该数据库可以帮助研究人员和管理人员评估藻华成因和预测未来藻华的发生。
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EstuarySAT Database Development of Harmonized Remote Sensing and Water Quality Data for Tidal and Estuarine Systems.

Researchers and environmental managers need big datasets spanning long time periods to accurately assess current and historical water quality conditions in fresh and estuarine waters. Using remote sensing data, we can survey many water bodies simultaneously and evaluate water quality conditions with greater frequency. The combination of existing and historical water quality data with remote sensing imagery into a unified database allows researchers to improve remote sensing algorithms and improves understanding of mechanisms causing blooms. We report on the development of a water quality database "EstuarySAT" which combines data from the Sentinel-2 multi-spectral instrument (MSI) remote sensing platform and water quality data throughout the coastal USA. EstuarySAT builds upon an existing database and set of methods developed by the creators of AquaSat, whose region of interest is primarily larger freshwater lakes in the USA. Following the same basic methods, EstuarySAT utilizes open-source tools: R v. 3.24+ (statistical software), Python (dynamic programming environment), and Google Earth Engine (GEE) to develop a combined water quality data and remote sensing imagery database (EstuarySAT) for smaller coastal estuarine and freshwater tidal riverine systems. EstuarySAT fills a data gap that exists between freshwater and estuarine water bodies. We are able to evaluate smaller systems due to the higher spatial resolution of Sentinel-2 (10 m pixel image resolution) vs. the Landsat platform used by AquaSat (30 m pixel resolution). Sentinel-2 also has a more frequent revisit (overpass) schedule of every 5 to 10 days vs. Landsat 7 which is every 17 days. EstuarySAT incorporates publicly available water quality data from 23 individual water quality data sources spanning 1984-2021 and spatially matches them with Sentinel-2 imagery from 2015-2021. EstuarySAT currently contains 299,851 matched observations distributed across the coastal USA. EstuarySAT's primary focus is on collecting chlorophyll data; however, it also contains other ancillary water quality data, including temperature, salinity, pH, dissolved oxygen, dissolved organic carbon, and turbidity (where available). As compared to other ocean color databases used for developing predictive chlorophyll algorithms, this coastal database contains spectral profiles more typical of CDOM-dominated systems. This database can assist researchers and managers in evaluating algal bloom causes and predicting the occurrence of future blooms.

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来源期刊
Water
Water WATER RESOURCES-
CiteScore
5.80
自引率
14.70%
发文量
3491
审稿时长
19.85 days
期刊介绍: Water (ISSN 2073-4441) is an international and cross-disciplinary scholarly journal covering all aspects of water including water science and technology, and the hydrology, ecology and management of water resources. It publishes regular research papers, critical reviews and short communications, and there is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles. Computed data or files regarding the full details of the experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.
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