Suppr超能文献

利用陆地卫星8号业务陆地成像仪监测饮用水水库中的藻华。

Monitoring Algal Blooms in drinking water reservoirs using the Landsat 8 Operational Land Imager.

作者信息

Keith Darryl, Rover Jennifer, Green Jason, Zalewsky Brian, Charpentier Mike, Thursby Glen, Bishop Joseph

机构信息

United States Environmental Protection Agency, Atlantic Ecology Division, Narragansett, Rhode Island 02882, USA.

United States Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, South Dakota 57198-0001, USA.

出版信息

Int J Remote Sens. 2018 Jan 29;39(9):2818-2846. doi: 10.1080/01431161.2018.1430912.

Abstract

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance (LSR) product and field-collected chlorophyll- (chl-) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl- concentrations using spectral data. We found that using the 3 band reflectance approach with a combination of OLI spectral bands 1, 3, and 5, produced the most promising results for accurately estimating chl- concentrations in lakes ( value of 0.66; RMSE value of 8.9 μg l). Using this model, we forecast the spatial and temporal variability of chl- for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.

摘要

在本研究中,我们证明了陆地卫星8号业务陆地成像仪(OLI)传感器是一种强大的工具,可提供有关饮用水水库状况的周期性和全系统信息。OLI是一种多光谱辐射计(空间分辨率为30米),它能够在空间和时间尺度上进行生态系统观测,为环境领域和水资源管理者提供了另一种监测水质变化的手段,而基于实地的监测则无法做到这一点。利用临时陆地表面反射率(LSR)产品以及从北卡罗来纳州和罗德岛州饮用水监测项目中实地采集的叶绿素(chl-)浓度数据,我们比较了五种利用光谱数据估算chl-浓度的既定方法。我们发现,使用由OLI光谱波段1、3和5组合而成的三波段反射率方法,在准确估算湖泊中的chl-浓度方面产生了最有前景的结果( 值为0.66;均方根误差值为8.9微克/升)。利用该模型,我们预测了乔丹湖(北卡罗来纳州皮埃蒙特地区的一个休闲和饮用水源)以及罗德岛州东南部几个供应饮用水的小池塘中chl-的时空变异性。

相似文献

1
Monitoring Algal Blooms in drinking water reservoirs using the Landsat 8 Operational Land Imager.
Int J Remote Sens. 2018 Jan 29;39(9):2818-2846. doi: 10.1080/01431161.2018.1430912.
2
Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea.
Environ Monit Assess. 2015 Jun;187(6):384. doi: 10.1007/s10661-015-4616-1. Epub 2015 May 29.
3
A Multiscale Mapping Assessment of Lake Champlain Cyanobacterial Harmful Algal Blooms.
Int J Environ Res Public Health. 2015 Sep 15;12(9):11560-78. doi: 10.3390/ijerph120911560.
5
A new approach to quantify chlorophyll-a over inland water targets based on multi-source remote sensing data.
Sci Total Environ. 2024 Jan 1;906:167631. doi: 10.1016/j.scitotenv.2023.167631. Epub 2023 Oct 6.
6
Water clarity mapping of global lakes using a novel hybrid deep-learning-based recurrent model with Landsat OLI images.
Water Res. 2022 May 15;215:118241. doi: 10.1016/j.watres.2022.118241. Epub 2022 Mar 1.
8
Ground-based remote sensing provides alternative to satellites for monitoring cyanobacteria in small lakes.
Water Res. 2023 Aug 15;242:120076. doi: 10.1016/j.watres.2023.120076. Epub 2023 May 23.
9
A unified model for high resolution mapping of global lake (>1 ha) clarity using Landsat imagery data.
Sci Total Environ. 2022 Mar 1;810:151188. doi: 10.1016/j.scitotenv.2021.151188. Epub 2021 Oct 25.

引用本文的文献

1
Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes.
Remote Sens (Basel). 2024 May 30;16(11):1-29. doi: 10.3390/rs16111977.
3
Simultaneous Removal of and 2,4,6-Trichlorophenol by UV/Persulfate Process.
Front Chem. 2020 Nov 4;8:591641. doi: 10.3389/fchem.2020.591641. eCollection 2020.

本文引用的文献

1
Polarized reflectance and transmittance properties of windblown sea surfaces.
Appl Opt. 2015 May 20;54(15):4828-49. doi: 10.1364/AO.54.004828.
4
Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate.
Proc Natl Acad Sci U S A. 2010 Oct 5;107(40):17073-8. doi: 10.1073/pnas.0913800107. Epub 2010 Sep 22.
5
Refractive indices of water and ice in the 0.65- to 2.5-µm spectral range.
Appl Opt. 1993 Jul 1;32(19):3531-40. doi: 10.1364/AO.32.003531.
6
Correction of Sun glint Contamination on the SeaWiFS Ocean and Atmosphere Products.
Appl Opt. 2001 Sep 20;40(27):4790-8. doi: 10.1364/ao.40.004790.
7
Atmospheric correction of satellite ocean color imagery: the black pixel assumption.
Appl Opt. 2000 Jul 20;39(21):3582-91. doi: 10.1364/ao.39.003582.
8
Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters.
Appl Opt. 2000 Feb 20;39(6):897-912. doi: 10.1364/ao.39.000897.
9
Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements.
Appl Opt. 1997 Nov 20;36(33):8710-23. doi: 10.1364/ao.36.008710.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验