期刊
FRONTIERS IN ENVIRONMENTAL SCIENCE
卷 9, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fenvs.2021.674247
关键词
multispectral; water quality; chlorophyll a; total suspended solids; unoccupied aircraft system; drones; coastal
资金
- Maryland Sea Grant from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce [NA18OAR4170070, SA75281900-J]
- Mid-Shore Chapter of the Izaak Walton League
- Horn Point Laboratory
Unoccupied aircraft systems equipped with multispectral sensors can be used to derive water quality properties in coastal waters. Removal of surface reflected light from total UAS radiance measurements improves accuracy in water quality estimates. Multiple linear regressions applied to UAS derived measurements result in comparable relative error to existing coastal water quality algorithms, providing guidance for future improvements in monitoring water quality.
Unoccupied aircraft systems (UAS, or drones) equipped with off-the-shelf multispectral sensors originally designed for terrestrial applications can also be used to derive water quality properties in coastal waters. The at-sensor total radiance a UAS measured constitutes the sum of water-leaving radiance (L-W) and incident radiance reflected off the sea surface into the detector's field of view (L-SR). L-W is radiance that emanates from the water and contains a spectral shape and magnitude governed by optically active water constituents interacting with downwelling irradiance while L-SR is independent of water constituents and is instead governed by a given sea-state surface reflecting light; a familiar example is sun glint. Failure to accurately account for L-SR can significantly influence Rrs, resulting in inaccurate water quality estimates once algorithms are applied. The objective of this paper is to evaluate the efficacy of methods that remove L-SR from total UAS radiance measurements in order to derive more accurate remotely sensed retrievals of scientifically valuable in-water constituents. UAS derived radiometric measurements are evaluated against in situ hyperspectral Rrs measurements to determine the best performing method of estimating and removing surface reflected light and derived water quality estimates. It is recommended to use a pixel-based approach that exploits the high absorption of water at NIR wavelengths to estimate and remove L-SR. Multiple linear regressions applied to UAS derived Rrs measurements and in situ chlorophyll a and total suspended solid concentrations resulted in 37 and 9% relative error, respectively, which is comparable to coastal water quality algorithms found in the literature. Future research could account for the high resolution and multi-angular aspect of L-SR by using a combination of photogrammetry and radiometry techniques. Management implications from this research include improved water quality monitoring of coastal and inland water bodies in order to effectively track trends, identify and mitigate pollution sources, and discern potential human health risks.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据