Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image

The particulate backscattering coefficient (<italic>b</italic><sub>bp</sub>) plays an important role in the underwater light field. However, it is difficult to accurately estimate <italic>b</italic><sub>bp</sub>(<italic>&#x03BB;</italic>...

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Main Authors: Jiafeng Xu, Yingchun Bian, Heng Lyu, Song Miao, Yunmei Li, Huaiqing Liu, Jie Xu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9519559/
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spelling doaj-c07b522c6f83431eaecae7fc2ae427aa2021-09-09T23:00:18ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01148577859310.1109/JSTARS.2021.31062629519559Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI ImageJiafeng Xu0https://orcid.org/0000-0002-5515-7342Yingchun Bian1Heng Lyu2https://orcid.org/0000-0003-2844-3746Song Miao3Yunmei Li4https://orcid.org/0000-0001-8116-942XHuaiqing Liu5Jie Xu6https://orcid.org/0000-0002-5249-6197Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaKey Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing, ChinaThe particulate backscattering coefficient (<italic>b</italic><sub>bp</sub>) plays an important role in the underwater light field. However, it is difficult to accurately estimate <italic>b</italic><sub>bp</sub>(<italic>&#x03BB;</italic>) in turbid inland water with complex optical properties. To accurately estimate the backscattering coefficients in inland water, a simple classification method based on the shape of remote sensing reflectance was first proposed to distinguish two water types (i.e., water type 1 and water type 2) with different backscattering characteristics. Then, trigonometric functions were developed to simulate the backscattering coefficients at all bands in water type 1 and the backscattering coefficients in the visible band of water type 2, whereas a linear function was built to estimate the backscattering coefficients in the near-infrared band of water type 2. The proposed algorithm was compared with four state-of-the-art methods and validated by an independently measured dataset of three lakes in the middle and lower reaches of the Yangtze River in 2020. The results showed that the proposed algorithm performed well in inland waters, with all mean absolute percentage errors &lt; 40&#x0025; and root-mean-square errors &lt; 0.25 m<sup>&#x2212;1</sup>. Finally, the algorithm was applied to Ocean and Land Color Instrument images from 2016 to 2020 in Lake Taihu and Lake Hongze. It was found that the backscattering coefficients in Lake Taihu and Lake Hongze showed opposite seasonal variation trends, and the <italic>b</italic><sub>bp</sub>(676) in Lake Hongze began to decrease since 2017, whereas no obvious interannual variation was observed in Taihu Lake in recent five years.https://ieeexplore.ieee.org/document/9519559/Estimation algorithmsinland watersocean and land color instrument (OLCI) imagesparticulate backscattering coefficient
collection DOAJ
language English
format Article
sources DOAJ
author Jiafeng Xu
Yingchun Bian
Heng Lyu
Song Miao
Yunmei Li
Huaiqing Liu
Jie Xu
spellingShingle Jiafeng Xu
Yingchun Bian
Heng Lyu
Song Miao
Yunmei Li
Huaiqing Liu
Jie Xu
Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Estimation algorithms
inland waters
ocean and land color instrument (OLCI) images
particulate backscattering coefficient
author_facet Jiafeng Xu
Yingchun Bian
Heng Lyu
Song Miao
Yunmei Li
Huaiqing Liu
Jie Xu
author_sort Jiafeng Xu
title Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
title_short Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
title_full Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
title_fullStr Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
title_full_unstemmed Estimation of Particulate Backscattering Coefficient in Turbid Inland Water Using Sentinel 3A-OLCI Image
title_sort estimation of particulate backscattering coefficient in turbid inland water using sentinel 3a-olci image
publisher IEEE
series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
issn 2151-1535
publishDate 2021-01-01
description The particulate backscattering coefficient (<italic>b</italic><sub>bp</sub>) plays an important role in the underwater light field. However, it is difficult to accurately estimate <italic>b</italic><sub>bp</sub>(<italic>&#x03BB;</italic>) in turbid inland water with complex optical properties. To accurately estimate the backscattering coefficients in inland water, a simple classification method based on the shape of remote sensing reflectance was first proposed to distinguish two water types (i.e., water type 1 and water type 2) with different backscattering characteristics. Then, trigonometric functions were developed to simulate the backscattering coefficients at all bands in water type 1 and the backscattering coefficients in the visible band of water type 2, whereas a linear function was built to estimate the backscattering coefficients in the near-infrared band of water type 2. The proposed algorithm was compared with four state-of-the-art methods and validated by an independently measured dataset of three lakes in the middle and lower reaches of the Yangtze River in 2020. The results showed that the proposed algorithm performed well in inland waters, with all mean absolute percentage errors &lt; 40&#x0025; and root-mean-square errors &lt; 0.25 m<sup>&#x2212;1</sup>. Finally, the algorithm was applied to Ocean and Land Color Instrument images from 2016 to 2020 in Lake Taihu and Lake Hongze. It was found that the backscattering coefficients in Lake Taihu and Lake Hongze showed opposite seasonal variation trends, and the <italic>b</italic><sub>bp</sub>(676) in Lake Hongze began to decrease since 2017, whereas no obvious interannual variation was observed in Taihu Lake in recent five years.
topic Estimation algorithms
inland waters
ocean and land color instrument (OLCI) images
particulate backscattering coefficient
url https://ieeexplore.ieee.org/document/9519559/
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