Specific inherent optical properties of highly turbid productive water for retrieval of water quality after optical classification

Huang, Changchun; Chen, Xia; Li, Yunmei; Sun, Deyong; Li, Junsheng; Le, Chengfeng; Zhou, Liangchen; Zhang, Mingli; Xu, Long

doi:10.1007/s12665-014-3548-3

Cited by 9 publications

(4 citation statements)

References 49 publications

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“…Semianalytical approaches rely on radiative transfer theory and modeling the propagation of light in water, through the radiative transfer equation that connects inherent optical properties of lake water with its radiance levels [10]. Solving this equation via either look-up tables or inversion methods can lead to the estimation of Chl-a concentration.…”

Section: Related Workmentioning

confidence: 99%

A Deep Multitask Semisupervised Learning Approach for Chlorophyll-a Retrieval from Remote Sensing Images

2021

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This article addresses the scarcity of labeled data in multitemporal remote sensing image analysis, and especially in the context of Chlorophyll-a (Chl-a) estimation for inland water quality assessment. We propose a multitask CNN architecture that can exploit unlabeled satellite imagery and that can be generalized to other multitemporal remote sensing image analysis contexts where the target parameter exhibits seasonal fluctuations. Specifically, Chl-a estimation is set as the main task, and an unlabeled sample’s month classification is set as an auxiliary network task. The proposed approach is validated with multitemporal/spectral Sentinel-2 images of Lake Balik in Turkey using in situ measurements acquired during 2017–2019. We show that harnessing unlabeled data through multitask learning improves water quality estimation performance.

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Section: Related Workmentioning

confidence: 99%

A Deep Multitask Semisupervised Learning Approach for Chlorophyll-a Retrieval from Remote Sensing Images

2021

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“…The detailed steps and calculation method follows methods described by Huang [39] and Lee [40]. The absorption coefficient of pigment phytoplankton (aph), no-pigment matter (aNAP) and chromophoric dissolved organic matter (aCDOM) were measured using a quantitative membrane filter technique with spectrophotometer [41].…”

Section: Optical Property Measurementsmentioning

confidence: 99%

“…The concentration of phycocyanin (PC) was determined by spectrofluorimetry [43]. The concentrations of total suspended particulate matter (SPM), organic suspended matter (OSM), and inorganic suspended matter (ISM) were detected following the gravimetric method [41].…”

Section: Water Constituent Measurementmentioning

confidence: 99%

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Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China

et al. 2017

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Abstract:In situ measured values of particulate organic carbon (POC) in Taihu Lake and remote sensing reflectance observed by three satellite courses from 2014 to 2015 were used to develop an near infrared-red (NIR-Red) empirical algorithm of POC for the Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) satellite image. The performance of the POC algorithm is highly consistent with the in situ measured POC, with root mean square error percentage (RMSPs) of 38.9% and 31.5% for two independent validations, respectively. The MODIS-derived POC also shows an acceptable result, with RMSPs of 53.6% and 61.0% for two periods of match-up data. POC from 2005 to 2007 is much higher than it is from 2002 to 2004 and 2008 to 2013, due to a large area of algal bloom. Riverine flux is an important source of POC in Taihu Lake, especially in the lake's bank and bays. The influence of a terrigenous source of POC can reach the center lake during periods of heavy precipitation. Sediment resuspension is also a source of POC in the lake due to the area's high dynamic ratio (25.4) and wind speed. The source of POC in an inland shallow lake is particularly complex, and additional research on POC is needed to more clearly reveal its variation in inland water.

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Spatial variability of absorption coefficients over a biogeochemical gradient in a large and optically complex shallow lake

et al. 2015

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In order to improve robustness of remote sensing algorithms for lakes, it is vital to understand the variability of inherent optical properties (IOPs) and their mass‐specific representations (SIOPs). In this study, absorption coefficients for particulate and dissolved constituents were measured at 38 stations distributed over a biogeochemical gradient in Lake Balaton, Hungary. There was a large range of phytoplankton absorption (aph(λ)) over blue and red wavelengths (aph(440) = 0.11–4.39 m−1, aph(675) = 0.048–2.52 m−1), while there was less variability in chlorophyll‐specific phytoplankton absorption (a*ph(λ)) in the lake (a*ph(440) = 0.022 ± 0.0046 m2 mg−1, a*ph(675) = 0.010 ± 0.0020 m2 mg−1) and adjoining wetland system, Kis‐Balaton (a*ph(440) = 0.017 ± 0.0015 m2 mg−1, a*ph(675) = 0.0088 ± 0.0017 m2 mg−1). However, in the UV, a*ph(350) significantly increased with increasing distance from the main inflow (Zala River). This was likely due to variable production of photoprotective pigments (e.g., MAAs) in response to the decreasing gradient of colored dissolved organic matter (CDOM). The slope of CDOM absorption (SCDOM) also increased from west to east due to larger terrestrial CDOM input in the western basins. Absorption by nonalgal particles (aNAP(λ)) was highly influenced by inorganic particulates, as a result of the largely mineral sediments in Balaton. The relative contributions to the absorption budget varied more widely than oceans with a greater contribution from NAP (up to 30%), and wind speed affected the proportion attributed to NAP, phytoplankton, or CDOM. Ultimately, these data provide knowledge of the heterogeneity of (S)IOPs in Lake Balaton, suggesting the full range of variability must be considered for future improvement of analytical algorithms for constituent retrieval in inland waters.

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Specific inherent optical properties of highly turbid productive water for retrieval of water quality after optical classification

Cited by 9 publications

References 49 publications

A Deep Multitask Semisupervised Learning Approach for Chlorophyll-a Retrieval from Remote Sensing Images

A Deep Multitask Semisupervised Learning Approach for Chlorophyll-a Retrieval from Remote Sensing Images

Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China

Spatial variability of absorption coefficients over a biogeochemical gradient in a large and optically complex shallow lake

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