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A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone SCIE
期刊论文 | 2021 , 42 (20) , 8004-8033 | INTERNATIONAL JOURNAL OF REMOTE SENSING
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Abstract :

A new semi-analytical algorithm that retrieves the total concentration of suspended matter (TSM) was derived from the China Eastern Coastal Zone using multiple ocean colour instruments including the Visible Infrared Imaging Radiometer (VIIRS), the Moderate-resolution Imaging Spectroradiometer (MODIS), and the Medium Resolution Spectral Imager II (MERSI II). The algorithm in one model derives TSM concentration (C-TSM) from satellite inherent optical properties products for clear and moderately turbid water. For turbid waters, a second model with a four-band approach was used. The two model algorithms were combined into one algorithm using a linking weighted function to generate a smooth C-TSM for clear and turbid water and for water with intermediate transparency. Compared to eight existing algorithms, our new algorithm performed better with a wide dynamic range for the C-TSM retrievals. The mean absolute percent difference was 28.22% for the CECZ data and the C-TSM varied from 0.5 mg l(-1) to 2435.4 mg l(-1). New algorithm decreased the MAPD by >11% for the C-TSM retrievals compared to the eight existing algorithms. Furthermore, when new algorithm was tested with a synthetic data set that had been contaminated with residual error, it exhibited more residual error tolerance than the other algorithms when retrieving C-TSM, which agreed well with the results provided by a multi-mission consistency analysis. These results indicate that new algorithm could provide accurate and consistent multi-mission C-TSM from turbid coastal water with a widely varying range of C-TSM.

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GB/T 7714 Liu, Zhongli , Chen, Jun , Cui, Tingwei et al. A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone [J]. | INTERNATIONAL JOURNAL OF REMOTE SENSING , 2021 , 42 (20) : 8004-8033 .
MLA Liu, Zhongli et al. "A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone" . | INTERNATIONAL JOURNAL OF REMOTE SENSING 42 . 20 (2021) : 8004-8033 .
APA Liu, Zhongli , Chen, Jun , Cui, Tingwei , Tang, Junwu , Wang, Lin . A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone . | INTERNATIONAL JOURNAL OF REMOTE SENSING , 2021 , 42 (20) , 8004-8033 .
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An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters SCIE
期刊论文 | 2021 , 14 , 6596-6607 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
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Being able to accurately estimate inherent optical properties (IOPs) at long time scales is key to comprehending the aquatic biological and biogeochemical responses to long-term global climate change. We employed the near-infrared band and combined it with four "common bands" at visible wavelengths (around 443, 490, 551, and 670 nm) to adjust the IOPs data processing system, IDAS(v2). We applied the IDAS(v2) algorithm further to correct for the residual error in images of turbid waters. We evaluated the performance of the IDAS(v2) algorithm using datasets covering a wide range of natural water types from clear open ocean to turbid coastal and inland waters. Due to the water-leaving signals' sensitivity to the optically significant constituents of highly turbid waters, the near-infrared band was very important for retrieving IOPs from those waters. In our analysis, we found that the IDAS(v2) algorithm provided IOPs data with <28.36% uncertainty for oceanic waters and <37.83% uncertainty for inland waters, which was much more effective than what a quasi-analytical algorithm provided. Moreover, the near-infrared band was better at removing the residual error and partial intermission bias in satellite remote sensing reflectance (R-rs) data because of the strong absorption of pure water. We tested the IDAS(v2) algorithm with numerically simulated and satellite observed data of turbid water. After applying IDAS(v2), the IOPs data were accurately determined from R-rs data contaminated by the residual error. Furthermore, the mean intermission difference between Medium Resolution Spectral Imager 2 and Visible Infrared Imaging Radiometer R-rs data at 443 and 551 nm decreased from 8%-25% to 1%-9%. These results suggest that we can accurately estimate IOPs data for natural waters including naturally clear and turbid waters.

Keyword :

Absorption Water Backscatter natural turbid water Adaptive optics IDAS inherent optical property Optical imaging Optical sensors Lakes

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GB/T 7714 Chen, Jun , Quan, Wenting , Duan, Hongtao et al. An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters [J]. | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2021 , 14 : 6596-6607 .
MLA Chen, Jun et al. "An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters" . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 14 (2021) : 6596-6607 .
APA Chen, Jun , Quan, Wenting , Duan, Hongtao , Xing, Qianguo , Xu, Na . An Improved Inherent Optical Properties Data Processing System for Residual Error Correction in Turbid Natural Waters . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2021 , 14 , 6596-6607 .
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Sun glint correction with an inherent optical properties data processing system EI SCIE
期刊论文 | 2021 , 42 (2) , 617-638 | International Journal of Remote Sensing
WoS CC Cited Count: 1
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Frequent and extensive sun glint is a serious obstacle to real-time monitoring of ocean colour anomalies. We semi-analytically adjust an inherent optical properties (IOPs) data processing system for the open ocean to correct for sun glint (called ‘IDAS-SGC’) and for remote sensing reflectance (R rs) and IOPs retrievals. Tests with synthetic data validated the effectiveness of our algorithm in deriving ocean colour data from severely glint-contaminated images to produce high quality images. Evaluating results from single mission images suggested that our approach provides spatially smooth and consistent ocean colour products from both severe glint and glint-free regions for Visible Infrared Imaging Radiometer Suite and for Medium Resolution Spectral Imager II instruments. Specifically, complete coverage of circulation-caused ocean colour anomalies can be recovered from a single severe sun glint image. Comparing multi-mission images found that the inter-mission consistency for IDAS-SGC R rs in sun glint regions is comparable with the inter-mission consistency in glint-free regions. Furthermore, we evaluate the performance of the Cox-Munk algorithm for sun glint estimation, and we find that our IDAS-SGC algorithm is more effective than the Cox-Munk algorithm in deriving R rs products from severe sun glint regions due to the absence of accurate real-time wind data. Our results suggest that the IDAS-SGC algorithm obtains meaningful ocean colour products from sun glint-contaminated images of the open oceans. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Keyword :

Color Oceanography Remote sensing Thermography (imaging) Data handling Spectroscopy

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GB/T 7714 Chen, Jun , He, Xianqiang , Liu, Zhongli et al. Sun glint correction with an inherent optical properties data processing system [J]. | International Journal of Remote Sensing , 2021 , 42 (2) : 617-638 .
MLA Chen, Jun et al. "Sun glint correction with an inherent optical properties data processing system" . | International Journal of Remote Sensing 42 . 2 (2021) : 617-638 .
APA Chen, Jun , He, Xianqiang , Liu, Zhongli , Lin, Nan , Xing, Qianguo , Pan, Delu . Sun glint correction with an inherent optical properties data processing system . | International Journal of Remote Sensing , 2021 , 42 (2) , 617-638 .
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An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China EI SCIE
期刊论文 | 2020 , 12 (10) | WATER
WoS CC Cited Count: 6
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Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the suppression of coastal total suspended matter (TSM) on the Chl-a optical characteristics and developed an improved model using the imagery from a hyper-spectrometer mounted on an unmanned aerial vehicle (UAV). The new model was applied to estimate the spatiotemporal distribution of Chl-a concentration in coastal waters of Qingdao on 17 December 2018, 22 March 2019, and 20 July 2019. Compared with the previous models, the correlation coefficients (R-2) of Chl-a concentrations retrieved by the new model and in situ measurements were greatly improved, proving that the new model shows a better performance in retrieving coastal Chl-a concentration. On this basis, the spatiotemporal variations of Chl-a in Qingdao coastal waters were analyzed, showing that the spatial variation is mainly related to the TSM concentration, wind waves, and aquaculture, and the temporal variation is mainly influenced by the sea surface temperature (SST), sea surface salinity (SSS), and human activities.

Keyword :

bio-optical model coastal water chlorophyll-a concentration spectral correction spatiotemporal variation Qingdao UAV-borne hyper-spectrometer

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GB/T 7714 Gai, Yingying , Yu, Dingfeng , Zhou, Yan et al. An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China [J]. | WATER , 2020 , 12 (10) .
MLA Gai, Yingying et al. "An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China" . | WATER 12 . 10 (2020) .
APA Gai, Yingying , Yu, Dingfeng , Zhou, Yan , Yang, Lei , Chen, Chao , Chen, Jun . An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China . | WATER , 2020 , 12 (10) .
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Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms SCIE Scopus
期刊论文 | 2019 , 231 , 111279 | REMOTE SENSING OF ENVIRONMENT
WoS CC Cited Count: 5 SCOPUS Cited Count: 6
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Abstract :

Multi-sensor remote sensing is a critical part of the surveillance of coastal ocean for hazard management. The world's largest green macroalgae blooms (green tide) in the Yellow Sea since 2007 are caused by the macroalgae of Ulva, which are disposed as biofoulings into sea water when workers recycle seaweed (Porphyra) farming facilities. We traced the development processes of seaweed cultivation in which area since 2000 and the variation in macroalgal blooms since 2007 through multi-sensors (satellite, Unmanned Aerial Vehicle, and ground spectroradiometer) remote sensing in this study. We found that the sudden occurrence of large-scale green tide in 2007 and the increasing trend since that year were caused by the seaweed aquaculture in a specific mode at specific locations. A numerical simulation and satellite observations on the relationship between the timing of recycling seaweed facilities and the volume of green tide suggest that the green tide is manageable. Adoption of multi-sensor, multi-scale, and multi-temporal observations, translocating seaweed farming sites, and changing the cultivation mode are deemed as key tools for controlling the green tide and sustaining the seaweed aqua culture.

Keyword :

Multi-sensor observation Marine hazard Floating algae Human activity Seaweed cultivation The Yellow Sea

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GB/T 7714 Xing, QG , An, DY , Zheng, XY et al. Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms [J]. | REMOTE SENSING OF ENVIRONMENT , 2019 , 231 : 111279 .
MLA Xing, QG et al. "Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms" . | REMOTE SENSING OF ENVIRONMENT 231 (2019) : 111279 .
APA Xing, QG , An, DY , Zheng, XY , Wei, ZN , Wang, XH , Li, L et al. Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms . | REMOTE SENSING OF ENVIRONMENT , 2019 , 231 , 111279 .
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A Secchi Depth Algorithm Considering the Residual Error in Satellite Remote Sensing Reflectance Data EI SCIE Scopus
期刊论文 | 2019 , 11 (16) , 1948 | REMOTE SENSING | IF: 4.509
WoS CC Cited Count: 4 SCOPUS Cited Count: 4
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A scheme to semi-analytically derive waters' Secchi depth (Z(sd)) from remote sensing reflectance (R-rs) considering the effects of the residual errors in satellite R-rs was developed for the China Eastern Coastal Zone (CECZ). This approach was evaluated and compared against three existing algorithms using field measurements. As it was challenging to provide the accurately inherent optical properties data for running the three existing algorithms in the extremely turbid waters, the new developed algorithm worked more effective than the latter. Moreover, with both synthetic and match-up data, the results indicated that the proposed algorithm was able to minimize some residual errors in R-rs, and thus could generate inter-mission consistent Z(sd) results from two ocean color missions. Finally, after application of new model to satellite images, we presented the spatial and temporal variations of Secchi depth and trophic state in the CECZ during 2002-2014. The study led to several findings: Firstly, the Z(sd)-based trophic state index (TSI) in the East China Sea first increased since 2002, and then gradually dropped during 2008-2014. Secondly, more and more waters within 30-35 m and 20-25 m isobaths were deteriorating from oligotrophic to mesotrophic type and from mesotrophic to eutrophic water, respectively, during 2002-2014. Lastly, the TSI increased on average 0.091 and 0.286 m per year respectively in Bohai Sea and Yellow Sea since 2002, and it might only take 14 and 67 years for Bohai Sea and Yellow Sea to deteriorate from mesotrophic to eutrophic water, following their current yearly deterioration rate and trophic trend. These results highlighted the importance to make some strict regulations for protecting the aquatic environment in the CECZ.

Keyword :

china eastern coastal zone optically complex water remote sensing Secchi depth trophic state index

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GB/T 7714 Chen, J , Han, QJ , Chen, YL et al. A Secchi Depth Algorithm Considering the Residual Error in Satellite Remote Sensing Reflectance Data [J]. | REMOTE SENSING , 2019 , 11 (16) : 1948 .
MLA Chen, J et al. "A Secchi Depth Algorithm Considering the Residual Error in Satellite Remote Sensing Reflectance Data" . | REMOTE SENSING 11 . 16 (2019) : 1948 .
APA Chen, J , Han, QJ , Chen, YL , Li, YD . A Secchi Depth Algorithm Considering the Residual Error in Satellite Remote Sensing Reflectance Data . | REMOTE SENSING , 2019 , 11 (16) , 1948 .
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Deriving colored dissolved organic matter absorption coefficient from ocean color with a neural quasi-analytical algorithm SCIE Scopus
期刊论文 | 2017 , 122 (11) , 8543-8556 | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS | IF: 2.711
WoS CC Cited Count: 8 SCOPUS Cited Count: 8
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The objective of this study is to develop an approach to estimate the gelbstoff absorption coefficient (a(g)) from remote sensing reflectance (R-rs). This approach includes two components: the inherent optical properties are semianalytically derived from the R-rs by a neural quasianalytical algorithm (NQAA), and then the derivations are semianalytically extended to a(g) estimations using a band difference approach. This method is then evaluated with the various type of ocean color data including synthetic, field measured, and satellite-observed data. The results show that the method can produce an excellent quantitative agreement between the estimated and known a(g) in ocean waters with a wide range of optical properties, while significantly reducing the effects of residual error in SeaWiFS R-rs, primarily from the imperfect atmospheric correction algorithm on the retrieval of a(g) in the clear open oceans. Furthermore, with the application of this new algorithm, the SeaWiFS a(g) products exhibit more spatially and temporally uniform results than the band ratio approach-based a(g) retrieval algorithm. These results indicate that the new algorithm is an encouraging approach to process ocean color images for a(g) retrieval, although a greater number of independent tests with in situ and satellite data are required to further validate and improve this approach.

Keyword :

neural quasi-analytical algorithm SeaWiFS residual error gelbstoff absorption coefficient inherent optical properties

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GB/T 7714 Chen, Jun , He, Xianqiang , Zhou, Bin et al. Deriving colored dissolved organic matter absorption coefficient from ocean color with a neural quasi-analytical algorithm [J]. | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2017 , 122 (11) : 8543-8556 .
MLA Chen, Jun et al. "Deriving colored dissolved organic matter absorption coefficient from ocean color with a neural quasi-analytical algorithm" . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 122 . 11 (2017) : 8543-8556 .
APA Chen, Jun , He, Xianqiang , Zhou, Bin , Pan, Delu . Deriving colored dissolved organic matter absorption coefficient from ocean color with a neural quasi-analytical algorithm . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2017 , 122 (11) , 8543-8556 .
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A Spectrally Selective Attenuation Mechanism-Based K-par Algorithm for Biomass Heating Effect Simulation in the Open Ocean SCIE Scopus
期刊论文 | 2017 , 122 (12) , 9370-9386 | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS | IF: 2.711
WoS CC Cited Count: 4 SCOPUS Cited Count: 2
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Quantifying the diffuse attenuation coefficient of the photosynthetically available radiation (K-par) can improve our knowledge of euphotic depth (Z(eu)) and biomass heating effects in the upper layers of oceans. An algorithm to semianalytically derive K-par from remote sensing reflectance (R-rs) is developed for the global open oceans. This algorithm includes the following two portions: (1) a neural network model for deriving the diffuse attention coefficients (K-d) that considers the residual error in satellite R-rs, and (2) a three band depth-dependent K-par algorithm (TDKA) for describing the spectrally selective attenuation mechanism of underwater solar radiation in the open oceans. This algorithm is evaluated with both in situ PAR profile data and satellite images, and the results show that it can produce acceptable PAR profile estimations while clearly removing the impacts of satellite residual errors on K-par estimations. Furthermore, the performance of the TDKA algorithm is evaluated by its applicability in Z(eu) derivation and mean temperature within a mixed layer depth (T-ML) simulation, and the results show that it can significantly decrease the uncertainty in both compared with the classical chlorophyll-a concentration-based K-par algorithm. Finally, the TDKA algorithm is applied in simulating biomass heating effects in the Sargasso Sea near Bermuda, with new K-par data it is found that the biomass heating effects can lead to a 3.4 degrees C maximum positive difference in temperature in the upper layers but could result in a 0.67 degrees C maximum negative difference in temperature in the deep layers.

Keyword :

photosynthetically available radiation ocean color euphotic depth diffuse attenuation coefficient biomass heating effects

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GB/T 7714 Chen, Jun , Zhang, Xiangguang , Xing, Xiaogang et al. A Spectrally Selective Attenuation Mechanism-Based K-par Algorithm for Biomass Heating Effect Simulation in the Open Ocean [J]. | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2017 , 122 (12) : 9370-9386 .
MLA Chen, Jun et al. "A Spectrally Selective Attenuation Mechanism-Based K-par Algorithm for Biomass Heating Effect Simulation in the Open Ocean" . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 122 . 12 (2017) : 9370-9386 .
APA Chen, Jun , Zhang, Xiangguang , Xing, Xiaogang , Ishizaka, Joji , Yu, Zhifeng . A Spectrally Selective Attenuation Mechanism-Based K-par Algorithm for Biomass Heating Effect Simulation in the Open Ocean . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2017 , 122 (12) , 9370-9386 .
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Improving satellite data products for open oceans with a scheme to correct the residual errors in remote sensing reflectance SCIE Scopus
期刊论文 | 2016 , 121 (6) , 3866-3886 | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS | IF: 2.939
WoS CC Cited Count: 11 SCOPUS Cited Count: 13
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An approach to semianalytically derive waters' inherent optical properties (IOPs) from remote sensing reflectance (R-rs) and at the same time to take into account the residual errors in satellite R-rs is developed for open-ocean clear waters where aerosols are likely of marine origin. This approach has two components: (1) a scheme of combining a neural network and an algebraic solution for the derivation of IOPs, and (2) relationships between R-rs residual errors at 670 nm and other spectral bands. This approach is evaluated with both synthetic and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data, and the results show that it can significantly reduce the effects of residual errors in R-rs on the retrieval of IOPs, and at the same time remove partially the R-rs residual errors for "low-quality'' and "high-quality'' data defined in this study. Furthermore, more consistent estimation of chlorophyll concentrations between the empirical blue-green ratio and band-difference algorithms can be derived from the corrected "low-quality'' and "high-quality'' R-rs. These results suggest that it is possible to improve both data quality and quantity of satellite-retrieved R-rs over clear open-ocean waters with a step considering the spectral relationships of the residual errors in R-rs after the default atmospheric correction procedure and without fixing R-rs at 670 nm to one value for clear waters in a small region such as 3 x 3 box.

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GB/T 7714 Chen, J , Lee, Z , Hu, CM et al. Improving satellite data products for open oceans with a scheme to correct the residual errors in remote sensing reflectance [J]. | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2016 , 121 (6) : 3866-3886 .
MLA Chen, J et al. "Improving satellite data products for open oceans with a scheme to correct the residual errors in remote sensing reflectance" . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 121 . 6 (2016) : 3866-3886 .
APA Chen, J , Lee, Z , Hu, CM , Wei, JW . Improving satellite data products for open oceans with a scheme to correct the residual errors in remote sensing reflectance . | JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS , 2016 , 121 (6) , 3866-3886 .
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On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain EI SCIE Scopus Pubmed
期刊论文 | 2016 , 55 (7) , 1738-1750 | APPLIED OPTICS | IF: 1.65
WoS CC Cited Count: 22 SCOPUS Cited Count: 23
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We evaluated three key components in modeling hyperspectral remote-sensing reflectance in the visible to short-wave-infrared (Vis-SWIR) domain of high-sediment-load (HSL) waters, which are the relationship between remote-sensing reflectance (R-rs) and inherent optical properties (IOPs), the absorption coefficient spectrum of pure water (a(w)) in the IR-SWIR region, and the spectral variation of sediment absorption coefficient (a(sed)). Results from this study indicate that it is necessary to use a more generalized R-rs-IOP model to describe the spectral variation of R-rs of HSL waters from Vis to SWIR; otherwise it may result in a spectrally distorted R-rs spectrum if a constant model parameter is used. For hyperspectral a(w) in the IR-SWIR domain, the values reported in Kou et al. (1993) provided a much better match with the spectral variation of R-rs in this spectral range compared to that of Segelstein (1981). For a(sed) spectrum, an empirical a(sed) spectral shape derived from sample measurements is found working much better than the traditional exponential-decay function of wavelength in modeling the spectral variation of R-rs in the visible domain. These results would improve our understanding of the spectral signatures of R-rs of HSL waters in the Vis-SWIR domain and subsequently improve the retrieval of IOPs from ocean color remote sensing, which could further help the estimation of sediment loading of such waters. Limitations in estimating chlorophyll concentration in such waters are also discussed. (C) 2016 Optical Society of America

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GB/T 7714 Lee, Z , Shang, SL , Lin, G et al. On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain [J]. | APPLIED OPTICS , 2016 , 55 (7) : 1738-1750 .
MLA Lee, Z et al. "On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain" . | APPLIED OPTICS 55 . 7 (2016) : 1738-1750 .
APA Lee, Z , Shang, SL , Lin, G , Chen, J , Doxaran, D . On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain . | APPLIED OPTICS , 2016 , 55 (7) , 1738-1750 .
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