The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Kun Shi - One of the best experts on this subject based on the ideXlab platform.
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Chromophoric dissolved organic matter in Inland Waters: Present knowledge and future challenges.
The Science of the total environment, 2020Co-Authors: Yunlin Zhang, Lei Zhou, Yongqiang Zhou, Liu-qing Zhang, Xiaolong Yao, Kun Shi, Erik Jeppesen, Weining ZhuAbstract:Chromophoric dissolved organic matter (CDOM) plays an important role in the biogeochemical cycle and energy flow of aquatic ecosystems. Thus, systematic and comprehensive understanding of CDOM dynamics is critically important for aquatic ecosystem management. CDOM spans multiple study fields, including analytical chemistry, biogeochemistry, water color remote sensing, and global environmental change. Here, we thoroughly summarize the progresses of recent studies focusing on the characterization, distribution, sources, composition, and fate of CDOM in Inland Waters. Characterization methods, remote sensing estimation, and biogeochemistry cycle processes were the hotspots of CDOM studies. Specifically, optical, isotope, and mass spectrometric techniques have been widely used to characterize CDOM abundance, composition, and sources. Remote sensing is an effective tool to map CDOM distribution with high temporal and spatial resolutions. CDOM dynamics are mainly determined by Watershed-related processes, including rainfall discharge, groundwater, wastewater discharges/effluents, and biogeochemical cycling occurring in soil and water bodies. We highlight the underlying mechanisms of the photochemical degradation and microbial decomposition of CDOM, and emphasize that photochemical and microbial processes of CDOM in Inland Waters accelerate nutrient cycling and regeneration in the water column and also exacerbate global warming by releasing greenhouse gases. Future study directions to improve the understanding of CDOM dynamics in Inland Waters are proposed. This review provides an interdisciplinary view and new insights on CDOM dynamics in Inland Waters.
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Remote sensing of cyanobacterial blooms in Inland Waters: present knowledge and future challenges
Science Bulletin, 2019Co-Authors: Kun Shi, Yunlin Zhang, Boqiang Qin, Botian ZhouAbstract:Abstract Timely monitoring, detection and quantification of cyanobacterial blooms are especially important for controlling public health risks and understanding aquatic ecosystem dynamics. Due to the advantages of simultaneous data acquisition over large geographical areas and high temporal coverage, remote sensing strongly facilitates cyanobacterial bloom monitoring in Inland Waters. We provide a comprehensive review regarding cyanobacterial bloom remote sensing in Inland Waters including cyanobacterial optical characteristics, operational remote sensing algorithms of chlorophyll, phycocyanin and cyanobacterial bloom areas, and satellite imaging applications. We conclude that there have many significant progresses in the remote sensing algorithm of cyanobacterial pigments over the past 30 years. The band ratio algorithms in the red and near-infrared (NIR) spectral regions have great potential for the remote estimation of chlorophyll a in eutrophic and hypereutrophic Inland Waters, and the floating algae index (FAI) is the most widely used spectral index for detecting dense cyanobacterial blooms. Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer) and MERIS (MEdium Resolution Imaging Spectrometer) are the most widely used products for monitoring the spatial and temporal dynamics of cyanobacteria in Inland Waters due to the appropriate temporal, spatial and spectral resolutions. Future work should primarily focus on the development of universal algorithms, remote retrievals of cyanobacterial blooms in oligotrophic Waters, and the algorithm applicability to mapping phycocyanin at a large spatial-temporal scale. The applications of satellite images will greatly improve our understanding of the driving mechanism of cyanobacterial blooms by combining numerical and ecosystem dynamics models.
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Remote estimation of cyanobacteria-dominance in Inland Waters.
Water research, 2015Co-Authors: Kun Shi, Yunlin Zhang, Xiaohan LiuAbstract:Abstract Remote sensing of the concentration ratio of phycocyanin (PC) to chlorophyll a ( Chl-a ) is important for water management, as it provides critical knowledge regarding the phytoplankton community. Using the observed in situ datasets, a simple empirical model was developed to estimate PC: Chl-a based on the band ratio index of R rs (550)/ R rs (620) ( R rs : remote sensing reflectance) ( R 2 = 0.84; RMSE = 1.01). This simple model exhibited relatively high validation accuracy using the independent validation dataset. In addition, the model can be successfully applied to AISA (Airborne Imaging Spectrometer for Application) image data, indicating the practicality of the developed model for determining the dominance of cyanobacteria among the total phytoplankton from airborne image data in Inland Waters. However, the present model cannot be used directly to estimate PC: Chl-a in extremely turbid Waters with total suspended matter (TSM) concentrations higher than 25 mg/l. For these Waters, the model parameters may require local optimization according to the conditions of the water under analysis. The findings of this study indicate that our proposed model is able to detect the dominance of cyanobacteria among the phytoplankton in Inland Waters, where the turbidity is not too much high. This study improves our understanding of the species composition of phytoplankton biomass in optically complex Inland bodies of water.
Takehiko Fukushima - One of the best experts on this subject based on the ideXlab platform.
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retrieval of inherent optical properties for turbid Inland Waters from remote sensing reflectance
IEEE Transactions on Geoscience and Remote Sensing, 2013Co-Authors: Wei Yang, Bunkei Matsushita, Jin Chen, Kazuya Yoshimura, Takehiko FukushimaAbstract:Remote estimation of inherent optical properties (IOPs) for water bodies cannot only provide indicators of water quality, but also be used in the study on biological and biogeochemical processes of Waters. The quasi-analytical algorithm (QAA) is a simple and effective method to retrieve IOPs from remote-sensing reflectance (Rrs). The QAA has been widely validated and applied in oceans, but its application in Inland Waters is far less extensive. In this paper, the QAA was enhanced to retrieve IOPs for turbid Inland Waters based on the bandwidths of Medium Resolution Imaging Spectrometer (MERIS). The enhancement was achieved by proposing a semi-analytical model to estimate the spectral slope of particle backscattering, as well as a novel estimation model for phytoplankton absorption coefficient at 443 nm. Two data sets (i.e., noise-free synthetic data and in-situ data) were collected to assess the performance of the enhanced algorithm. Results show that the algorithm yields almost error-free estimations for total absorption and backscattering coefficients and estimations for phytoplankton absorption at 443 nm with acceptable accuracy in the case of synthetic data set. For the in-situ data set, the algorithm retrieves the total absorption coefficients (ranging 0.337-8.331 m-1) with root-mean-square-error in log scale (RMSE) and bias in log scale lower than 0.130 and 0.094, respectively, and phytoplankton absorption at 443 nm (ranging 0.378-4.669 m-1) with RMSE and bias in log scale of 0.151 and 0.096, respectively. These results indicate the potential of the enhanced QAA to accurately retrieve the IOPs from MERIS satellite observations for Inland Waters.
Yunlin Zhang - One of the best experts on this subject based on the ideXlab platform.
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Chromophoric dissolved organic matter in Inland Waters: Present knowledge and future challenges.
The Science of the total environment, 2020Co-Authors: Yunlin Zhang, Lei Zhou, Yongqiang Zhou, Liu-qing Zhang, Xiaolong Yao, Kun Shi, Erik Jeppesen, Weining ZhuAbstract:Chromophoric dissolved organic matter (CDOM) plays an important role in the biogeochemical cycle and energy flow of aquatic ecosystems. Thus, systematic and comprehensive understanding of CDOM dynamics is critically important for aquatic ecosystem management. CDOM spans multiple study fields, including analytical chemistry, biogeochemistry, water color remote sensing, and global environmental change. Here, we thoroughly summarize the progresses of recent studies focusing on the characterization, distribution, sources, composition, and fate of CDOM in Inland Waters. Characterization methods, remote sensing estimation, and biogeochemistry cycle processes were the hotspots of CDOM studies. Specifically, optical, isotope, and mass spectrometric techniques have been widely used to characterize CDOM abundance, composition, and sources. Remote sensing is an effective tool to map CDOM distribution with high temporal and spatial resolutions. CDOM dynamics are mainly determined by Watershed-related processes, including rainfall discharge, groundwater, wastewater discharges/effluents, and biogeochemical cycling occurring in soil and water bodies. We highlight the underlying mechanisms of the photochemical degradation and microbial decomposition of CDOM, and emphasize that photochemical and microbial processes of CDOM in Inland Waters accelerate nutrient cycling and regeneration in the water column and also exacerbate global warming by releasing greenhouse gases. Future study directions to improve the understanding of CDOM dynamics in Inland Waters are proposed. This review provides an interdisciplinary view and new insights on CDOM dynamics in Inland Waters.
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Remote sensing of cyanobacterial blooms in Inland Waters: present knowledge and future challenges
Science Bulletin, 2019Co-Authors: Kun Shi, Yunlin Zhang, Boqiang Qin, Botian ZhouAbstract:Abstract Timely monitoring, detection and quantification of cyanobacterial blooms are especially important for controlling public health risks and understanding aquatic ecosystem dynamics. Due to the advantages of simultaneous data acquisition over large geographical areas and high temporal coverage, remote sensing strongly facilitates cyanobacterial bloom monitoring in Inland Waters. We provide a comprehensive review regarding cyanobacterial bloom remote sensing in Inland Waters including cyanobacterial optical characteristics, operational remote sensing algorithms of chlorophyll, phycocyanin and cyanobacterial bloom areas, and satellite imaging applications. We conclude that there have many significant progresses in the remote sensing algorithm of cyanobacterial pigments over the past 30 years. The band ratio algorithms in the red and near-infrared (NIR) spectral regions have great potential for the remote estimation of chlorophyll a in eutrophic and hypereutrophic Inland Waters, and the floating algae index (FAI) is the most widely used spectral index for detecting dense cyanobacterial blooms. Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer) and MERIS (MEdium Resolution Imaging Spectrometer) are the most widely used products for monitoring the spatial and temporal dynamics of cyanobacteria in Inland Waters due to the appropriate temporal, spatial and spectral resolutions. Future work should primarily focus on the development of universal algorithms, remote retrievals of cyanobacterial blooms in oligotrophic Waters, and the algorithm applicability to mapping phycocyanin at a large spatial-temporal scale. The applications of satellite images will greatly improve our understanding of the driving mechanism of cyanobacterial blooms by combining numerical and ecosystem dynamics models.
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Remote estimation of cyanobacteria-dominance in Inland Waters.
Water research, 2015Co-Authors: Kun Shi, Yunlin Zhang, Xiaohan LiuAbstract:Abstract Remote sensing of the concentration ratio of phycocyanin (PC) to chlorophyll a ( Chl-a ) is important for water management, as it provides critical knowledge regarding the phytoplankton community. Using the observed in situ datasets, a simple empirical model was developed to estimate PC: Chl-a based on the band ratio index of R rs (550)/ R rs (620) ( R rs : remote sensing reflectance) ( R 2 = 0.84; RMSE = 1.01). This simple model exhibited relatively high validation accuracy using the independent validation dataset. In addition, the model can be successfully applied to AISA (Airborne Imaging Spectrometer for Application) image data, indicating the practicality of the developed model for determining the dominance of cyanobacteria among the total phytoplankton from airborne image data in Inland Waters. However, the present model cannot be used directly to estimate PC: Chl-a in extremely turbid Waters with total suspended matter (TSM) concentrations higher than 25 mg/l. For these Waters, the model parameters may require local optimization according to the conditions of the water under analysis. The findings of this study indicate that our proposed model is able to detect the dominance of cyanobacteria among the phytoplankton in Inland Waters, where the turbidity is not too much high. This study improves our understanding of the species composition of phytoplankton biomass in optically complex Inland bodies of water.
Guibing Zhu - One of the best experts on this subject based on the ideXlab platform.
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ubiquitous anaerobic ammonium oxidation in Inland Waters of china an overlooked nitrous oxide mitigation process
Scientific Reports, 2015Co-Authors: Guibing Zhu, Shanyun Wang, Leiliu Zhou, Yu Wang, Siyan Zhao, Chao Xia, Weidong Wang, Rong Zhou, Chaoxu WangAbstract:Denitrification has long been regarded as the only pathway for terrestrial nitrogen (N) loss to the atmosphere. Here we demonstrate that large-scale anaerobic ammonium oxidation (anammox), an overlooked N loss process alternative to denitrification which bypasses nitrous oxide (N2O), is ubiquitous in Inland Waters of China and contributes significantly to N loss. Anammox rates in aquatic systems show different levels (1.0-975.9 mu mol N m(-2) h(-1), n = 256) with hotspots occurring at oxic-anoxic interfaces and harboring distinct biogeochemical and biogeographical features. Extrapolation of these results to the China-national level shows that anammox could contribute about 2.0 Tg N yr(-1), which equals averagely 11.4% of the total N loss from China's Inland Waters. Our results indicate that a significant amount of the nitrogen lost from Inland Waters bypasses denitrification, which is important for constructing more accurate climate models and may significantly reduce potential N2O emission risk at a large scale.
Peter D. Hunter - One of the best experts on this subject based on the ideXlab platform.
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Remote sensing of Inland Waters: Challenges, progress and future directions
Remote Sensing of Environment, 2015Co-Authors: Stephanie C. J. Palmer, Tiit Kutser, Peter D. HunterAbstract:Abstract Monitoring and understanding the physical, chemical and biological status of global Inland Waters are immensely important to scientists and policy makers alike. Whereas conventional monitoring approaches tend to be limited in terms of spatial coverage and temporal frequency, remote sensing has the potential to provide an invaluable complementary source of data at local to global scales. Furthermore, as sensors, methodologies, data availability and the network of researchers and engaged stakeholders in this field develop, increasingly widespread use of remote sensing for operational monitoring of Inland Waters can be envisaged. This special issue on Remote Sensing of Inland Waters comprises 16 articles on freshwater ecosystems around the world ranging from lakes and reservoirs to river systems using optical data from a range of in situ instruments as well as airborne and satellite platforms. The papers variably focus on the retrieval of in-water optical and biogeochemical parameters as well as information on the biophysical properties of shoreline and benthic vegetation. Methodological advances include refined approaches to adjacency correction, inversion-based retrieval models and in situ inherent optical property measurements in highly turbid Waters. Remote sensing data are used to evaluate models and theories of environmental drivers of change in a number of different aquatic ecosystems. The range of contributions to the special issue highlights not only the sophistication of methods and the diversity of applications currently being developed, but also the growing international community active in this field. In this introductory paper we briefly highlight the progress that the community has made over recent decades as well as the challenges that remain. It is argued that the operational use of remote sensing for Inland water monitoring is a realistic ambition if we can continue to build on these recent achievements.