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Remote estimation of biomass of Ulva prolifera macroalgae in the Yellow Sea
2017
Remote Sensing of Environment
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Since 2008, macroalgal blooms of Ulva prolifera (also called green tides) occurred every summer in the Yellow Sea (YS), causing environmental and economic problems. ...
The lab-based model has been validated with in situ measurements, with an estimated relative uncertainty of b 16% for algae with FAI values b0.2 (corresponding to ~2 kg/m 2 biomass and accounting for N ...
Zhongwei Huang, and Ms. Bingqing Huang for their help in the laboratory and in situ experiment. ...
doi:10.1016/j.rse.2017.01.037
fatcat:2fccxnbbzfaxbojf54iwrxznfy
World's largest macroalgal bloom caused by expansion of seaweed aquaculture in China
2009
Marine Pollution Bulletin
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Acknowledgements We thank Shanglin Wang for the photo of P. yezoensis aquaculture and Peter Thompson and Ming Feng of CSIRO for reviewing the manuscript and for helpful discussions on prevailing ocean ...
Tennille Irvine of CSIRO helped prepare some of the figures. ...
Results
The pathway of green-tide Analysis of the remotely sensed images of the Yellow Sea off north eastern China ( Fig. 2a-f ) confirmed the possibility of non-local sources for the Qingdao green-tide ...
doi:10.1016/j.marpolbul.2009.01.013
pmid:19261301
fatcat:l3ydlawxsfh75huuklqtoqxm2i
Research on the dissipation of green tide and its influencing factors in the Yellow Sea based on Google Earth Engine
2021
Marine Pollution Bulletin
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Since 2007, the outbreak of green tides has become the most serious ecological problem in the Yellow Sea. ...
The date of dissipation was influenced by sea surface temperature (SST) and precipitation, and high SST accelerated the process of green tide dissipation, while precipitation slowed it down. ...
, Chinese Academy of Sciences (ZDBS-LY-7010), Open Fund of CAS Key Laboratory of Marine Ecology and Environmental Sciences (KLMEES202005), CAS Key Laboratory of Coastal Environmental Processes and Ecological ...
doi:10.1016/j.marpolbul.2021.112801
pmid:34385022
fatcat:26cnznqkzzgefdm7scimslnpvi
The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide
2021
Geoscientific Model Development
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, a phytoplankton species causing the largest worldwide bloom of green tide in the Yellow Sea, China. ...
The FMGDM was applied to simulate the green tide around the Yellow Sea in 2014 and 2015. ...
This paper was edited by Andrew Yool and reviewed by Jonathan Whiting and two anonymous referees. ...
doi:10.5194/gmd-14-6049-2021
fatcat:w2tgtabhbfa37ex24k7kz4bppq
Introduction to the Special Issue on green tides in the Yellow Sea
2015
Estuarine, Coastal and Shelf Science
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The spectacular massive green tide of Ulva prolifera in the southern Yellow Sea, which has become a recurrent phenomenon in this region over the last 8 years, attracted much attention of scientists and ...
Two years after the first occurrence of massive green tide in the Yellow Sea, a project in the National Basic Research Priority Program (973 project) -Succession of Harmful Algal Blooms in the Coastal ...
Acknowledgements We gratefully acknowledge the National Basic Research Priority Project ...
doi:10.1016/j.ecss.2015.06.023
fatcat:a6kyj4t6j5ahvglwuztuztsqi4
QUANTITATIVE ULVA PROLIFERA BLOOM MONITORING BASED ON MULTI-SOURCE SATELLITE OCEAN COLOR REMOTE SENSING DATA
2020
Applied Ecology and Environmental Research
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Since 2007, a large-scare green macroalgae bloom of Ulva prolifera has occurred every year in the Yellow Sea, and satellite ocean color remote sensing monitoring of such event is an effective technical ...
In view of the threshold selection of the detection, the scaled algae index (SAI) is less sensitive to the environment and shows accurate stability. ...
Ocean color remote sensing is a passive measurement technique that utilizes visible and near-infrared bands. ...
doi:10.15666/aeer/1804_48974913
fatcat:7uauhntnv5a37a4lnf3zanj7oq
AlgaeNet: A Deep-Learning Framework to Detect Floating Green Algae From Optical and SAR Imagery
2022
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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We process satellite images containing U. prolifera in the Yellow Sea and draw two conclusions. ...
Second, we define a floating and submerged ratio number (FS ratio) based on the floating and submerged parts of U. prolifera detected by SAR and MODIS. ...
ACKNOWLEDGMENT The MODIS true-color. 2 Sentinel-1 SAR. 3 The Chinese GF-3 SAR images. 4 The Sentinel-2 true-color. 5 ...
doi:10.1109/jstars.2022.3162387
fatcat:6uxkae2q7railo3ozfxtvsnfum
Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: A Case Study in Jiaozhou Bay, China
2019
Remote Sensing
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Analysis of the remote-sensing reflectance and application of the Normalised Difference Water Index demonstrate that this phenomenon is caused by contamination of the signal by bridge pixels. ...
In this study, we use Jiaozhou Bay (East China) and its cross-bay bridge to examine the impact of coastal infrastructure on water-quality remote-sensing products, in particular on chlorophyll-a concentration ...
Conflicts of Interest: The authors declare no conflict of interest. Remote Sens. 2019, 11, 946 ...
doi:10.3390/rs11080946
fatcat:ziwi23g72rhwpovhyik2jo5lgi
The status of coastal oceanography in heavily impacted Yellow and East China Sea: Past trends, progress, and possible futures
2015
Estuarine, Coastal and Shelf Science
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The rapid expansion in economic development and anticipated growth of the population in the coastal zones along the Yellow and East China Sea basin has placed this region under intense multiple stresses ...
Keywords: coastal oceanography physical and biogeochemical processes conservation management Yellow Sea and East China Sea China Korea Japan Taiwan a b s t r a c t Coastal environments are a key location ...
Acknowledgements We would like to express our sincere gratitude to Julie Kesby for collecting and grouping papers as well as editorial assistance and advice in the production of this paper. ...
doi:10.1016/j.ecss.2015.05.039
fatcat:7cg7kvnyxfgy5eeg4k7vyirjoa
Interpreting the progressive eutrophication behind the world's largest macroalgal blooms with water quality and ocean color data
2015
Natural Hazards
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World's largest macroalgal blooms (MAB) caused by Ulva prolifera outbreak every summer in the Yellow Sea since 2007, which bring potential damage to regional marine environment and economics. ...
In this study, we used an area-weighted nutrient pollution index (AWCPI-NP) and ocean color data to assess temporal changes in eutrophication status in the Yellow Sea basin. ...
We especially thank the Institute of Oceanology, Chinese Academy of Sciences, for organizing the open cruise in the Yellow Sea, and Dr. Yanju HAO and Ms. ...
doi:10.1007/s11069-015-1694-x
fatcat:xedvehar7fe73g5etuuz5q5awm
Adaptive Threshold Model in Google Earth Engine: A Case Study of Ulva prolifera Extraction in the South Yellow Sea, China
2021
Remote Sensing
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An outbreak of Ulva prolifera poses a massive threat to coastal ecology in the Southern Yellow Sea, China (SYS). It is a necessity to extract its area and monitor its development accurately. ...
The model first applies the Floating Algae Index (FAI) or Normalized Difference Vegetation Index (NDVI) algorithm on the preprocessed remote sensing images and then uses the Canny Edge Filter and Otsu ...
Data of the U.prolifera by the Ministry of Natural Resources North China Sea Administration are available online at http://ncs.mnr.gov.cn/ (accessed on 10 July 2021). ...
doi:10.3390/rs13163240
fatcat:h75eukkfv5hzhhvfpqbx74rcs4
Monitoring the Chl-a Distribution Details in the Yangtze River Mouth Using Satellite Remote Sensing
2022
Water
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Chl-a downstream of islands and bridges increased by 0.5–1.7 µg/L compared with upstream. (2) Short-term (within 3 h) changes of Chl-a concentration were effectively detected. ...
The distribution of chlorophyll-a (Chl-a) in the Yangtze River Mouth area was analyzed using a new Chl-a inversion model (PMS-C) based on the relationship between in situ Chl-a and GF-4 PMS band combinations ...
Chl-a in the Yellow Sea and East China Sea [23] was retrieved using an empirical algorithm to invert Chl-a concentration and it was detected that the uncertainty of Chl-a was up to 35%. ...
doi:10.3390/w14081295
doaj:ac167cc38d39425698c7f6a035cc9c77
fatcat:3tlqv2rphzcqhiaqccszwfvku4
Assessing Herbivorous Impacts of Apohale sp. on the Ulva prolifera Green Tide in China
2021
Frontiers in Plant Science
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., was abundant in the floating Ulva prolifera (U. prolifera), which forms large-scale green tides in the Yellow Sea (YSGT). ...
webs in the southern Yellow Sea. ...
ACKNOWLEDGMENTS We sincerely thank Captain Wei Lin and crews from Suruyuyun-288 for their assistance in sampling. ...
doi:10.3389/fpls.2021.795560
pmid:34975983
pmcid:PMC8715085
fatcat:3rumvjfhxfdpjc4c43vuxsmjwe
High-resolution phytoplankton diel variations in the summer stratified central Yellow Sea
2012
Journal of Oceanography
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Vertical distributions of phytoplankton biomass and community structure were studied in the summer stratified central Yellow Sea (YS) using a submersible spectrofluorometer (Fluoroprobe, bbe Moldaenke, ...
The concentrations of brown algae, green algae and total chlorophyll a (Chl a) biomass were highly correlated between the results of Fluoroprobe observations and pigments analysis (r = 0.79, 0.91 and 0.82 ...
This work was supported by Grants of the National Basic Research Programme (Nos. 2011CB403603 and 2006CB400604), the China NSF (Nos. 40925018 and 41176112), and SOA Project (No. 201105021). ...
doi:10.1007/s10872-012-0144-6
fatcat:lri5kole7nb7jkdrchpkdrgsfm
UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities
2018
Drones
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In response, various remotely-sensed methods of detection, analysis, and forecasting have been developed. ...
Satellite imaging has proven successful in the identification of various inland and coastal blooms at large spatial and temporal scales, and airborne platforms offer higher spatial and often spectral resolution ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/drones2040035
fatcat:j4jaxopisbbbpcqr346adpa5hq
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