Algal Blooms, Analysis, Detection

Chapter Contents (Back)
Classification. Algal Blooms.

Zavalas, R.[Richard], Ierodiaconou, D.[Daniel], Ryan, D.[David], Rattray, A.[Alex], Monk, J.[Jacquomo],
Habitat Classification of Temperate Marine Macroalgal Communities Using Bathymetric LiDAR,
RS(6), No. 3, 2014, pp. 2154-2175.
DOI Link 1404

Song, W.L.[Wei-Long], Dolan, J.M.[John M.], Cline, D.[Danelle], Xiong, G.M.[Guang-Ming],
Learning-Based Algal Bloom Event Recognition for Oceanographic Decision Support System Using Remote Sensing Data,
RS(7), No. 10, 2015, pp. 13564.
DOI Link 1511

Xing, Q.G.[Qian-Guo], Hu, C.M.[Chuan-Min], Tang, D.L.[Dan-Ling], Tian, L.[Liqiao], Tang, S.L.[Shi-Lin], Wang, X.H.[Xiao Hua], Lou, M.J.[Ming-Jing], Gao, X.[Xuelu],
World's Largest Macroalgal Blooms Altered Phytoplankton Biomass in Summer in the Yellow Sea: Satellite Observations,
RS(7), No. 9, 2015, pp. 12297.
DOI Link 1511

Zhang, Y.[Yuchao], Ma, R.H.[Rong-Hua], Zhang, M.[Min], Duan, H.T.[Hong-Tao], Loiselle, S.[Steven], Xu, J.[Jinduo],
Fourteen-Year Record (2000-2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images,
RS(7), No. 8, 2015, pp. 10523.
DOI Link 1509

Kamerosky, A.[Andrew], Cho, H.J.[Hyun Jung], Morris, L.[Lori],
Monitoring of the 2011 Super Algal Bloom in Indian River Lagoon, FL, USA, Using MERIS,
RS(7), No. 2, 2015, pp. 1441-1460.
DOI Link 1503

Zhao, J.[Jun], Temimi, M.[Marouane], Ghedira, H.[Hosni],
Characterization of harmful algal blooms (HABs) in the Arabian Gulf and the Sea of Oman using MERIS fluorescence data,
PandRS(101), No. 1, 2015, pp. 125-136.
Elsevier DOI 1503
HAB BibRef

El-Habashi, A.[Ahmed], Ioannou, I.[Ioannis], Tomlinson, M.C.[Michelle C.], Stumpf, R.P.[Richard P.], Ahmed, S.[Sam],
Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques,
RS(8), No. 5, 2016, pp. 377.
DOI Link 1606

Ouyang, Z.T.[Zu-Tao], Shao, C.L.[Chang-Liang], Chu, H.[Housen], Becker, R.[Richard], Bridgeman, T.[Thomas], Stepien, C.A.[Carol A.], John, R.[Ranjeet], Chen, J.[Jiquan],
The Effect of Algal Blooms on Carbon Emissions in Western Lake Erie: An Integration of Remote Sensing and Eddy Covariance Measurements,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702

Shehhi, M.R.A.[Maryam R. Al], Gherboudj, I.[Imen], Zhao, J.[Jun], Ghedira, H.[Hosni],
Improved atmospheric correction and chlorophyll-a remote sensing models for turbid waters in a dusty environment,
PandRS(133), No. Supplement C, 2017, pp. 46-60.
Elsevier DOI 1711
Harmful algal blooms, Chlorophyll a, Atmospheric correction, Arabian Gulf, Sea of Oman, Arabian Sea, Dusty climate, Shallow water, Turbid, water BibRef

Wang, G.Q.[Guo-Qing], Lee, Z.P.[Zhong-Ping], Mouw, C.[Colleen],
Multi-Spectral Remote Sensing of Phytoplankton Pigment Absorption Properties in Cyanobacteria Bloom Waters: A Regional Example in the Western Basin of Lake Erie,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
And: Erratum: RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

Tan, W.X.[Wen-Xia], Liu, P.C.[Peng-Cheng], Liu, Y.[Yi], Yang, S.[Shao], Feng, S.[Shunan],
A 30-Year Assessment of Phytoplankton Blooms in Erhai Lake Using Landsat Imagery: 1987 to 2016,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802

Wu, L.[Lin], Wang, L.[Le], Min, L.[Lin], Hou, W.[Wei], Guo, Z.[Zhengwei], Zhao, J.H.[Jian-Hui], Li, N.[Ning],
Discrimination of Algal-Bloom Using Spaceborne SAR Observations of Great Lakes in China,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806

Cui, T.W., Liang, X.J., Gong, J.L., Tong, C., Xiao, Y.F., Liu, R.J., Zhang, X., Zhang, J.,
Assessing and refining the satellite-derived massive green macro-algal coverage in the Yellow Sea with high resolution images,
PandRS(144), 2018, pp. 315-324.
Elsevier DOI 1809
Green macro-algal bloom, Coverage, MODIS, SAR, Pixel un-mixing, Mixed pixel effect BibRef

Harun-Al-Rashid, A.[Ahmed], Yang, C.S.[Chan-Su],
Improved Detection of Tiny Macroalgae Patches in Korea Bay and Gyeonggi Bay by Modification of Floating Algae Index,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Gao, B.C.[Bo-Cai], Li, R.R.[Rong-Rong],
FVI: A Floating Vegetation Index Formed with Three Near-IR Channels in the 1.0-1.24 Ám Spectral Range for the Detection of Vegetation Floating over Water Surfaces,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Karki, S.[Sita], Sultan, M.[Mohamed], Elkadiri, R.[Racha], Elbayoumi, T.[Tamer],
Mapping and Forecasting Onsets of Harmful Algal Blooms Using MODIS Data over Coastal Waters Surrounding Charlotte County, Florida,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811

Li, J.[Jing], Ma, R.[Ronghua], Xue, K.[Kun], Zhang, Y.[Yuchao], Loiselle, S.[Steven],
A Remote Sensing Algorithm of Column-Integrated Algal Biomass Covering Algal Bloom Conditions in a Shallow Eutrophic Lake,
IJGI(7), No. 12, 2018, pp. xx-yy.
DOI Link 1901

Shin, J.[Jisun], Kim, K.[Keunyong], Son, Y.B.[Young Baek], Ryu, J.H.[Joo-Hyung],
Synergistic Effect of Multi-Sensor Data on the Detection of Margalefidinium polykrikoides in the South Sea of Korea,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901

Mcilwaine, B.[Ben], Casado, M.R.[Monica Rivas], Leinster, P.[Paul],
Using 1st Derivative Reflectance Signatures within a Remote Sensing Framework to Identify Macroalgae in Marine Environments,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903

Marmorino, G.[George], Chen, W.[Wei],
Use of WorldView-2 Along-Track Stereo Imagery to Probe a Baltic Sea Algal Spiral,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Zong, J.M.[Jia-Min], Wang, X.X.[Xin-Xin], Zhong, Q.Y.[Qiao-Yan], Xiao, X.M.[Xiang-Ming], Ma, J.[Jun], Zhao, B.[Bin],
Increasing Outbreak of Cyanobacterial Blooms in Large Lakes and Reservoirs under Pressures from Climate Change and Anthropogenic Interferences in the Middle-Lower Yangtze River Basin,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908

Medina, E., Petraglia, M.R., Gomes, J.G.R.C., Petraglia, A.,
Comparison of CNN and MLP classifiers for algae detection in underwater pipelines,
biology computing, computer vision, learning (artificial intelligence), microorganisms, Image processing BibRef

Kumar, A.C., Bhandarkar, S.M.,
A Deep Learning Paradigm for Detection of Harmful Algal Blooms,
Feature extraction, Hyperspectral sensors, Lakes, Monitoring, Satellites, Twitter, HAB detection, citizen science, deep learning, image segmentation, texture, classification BibRef

Lu, C.G.[Chun-Guang], Tian, Q.J.[Qing-Jiu],
Extracting Temporal And Spatial Distributions Information About Algal Blooms Based On Multitemporal Modis,
DOI Link 1209

Gokaraju, B.[Balakrishna], Durbha, S.S.[Surya S.], King, R.L.[Roger L.], Younan, N.H.[Nicolas H.],
Investigation of evolutionary feature subset selection in multi-temporal datasets for harmful algal bloom detection,

Qing-Yu, W.[Wei], Nan, J.[Jiang], Heng, L.[Lu], Bin, H.[Hu],
A System for Dynamically Monitoring and Warning Algae Blooms in Taihu Lake Based on Remote Sensing,

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Last update:Oct 1, 2019 at 15:23:24