Cyanobacteria, Analysis, Detection

Chapter Contents (Back)
Classification. Cyanobacteria.

Song, K.[Kaishan], Li, L.[Lin], Tedesco, L.P.[Lenore P.], Li, S.[Shuai], Hall, B.E.[Bob E.], Du, J.[Jia],
Remote quantification of phycocyanin in potable water sources through an adaptive model,
PandRS(95), No. 1, 2014, pp. 68-80.
Elsevier DOI 1408
Cyanobacteria BibRef

Mishra, S., Mishra, D.R., Lee, Z.P.[Zhong-Ping],
Bio-Optical Inversion in Highly Turbid and Cyanobacteria-Dominated Waters,
GeoRS(52), No. 1, January 2014, pp. 375-388.
hydrological techniques BibRef

Wozniak, M.[Monika], Bradtke, K.M.[Katarzyna M.], Darecki, M.[Miroslaw], Krezel, A.[Adam],
Empirical Model for Phycocyanin Concentration Estimation as an Indicator of Cyanobacterial Bloom in the Optically Complex Coastal Waters of the Baltic Sea,
RS(8), No. 3, 2016, pp. 212.
DOI Link 1604

Liang, Q.C.[Qi-Chun], Zhang, Y.C.[Yu-Chao], Ma, R.H.[Rong-Hua], Loiselle, S.[Steven], Li, J.[Jing], Hu, M.Q.[Min-Qi],
A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Beck, R.[Richard], Xu, M.[Min], Zhan, S.A.[Sheng-An], Liu, H.X.[Hong-Xing], Johansen, R.A.[Richard A.], Tong, S.[Susanna], Yang, B.[Bo], Shu, S.[Song], Wu, Q.S.[Qiu-Sheng], Wang, S.[Shujie], Berling, K.[Kevin], Murray, A.[Andrew], Emery, E.[Erich], Reif, M.[Molly], Harwood, J.[Joseph], Young, J.[Jade], Martin, M.[Mark], Stillings, G.[Garrett], Stumpf, R.[Richard], Su, H.B.[Hai-Bin], Ye, Z.X.[Zhao-Xia], Huang, Y.[Yan],
Comparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706

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

Soja-Wozniak, M.[Monika], Craig, S.E.[Susanne E.], Kratzer, S.[Susanne], Wojtasiewicz, B.[Bozena], Darecki, M.[Miroslaw], Jones, C.T.[Chris T.],
A Novel Statistical Approach for Ocean Colour Estimation of Inherent Optical Properties and Cyanobacteria Abundance in Optically Complex Waters,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705

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

Jia, T.X.[Tian-Xia], Zhang, X.Q.[Xue-Qi], Dong, R.C.[Ren-Cai],
Long-Term Spatial and Temporal Monitoring of Cyanobacteria Blooms Using MODIS on Google Earth Engine: A Case Study in Taihu Lake,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910

Riddick, C.A.L.[Caitlin A.L.], Hunter, P.D.[Peter D.], Gómez, J.A.D.[José Antonio Domínguez], Martinez-Vicente, V.[Victor], Présing, M.[Mátyás], Horváth, H.[Hajnalka], Kovács, A.W.[Attila W.], Vörös, L.[Lajos], Zsigmond, E.[Eszter], Tyler, A.N.[Andrew N.],
Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907

Pyo, J.C.[Jong-Cheol], Duan, H.T.[Hong-Tao], Ligaray, M.[Mayzonee], Kim, M.J.[Min-Jeong], Baek, S.[Sangsoo], Kwon, Y.S.[Yong Sung], Lee, H.[Hyuk], Kang, T.[Taegu], Kim, K.[Kyunghyun], Cha, Y.K.[Yoon-Kyung], Cho, K.H.[Kyung Hwa],
An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004

Miao, S., Li, Y., Wu, Z., Lyu, H., Li, Y., Bi, S., Xu, J., Lei, S., Mu, M., Wang, Q.,
A Semianalytical Algorithm for Mapping Proportion of Cyanobacterial Biomass in Eutrophic Inland Lakes Based on OLCI Data,
GeoRS(58), No. 7, July 2020, pp. 5148-5161.
Lakes, Absorption, Biomass, Indexes, Atmospheric measurements, Remote sensing, Particle measurements, Absorption coefficient, OLCI bands BibRef

Ogashawara, I.[Igor],
Determination of Phycocyanin from Space: A Bibliometric Analysis,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
pigment of inland water cyanobacteria. BibRef

Kumar, A.[Abhishek], Mishra, D.R.[Deepak R.], Ilango, N.[Nirav],
Landsat 8 Virtual Orange Band for Mapping Cyanobacterial Blooms,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003

Zhao, H.[Huan], Li, J.S.[Jun-Sheng], Yan, X.[Xiang], Fang, S.Z.[Sheng-Zhong], Du, Y.C.[Yi-Chen], Xue, B.[Bin], Yu, K.[Kai], Wang, C.[Chen],
Monitoring Cyanobacteria Bloom in Dianchi Lake Based on Ground-Based Multispectral Remote-Sensing Imaging: Preliminary Results,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110

Legleiter, C.J.[Carl J.], Hodges, S.W.[Shawn W.],
Mapping Benthic Algae and Cyanobacteria in River Channels from Aerial Photographs and Satellite Images: A Proof-of-Concept Investigation on the Buffalo National River, AR, USA,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202

Yan, K.[Kai], Li, J.S.[Jun-Sheng], Zhao, H.[Huan], Wang, C.[Chen], Hong, D.F.[Dan-Feng], Du, Y.C.[Yi-Chen], Mu, Y.C.[Yun-Chang], Tian, B.[Bin], Xie, Y.[Ya], Yin, Z.Y.[Zi-Yao], Zhang, F.F.[Fang-Fang], Wang, S.L.[Sheng-Lei],
Deep Learning-Based Automatic Extraction of Cyanobacterial Blooms from Sentinel-2 MSI Satellite Data,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Cao, Z.[Zhen], Jing, Y.Y.[Yuan-Yuan], Zhang, Y.C.[Yu-Chao], Lai, L.[Lai], Liu, Z.M.[Zhao-Min], Yang, Q.[Qiduo],
Innovative Remote Sensing Identification of Cyanobacterial Blooms Inspired from Pseudo Water Color,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Konik, M.[Marta], Bradtke, K.[Katarzyna], Ston-Egiert, J.[Joanna], Soja-Wozniak, M.[Monika], Sliwinska-Wilczewska, S.[Sylwia], Darecki, M.[Miroslaw],
Cyanobacteria Index as a Tool for the Satellite Detection of Cyanobacteria Blooms in the Baltic Sea,
RS(15), No. 6, 2023, pp. 1601.
DOI Link 2304

Bunyon, C.L.[Christine L.], Fraser, B.T.[Benjamin T.], McQuaid, A.[Amanda], Congalton, R.G.[Russell G.],
Using Imagery Collected by an Unmanned Aerial System to Monitor Cyanobacteria in New Hampshire, USA, Lakes,
RS(15), No. 11, 2023, pp. 2839.
DOI Link 2306

Song, T.[Ting], Liu, G.[Ge], Zhang, H.J.[Hu-Jun], Yan, F.[Fei], Fu, Y.[Yingbo], Zhang, J.[Junyi],
Lake Cyanobacterial Bloom Color Recognition and Spatiotemporal Monitoring with Google Earth Engine and the Forel-Ule Index,
RS(15), No. 14, 2023, pp. 3541.
DOI Link 2307

Lin, Y.[Yi], Ye, Z.L.[Zhang-Lin], Zhang, Y.[Yugan], Yu, J.[Jie],
Spectral Feature Analysis For Quantitative Estimation Of Cyanobacteria Chlorophyll-a,
ISPRS16(B7: 91-98).
DOI Link 1610

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Ice Detection, Glaciers Detection and Analysis .

Last update:Aug 31, 2023 at 09:37:21