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.
IEEE DOI
1402
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
BibRef
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
BibRef
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
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
BibRef
And:
Erratum:
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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.
IEEE DOI
2006
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
BibRef
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
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Ice Detection, Glaciers Detection and Analysis .