Abstract
Intensive land use favors eutrophication processes and algae bloom proliferation in freshwaters, which is considered to be one of the main environmental issues worldwide. In general, and particularly in South America, inland water monitoring only covers the main water bodies due to the high costs and efforts involved. In order to improve the coverage of spatial and temporal of algae bloom monitoring, remote sensing serves as an alternative tool. Thereby, the analysis of significant spatial clusters of high values (hotspots) and low values (coldspots) of chlorophyll-a has been applied in coastal studies; however, at present, there are no studies in freshwaters. In this study, Getis-Ord Gi* hotspot analysis was applied to detect spatial distribution patterns of algae bloom dynamics in small- and medium-sized freshwater bodies. Four in situ samplings were carried out in five suburban lakes of Uruguay, in agreement with the satellite capture. Total and cyanobacterial chlorophyll-a concentration, and suspended solids were evaluated. Linear models were developed by combining pre-established indexes with additional Sentinel-2 spectral bands and in situ data. The relationship between red and red edge regions allowed mapping the chlorophyll-a in the study lakes with an adjustment of R2 = 0.83. Hotspot analysis was performed with the selected linear model, and significant chlorophyll-a variability within each lake was successfully detected. The novel application of hotspots analyses presented in this work represents a contribution to advance knowledge in the remote detection of algae bloom dynamics and improve monitoring capabilities of inland water bodies.
Similar content being viewed by others
References
Aguilera, A., Aubriot, L., Echenique, R. O., Salerno, G. L., Brena, B. M., Pírez, M., & Bonilla, S. (2017). Synergistic effects of nutrients and light favor Nostocales over non-heterocystous cyanobacteria. Hydrobiologia, 794(1), 241–255.
Ansper, A. (2018). Sentinel-2/MSI applications for European Union Water Framework Directive reporting purposes (Doctoral dissertation, Tartu Ülikool).
APHA (2005) Standard methods for the examination of water and wastewater, American Public Health Association, APHA/AWWA/WPCF, Washington.
Aubriot, L., Conde, D., Bonilla, S., Hein, V. & Britos, A. (2005). Vulnerabilidad de una laguna costera reserva de biósfera: indicios recientes de eutrofización. In: Taller Internacional de Eutrofización y Embalses CYTED VXII B. (Eds I. Vila y J. Pizarro), 65–87.
Aubriot, L., Zabaleta, B., Bordet, F., Sienra, D., Risso, J., Achkar, M., & Somma, A. (2020). Assessing the origin of a massive cyanobacterial bloom in the Río de la Plata (2019): towards an early warning system. Water Research, 115944.
Augusto-Silva, P. B., Ogashawara, I., Barbosa, C. C., De Carvalho, L. A., Jorge, D. S., Fornari, C. I., & Stech, J. L. (2014). Analysis of MERIS reflectance algorithms for estimating chlorophyll-a concentration in a Brazilian Reservoir. Remote Sensing, 6(12), 11689–11707.
Bodhaine, B. A., Wood, N. B., Dutton, E. G., & Slusser, J. R. (1999). On Rayleigh optical depth calculations. Journal of Atmospheric and Oceanic Technology, 16(11), 1854–1861.
Bordet, F., Fontanarrosa, M. S., & O’farrell, I. (2017). Influence of light and mixing regime on bloom-forming phytoplankton in a subtropical reservoir. River Research and Applications, 33(8), 1315–1326.
Borras, M. A., Seoane, G., Gomez-Camponovo, M., Vazquez, E. U., & Perez, N. (2018). Early detection of chloroform hot spots in the Montevideo drinking water network. Cogent Environmental Science, 4(1), 1516501.
Brezonik, P. L., Olmanson, L. G., Finlay, J. C., & Bauer, M. E. (2015). Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters. Remote Sensing of Environment, 157, 199–215.
Burford, M. A., & O’Donohue, M. J. (2006). A comparison of phytoplankton community assemblages in artificially and naturally mixed subtropical water reservoirs. Freshwater Biology, 51(5), 973–982.
Burford, M. A., Carey, C. C., Hamilton, D. P., Huisman, J., Paerl, H. W., Wood, S. A., & Wulff, A. (2020). Perspective: advancing the research agenda for improving understanding of cyanobacteria in a future of global change. Harmful Algae, 91, 101601.
Candiani, G., Floricioiu, D., Giardino, C., & Rott, H. (2005). Monitoring water quality of the perialpine Italian Lake Garda through multi-temporal MERIS data. In Proceedings of MERIS-(A) ATSR Workshop, Frascati, Italy (pp. 26–30).
Carpenter, S. R., Caraco, N. F., Correll, D. L., Howarth, R. W., Sharpley, A. N., & Smith, V. H. (1998). Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications, 8(3), 559–568.
Carpenter, S. R., Stanley, E. H., & Vander Zanden, M. J. (2011). State of the world’s freshwater ecosystems: physical, chemical, and biological changes. Annual Review of Environment and Resources, 36, 75–99.
Chapin III, F. S., Matson, P. A., & Vitousek, P. (2011). Principles of terrestrial ecosystem ecology. Springer Science & Business Media.
Chorus, I., & Bartram, J. (Eds.). (1999). Toxic cyanobacteria in water: a guide to their public health consequences, monitoring and management. CRC Press.
Clark, J. M., Schaeffer, B. A., Darling, J. A., Urquhart, E. A., Johnston, J. M., Ignatius, A. R., & Stumpf, R. P. (2017). Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources. Ecological Indicators, 80, 84–95.
Conley, D. J., Paerl, H. W., Howarth, R. W., Boesch, D. F., Seitzinger, S. P., Havens, K. E., & Likens, G. E. (2009). Controlling eutrophication: nitrogen and phosphorus. Science, 323(5917), 1014–1015.
Copado-Rivera, A. G., Bello-Pineda, J., Aké-Castillo, J. A., & Arceo, P. (2020). Spatial modeling to detect potential incidence zones of harmful algae blooms in Veracruz, Mexico. Estuarine, Coastal and Shelf Science, 106908.
Cremella, B., Huot, Y., & Bonilla, S. (2018). Interpretation of total phytoplankton and cyanobacteria fluorescence from cross-calibrated fluorometers, including sensitivity to turbidity and colored dissolved organic matter. Limnology and Oceanography: Methods, 16(12), 881–894.
Crisci, C., Goyenola, G., Terra, R., Lagomarsino, J. J., Pacheco, J. P., Díaz, I., & Ghattas, B. (2017). Dinámica ecosistémica y calidad de agua: estrategias de monitoreo para la gestión de servicios asociados a Laguna del Sauce (Maldonado, Uruguay). Innotec, 13, 46–57.
Cunha, D. G. F., & do Carmo Calijuri, M., & Lamparelli, M. C. (2013). A trophic state index for tropical/subtropical reservoirs (TSItsr). Ecological Engineering, 60, 126–134.
Dall’Olmo, G., & Gitelson, A. A. (2005). Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results. Applied Optics, 44(3), 412–422.
Dall’Olmo, G., Gitelson, A. A., Rundquist, D. C., Leavitt, B., Barrow, T., & Holz, J. C. (2005). Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands. Remote Sensing of Environment, 96(2), 176–187.
Delegido, J., Urrego, P., Vicente, E., Sòria-Perpinyà, X., Soria, J. M., Pereira-Sandoval, M., & Moreno, J. (2019). Turbidez y profundidad de disco de Secchi con Sentinel-2 en embalses con diferente estado trófico en la Comunidad Valenciana. Revista de Teledetección, 54, 15–24.
Dodds, W. K., Bouska, W. W., Eitzmann, J. L., Pilger, T. J., Pitts, K. L., Riley, A. J., & Thornbrugh, D. J. (2009). Eutrophication of US freshwaters: analysis of potential economic damages.
Dörnhöfer, K., Göritz, A., Gege, P., Pflug, B., & Oppelt, N. (2016). Water constituents and water depth retrieval from Sentinel-2A—a first evaluation in an oligotrophic lake. Remote Sensing, 8(11), 941.
Dörnhöfer, K., Klinger, P., Heege, T., & Oppelt, N. (2018). Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake. Science of The Total Environment, 612, 1200–1214.
Drozd, A., de Tezanos Pinto, P., Fernández, V., Bazzalo, M., Bordet, F., & Ibañez, G. (2020). Hyperspectral remote sensing monitoring of cyanobacteria blooms in a large South American reservoir: high-and medium-spatial resolution satellite algorithm simulation. Marine and Freshwater Research, 71(5), 593–605.
Duan, H., Ma, R., Zhang, Y., Loiselle, S. A., Xu, J., Zhao, C., & Shang, L. (2010). A new three-band algorithm for estimating chlorophyll concentrations in turbid inland lakes. Environmental Research Letters, 5(4), 044009.
Fabre, A., Carballo, C., Hernandez, E., Piriz, P., Bergamino, L., Mello, L., & Bonilla, S. (2010). El nitrógeno y la relación zona eufótica/zona de mezcla explican la presencia de cianobacterias en pequeños lagos subtropicales, artificiales de Uruguay.
Fletcher, K. (2012). Sentinel-2: ESA’s optical high-resolution mission for GMES Operational Services (European Spatial Agency SP-1322/2) ISBN 978–92–9221–419–7.
Floricioiu, D., Rott, H., Rott, E., Dokulil, M., & Defrancesco, C. (2003). Retrieval of limnological parameters of perialpine lakes by means of MERIS data. Limnology, 16(09), 44.
Gallegos, C. L., & Neale, P. J. (2015). Long-term variations in primary production in a eutrophic sub-estuary: contribution of short-term events. Estuarine, Coastal and Shelf Science, 162, 22–34.
Getis, A., & Ord, J. K. (2010). The analysis of spatial association by use of distance statistics. In Perspectives on spatial data analysis (pp. 127–145). Springer, Berlin, Heidelberg.
Gitelson, A. (1992). The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. International Journal of Remote Sensing, 13(17), 3367–3373.
Gitelson, A. A., Nikanorov, A. M., Szabo, G. Y., & Szilagyi, F. (1986). Etude de la qualite des eaux de surface par teledetection. IAHS-AISH publication, 157, 111–121.
Gons, H. J. (1999). Optical teledetection of chlorophyll a in turbid inland waters. Environmental Science & Technology, 33(7), 1127–1132.
González-Piana, M., Fabián, D., Piccardo, A., & Chalar, G. (2017). Dynamics of total microcystin LR concentration in three subtropical hydroelectric generation reservoirs in Uruguay, South America. Bulletin of Environmental Contamination and Toxicology, 99(4), 488–492.
Gordon, H. R., Clark, D. K., Mueller, J. L., & Hovis, W. A. (1980). Phytoplankton pigments from the Nimbus-7 Coastal Zone Color Scanner: comparisons with surface measurements. Science, 210(4465), 63–66.
Ha, N. T. T., Thao, N. T. P., Koike, K., & Nhuan, M. T. (2017). Selecting the best band ratio to estimate chlorophyll-a concentration in a tropical freshwater lake using sentinel 2A images from a case study of Lake Ba Be (Northern Vietnam). ISPRS International Journal of Geo-Information, 6(9), 290.
Haakonsson, S., Rodríguez, M. A., Carballo, C., del Carmen Pérez, M., Arocena, R., & Bonilla, S. (2020). Predicting cyanobacterial biovolume from water temperature and conductivity using a Bayesian compound Poisson-Gamma model. Water Research, 115710.
Ho, J. C., Michalak, A. M., & Pahlevan, N. (2019). Widespread global increase in intense lake phytoplankton blooms since the 1980s. Nature, 574(7780), 667–670.
Huisman, J., Codd, G. A., Paerl, H. W., Ibelings, B. W., Verspagen, J. M., & Visser, P. M. (2018). Cyanobacterial blooms. Nature Reviews Microbiology, 16(8), 471–483.
ISO-10260 (1992) Water quality — Measurement of biochemical parameters — Spectrometric determination of the chlorophyll-a concentration ISO 10260.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer.
Kravitz, J., Matthews, M., Bernard, S., & Griffith, D. (2020). Application of Sentinel 3 OLCI for chl-a retrieval over small inland water targets: successes and challenges. Remote Sensing of Environment, 237, 111562.
Kruk, C., Martínez, A., de la Escalera, G. M., Trinchin, R., Manta, G., Segura, Á. M., & Gabito, L. (2019). Floración excepcional de cianobacterias tóxicas en la costa de Uruguay, verano 2019. Innotec, 18, 36–68.
Kutser, T., Pierson, D. C., Kallio, K. Y., Reinart, A., & Sobek, S. (2005). Mapping lake CDOM by satellite remote sensing. Remote Sensing of Environment, 94(4), 535–540.
Kutser, T., Paavel, B., Verpoorter, C., Ligi, M., Soomets, T., Toming, K., & Casal, G. (2016). Remote sensing of black lakes and using 810 nm reflectance peak for retrieving water quality parameters of optically complex waters. Remote Sensing, 8(6), 497.
Legendre, P., & Legendre, L. (1998). Numerical ecology: developments in environmental modelling. Developments in Environmental Modelling, 20.
Liu, H., Li, Q., Shi, T., Hu, S., Wu, G., & Zhou, Q. (2017). Application of sentinel 2 MSI images to retrieve suspended particulate matter concentrations in Poyang Lake. Remote Sensing, 9(7), 761.
Lunetta, R. S., Shao, Y., Ediriwickrema, J., & Lyon, J. G. (2010). Monitoring agricultural cropping patterns across the Laurentian Great Lakes Basin using MODIS-NDVI data. International Journal of Applied Earth Observation and Geoinformation, 12(2), 81–88.
Lürling, M., Waajen, G., & de Senerpont Domis, L. N. (2016). Evaluation of several end-of-pipe measures proposed to control cyanobacteria. Aquatic Ecology, 50(3), 499–519.
Martins, V. S., Barbosa, C. C. F., De Carvalho, L. A. S., Jorge, D. S. F., Lobo, F. D. L., & Novo, E. M. L. D. M. (2017). Assessment of atmospheric correction methods for Sentinel-2 MSI images applied to Amazon floodplain lakes. Remote Sensing, 9(4), 322.
Matthews, M. W. (2011). A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters. International Journal of Remote Sensing, 32(21), 6855–6899.
Matthews, M. W. (2014). Eutrophication and cyanobacterial blooms in South African inland waters: 10 years of MERIS observations. Remote Sensing of Environment, 155, 161–177.
Matthews, M. W., Bernard, S., & Robertson, L. (2012). An algorithm for detecting trophic status (chlorophyll-a), cyanobacterial-dominance, surface scums and floating vegetation in inland and coastal waters. Remote Sensing of Environment, 124, 637–652.
Matthews, M. W., Bernard, S., & Winter, K. (2010). Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS. Remote Sensing of Environment, 114(9), 2070–2087.
Michalak, A. M., Anderson, E. J., Beletsky, D., Boland, S., Bosch, N. S., Bridgeman, T. B., & DePinto, J. V. (2013). Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions. Proceedings of the National Academy of Sciences, 110(16), 6448–6452.
Mishra, S., & Mishra, D. R. (2012). Normalized difference chlorophyll index: a novel model for remote estimation of chlorophyll-a concentration in turbid productive waters. Remote Sensing of Environment, 117, 394–406.
Mishra, S., & Mishra, D. R. (2014). A novel remote sensing algorithm to quantify phycocyanin in cyanobacterial algal blooms. Environmental Research Letters, 9(11), 114003.
Mobley, C. D. (1994). Light and water: radiative transfer in natural waters. Academic press.
Molden, D., Schipper, L., De Fraiture, C., Faurés, J. M., & Vallée, D. (2007). Evaluación exhaustiva del manejo del Agua en Agricultura. 2007. Agua para la Alimentación, Agua para la Vida. Londres: Earthscan y Colombo: Instituto Internacional del Manejo del Agua.
Moran, P. A. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological), 10(2), 243–251.
Moses, W. J., Gitelson, A. A., Berdnikov, S., & Povazhnyy, V. (2009). Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data—successes and challenges. Environmental Research Letters, 4(4), 045005.
Mouw, C. B., Greb, S., Aurin, D., DiGiacomo, P. M., Lee, Z., Twardowski, M., & Moses, W. (2015). Aquatic color radiometry remote sensing of coastal and inland waters: challenges and recommendations for future satellite missions. Remote Sensing of Environment, 160, 15–30.
Nechad, B., Ruddick, K. G., & Park, Y. (2010). Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sensing of Environment, 114(4), 854–866.
Odermatt, D., Gitelson, A., Brando, V. E., & Schaepman, M. (2012). Review of constituent retrieval in optically deep and complex waters from satellite imagery. Remote Sensing of Environment, 118, 116–126.
Ogashawara, I., Mishra, D. R., & Gitelson, A. A. (2017). Remote sensing of inland waters: background and current state-of-the-art. In Bio-optical modeling and remote sensing of inland waters (pp. 1–24). Elsevier.
Olano, H., Martigani, F., Somma, A., & Aubriot, L. (2019). Wastewater discharge with phytoplankton may favor cyanobacterial development in the main drinking water supply river in Uruguay. Environmental Monitoring and Assessment, 191(3), 146.
Oliveira, E. N., Fernandes, A. M., Kampel, M., Cordeiro, R. C., Brandini, N., Vinzon, S. B., & Paranhos, R. (2016). Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay. Brazil. Journal of Applied Remote Sensing, 10(2), 026003.
Olmanson, L. G., Kloiber, S. M., Bauer, M. E., & Brezonik, P. L. (2001). Image processing protocol for regional assessments of lake water quality. Water resources center technical report, 14.
O’neil, J. M., Davis, T. W., Burford, M. A., & Gobler, C. J. (2012). The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change. Harmful Algae, 14, 313–334.
Paerl, H. W. (2017). Controlling harmful cyanobacterial blooms in a climatically more extreme world: management options and research needs. Journal of Plankton Research, 39(5), 763–771.
Pahlevan, N., Smith, B., Schalles, J., Binding, C., Cao, Z., Ma, R., & Matsushita, B. (2020). Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: a machine-learning approach. Remote Sensing of Environment, 111604.
Palmer, S. C., Kutser, T., & Hunter, P. D. (2015). Remote sensing of inland waters: Challenges, progress and future directions.
R. Team. (2013). R: a language and environment for statistical computing.
Restrepo Calle, S. (2014). Estado de los humedales de la cuenca alta del río Otún (Departamento de Risaralda, Colombia), una reinterpretación desde la estadística espacial (Bachelor's thesis, Quito, 2014).
Rodríguez-Gallego, L., Achkar, M., Defeo, O., Vidal, L., Meerhoff, E., & Conde, D. (2017). Effects of land use changes on eutrophication indicators in five coastal lagoons of the Southwestern Atlantic Ocean. Estuarine, Coastal and Shelf Science, 188, 116–126.
Romo, S., Soria, J., Fernandez, F., Ouahid, Y., & Barón-Solá, A. (2013). Water residence time and the dynamics of toxic cyanobacteria. Freshwater Biology, 58(3), 513–522.
Salas, H. J., & Martino, P. (1991). A simplified phosphorus trophic state model for warm-water tropical lakes. Water Research, 25(3), 341–350.
Schalles, J. F., & Hladik, C. M. (2012). Mapping phytoplankton chlorophyll in turbid, Case 2 estuarine and coastal waters. Israel Journal of Plant Sciences, 60(1–2), 169–191.
Schön, F., Dominguez, A., & Achkar, M. (2018). Distribución territorial de áreas urbanas en zonas de humedales en Uruguay. Geo UERJ, (33), e. 36322.
Shanmugam, P. (2012). CAAS: an atmospheric correction algorithm for the remote sensing of complex waters. Annales Geophysicae (09927689), 30(1).
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611.
Sinha, E., Michalak, A. M., & Balaji, V. (2017). Eutrophication will increase during the 21st century as a result of precipitation changes. Science, 357(6349), 405–408.
Smayda, T. J. (1997). What is a bloom? A commentary. Limnology and Oceanography, 42(5part2), 1132–1136.
Soria, X., Delegido, J., Urrego, E. P., Pereira-Sandoval, M., Vicente, E., Ruíz-Verdú, A., & Moreno, J. (2017). Validación de algoritmos para la estimación de la clorofila-a con Sentinel-2 en la Albufera de València. In Proceedings of the XVII Congreso de la Asociación Española de Teledetección (pp. 289–292).
Sosa, B., Romero, D., Fernández, G., & Achkar, M. (2018). Spatial analysis to identify invasion colonization strategies and management priorities in riparian ecosystems. Forest Ecology and Management, 411, 195–202.
Spyrakos, E., O’Donnell, R., Hunter, P. D., Miller, C., Scott, M., Simis, S. G., & Bresciani, M. (2018). Optical types of inland and coastal waters. Limnology and Oceanography, 63(2), 846–870.
Sterckx, S., Knaeps, S., Kratzer, S., & Ruddick, K. (2015). SIMilarity Environment Correction (SIMEC) applied to MERIS data over inland and coastal waters. Remote Sensing of Environment, 157, 96–110.
Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Boschung, J., & Midgley, P. M. (2013). Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, 1535.
Strong, A. E. (1974). Remote sensing of algal blooms by aircraft and satellite in Lake Erie and Utah Lake. Remote Sensing of Environment, 3(2), 99–107.
Tamm, M., Ligi, M., Panksep, K., Teeveer, K., Freiberg, R., Laas, P., & Nõges, T. (2019). Boosting the monitoring of phytoplankton in optically complex coastal waters by combining pigment-based chemotaxonomy and in situ radiometry. Ecological Indicators, 97, 329–340.
Tebbs, E. J., Remedios, J. J., & Harper, D. M. (2013). Remote sensing of chlorophyll-a as a measure of cyanobacterial biomass in Lake Bogoria, a hypertrophic, saline–alkaline, flamingo lake, using Landsat ETM+. Remote Sensing of Environment, 135, 92–106.
Techera, J., Arriguetti, R., & Spoturno, J. (2004). Mapa geológico y de recursos minerales del Departamento de Canelones a escala 1: 100.000. Memoria descriptiva, Recursos minerales, parte III. Facultad de Ciencias–DINAMIGE, Montevideo.
Toming, K., Kutser, T., Laas, A., Sepp, M., Paavel, B., & Nõges, T. (2016). First experiences in mapping lake water quality parameters with Sentinel-2 MSI imagery. Remote Sensing, 8(8), 640.
Uudeberg, K., Aavaste, A., Kõks, K. L., Ansper, A., Uusõue, M., Kangro, K., & Reinart, A. (2020). Optical water type guided approach to estimate optical water quality parameters. Remote Sensing, 12(6), 931.
Van der Linden, S., Okujeni, A., Canters, F., Degerickx, J., Heiden, U., Hostert, P., & Thiel, F. (2019). Imaging spectroscopy of urban environments. Surveys in Geophysics, 40(3), 471–488.
Vanhellemont, Q., & Ruddick, K. (2016). Acolite for Sentinel-2: aquatic applications of MSI imagery. In Proceedings of the 2016 ESA Living Planet Symposium, Prague, Czech Republic (pp. 9–13).
Verspagen, J. M., Passarge, J., Jöhnk, K. D., Visser, P. M., Peperzak, L., Boers, P., & Huisman, J. (2006). Water management strategies against toxic Microcystis blooms in the Dutch delta. Ecological Applications, 16(1), 313–327.
Vincent, R. K., Qin, X., McKay, R. M. L., Miner, J., Czajkowski, K., Savino, J., & Bridgeman, T. (2004). Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie. Remote Sensing of Environment, 89(3), 381–392.
Watanabe, F. S. Y., Alcântara, E., & Stech, J. L. (2018). High performance of chlorophyll-a prediction algorithms based on simulated OLCI Sentinel-3A bands in cyanobacteria-dominated inland waters. Advances in Space Research, 62(2), 265–273.
Wu, X., Kong, F., Chen, Y., Qian, X., Zhang, L., Yu, Y., & Xing, P. (2010). Horizontal distribution and transport processes of bloom-forming Microcystis in a large shallow lake (Taihu, China). Limnologica, 40(1), 8–15.
Yang, Z., Reiter, M., & Munyei, N. (2017). Estimation of chlorophyll-a concentrations in diverse water bodies using ratio-based NIR/Red indices. Remote Sensing Applications: Society and Environment, 6, 52–58.
Yunus, A. P., Dou, J., & Sravanthi, N. (2015). Remote sensing of chlorophyll-a as a measure of red tide in Tokyo Bay using hotspot analysis. Remote Sensing Applications: Society and Environment, 2, 11–25.
Zheng, G., & DiGiacomo, P. M. (2017). Uncertainties and applications of satellite-derived coastal water quality products. Progress in Oceanography, 159, 45–72.
Zimba, P. V., & Gitelson, A. (2006). Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: model tuning and accuracy optimization. Aquaculture, 256(1–4), 272–286.
Acknowledgements
We thank Edwin da Costa for his comments at the beginning of the study, and Elena Galvanese and Hernán Olano for field and laboratory assistance.
Funding
The research that gives rise to the results presented in this manuscript was funded by the National Agency for Research and Innovation under the code POS_NAC_2017_1_141497.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Zabaleta, B., Achkar, M. & Aubriot, L. Hotspot analysis of spatial distribution of algae blooms in small and medium water bodies. Environ Monit Assess 193, 221 (2021). https://doi.org/10.1007/s10661-021-08944-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-021-08944-z