Artificial neural networks and remote sensing in the analysis of the highly variable Pampean shallow lakes by Graciela Canziani, Rosana Ferrati, Claudia Marinelli, Federico Dukatz

“…The analysis oftheir optic properties through the spectral signatures obtained fromsatellite images allows us to infer the trophic state of the shallow lakesand generate a real time tool for studying the dynamics of shallow lakes.Field data (chlorophyll-a, total solids, and Secchi disk depth) allow us todefine levels of turbidity and to characterize the shallow lakes understudy. …”
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Integrating Satellite Data and In-situ Observations for Trophic State Assessment of Renuka Lake, Himachal Pradesh, India by Sujit Kumar Jally, Rakesh Kumar and Sibabrata Das

“…The present study focuses on estimating the Trophic State Index (TSI) of Renuka Lake, the smallest Ramsar site in India, utilizing in-situ observed Secchi disk transparency (SDT) and satellite data. Site-specific algorithms were developed by establishing the relationship between the spectral band ratio of Landsat 8 OLI and LISS-III with that of in-situ measured SDT data. …”
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Estimation of zooplankton density with artificial neural networks (a new statistical approach) method, Elazığ-Türkiye by Bulut Hilal

“…Water temperature, dissolved oxygen, pH, electrical conductivity, secchi disk, alkalinity, total nitrogen and total phosphorus were measured. …”
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Assessment of temporal and spatial eutrophication index in a water dam reservoir by F. Esfandi, A.H. Mahvi, M. Mosaferi, F. Armanfar, M. Hejazi, S. Maleki

“…Physico-chemical parametres that are effective on eutrphic condition occurrence  were analyzed, and trophic state index was calculated on a scale of 0-100 by measuring Secchi disk depth, chlorophyll a, total phosphorus, total nitrogen, total suspended solids, and phosphorus P/N ratio. …”
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