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Abstract:

The application of remote sensing technology to water quality monitoring has special significance for lake management at regional scales. Many studies have proposed algorithms between Landsat data and in-situ water quality parameters using classical regression models. The novelty of this paper is that we developed algorithms to determine log-transformed chlorophyll-a concentration (Chl-a) and Secchi disk transparency (SDT) in Río Tercero reservoir using Landsat TM and ETM. + imagery, ancillary environmental factors and linear mixed models (LMM), obtaining an increase in the accuracy of the estimates. The validation results showed that LMM with spatial correlation structure that take into account water surface temperature (WST) and rainfall were the most suitable method for estimating these parameters. WST derived from the Landsat thermal band was also validated. The algorithms were used to generate quantitative maps providing spatially and temporally rich information on patterns of water quality throughout the reservoir. Water quality features related to the hydrogeomorphology of the reservoir, typical seasonality and influx from the cooling system of a local nuclear reactor were identified in the time series maps. © 2014 Elsevier Inc.

Registro:

Documento: Artículo
Título:Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in Río Tercero reservoir (Argentina)
Autor:Bonansea, M.; Rodriguez, M.C.; Pinotti, L.; Ferrero, S.
Filiación:Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Departamento de Estudios Básicos y Agropecuarios, Facultad de Agronomía y Veterinaria (FAyV), Universidad Nacional de Río Cuarto (UNRC), Ruta Nacional 36 Km 601, Río Cuarto, Córdoba, Argentina
Departamento de Estudios Básicos y Agropecuarios, FAyV, UNRC, Ruta Nacional 36 Km 601, Río Cuarto, Córdoba, Argentina
CONICET, Rivadavia 1917, Buenos Aires, Argentina
Departamento Matemática, Facultad de Ciencias Exactas, Físico-Químicas y Naturales, UNRC, Ruta Nacional 36 Km 601, Río Cuarto, Córdoba, Argentina
Palabras clave:Algorithms; Landsat; Linear mixed models; Remote sensing; Reservoir; Water quality; Algorithms; Atmospheric temperature; Lakes; Nuclear reactors; Parameter estimation; Regression analysis; Remote sensing; Water quality; Chlorophyll-a concentration; LANDSAT; Linear mixed models; Remote sensing technology; Spatial correlation structures; Water quality monitoring; Water quality parameters; Water surface temperature; Reservoirs (water); algorithm; chlorophyll a; data set; Landsat; numerical model; satellite imagery; seasonality; surface temperature; transparency; water quality; Argentina; Cordoba [Argentina]; Tercero River
Año:2015
Volumen:158
Página de inicio:28
Página de fin:41
DOI: http://dx.doi.org/10.1016/j.rse.2014.10.032
Título revista:Remote Sensing of Environment
Título revista abreviado:Remote Sens. Environ.
ISSN:00344257
CODEN:RSEEA
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00344257_v158_n_p28_Bonansea

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Citas:

---------- APA ----------
Bonansea, M., Rodriguez, M.C., Pinotti, L. & Ferrero, S. (2015) . Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in Río Tercero reservoir (Argentina). Remote Sensing of Environment, 158, 28-41.
http://dx.doi.org/10.1016/j.rse.2014.10.032
---------- CHICAGO ----------
Bonansea, M., Rodriguez, M.C., Pinotti, L., Ferrero, S. "Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in Río Tercero reservoir (Argentina)" . Remote Sensing of Environment 158 (2015) : 28-41.
http://dx.doi.org/10.1016/j.rse.2014.10.032
---------- MLA ----------
Bonansea, M., Rodriguez, M.C., Pinotti, L., Ferrero, S. "Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in Río Tercero reservoir (Argentina)" . Remote Sensing of Environment, vol. 158, 2015, pp. 28-41.
http://dx.doi.org/10.1016/j.rse.2014.10.032
---------- VANCOUVER ----------
Bonansea, M., Rodriguez, M.C., Pinotti, L., Ferrero, S. Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in Río Tercero reservoir (Argentina). Remote Sens. Environ. 2015;158:28-41.
http://dx.doi.org/10.1016/j.rse.2014.10.032