Water quality monitoring using remote sensing and an artificial neural network

Water, Air, and Soil Pollution

Volumn 223, Issue 8, 2012, Pages 4875-4887

  Chebud, Yirgalem ^a,b   Naja, Ghinwa M ^a   Rivero, Rosanna G ^a   Melesse, Assefa M ^b  

^a Everglades Foundation   (United States)

^b FLORIDA INTERNATIONAL UNIVERSITY   (United States)

Author keywords

Ecological restoration; Landsat TM; Neural network; Remote sensing

Indexed keywords

CHLOROPHYLL A; DRY AND WET; ECOLOGICAL RESTORATION; ECOSYSTEM RESTORATION; FLORIDA EVERGLADES; HIGH COSTS; LANDSAT; LANDSAT TM; MONITORING WATER QUALITY; NEURAL NETWORK MODEL; NEURAL NETWORK TRAINING; ROOT MEAN SQUARE ERRORS; SPECTRAL DATA; TEMPORAL AND SPATIAL DYNAMICS; WATER COLUMNS; WATER QUALITY MONITORING; WATER QUALITY PARAMETERS; WATERBODIES; WET AND DRY SEASONS;

CHLOROPHYLL; ECOSYSTEMS; MEAN SQUARE ERROR; NEURAL NETWORKS; PHOSPHORUS; REMOTE SENSING; TURBIDITY;

WATER QUALITY;

ARTIFICIAL NEURAL NETWORK; CHLOROPHYLL A; LANDSAT THEMATIC MAPPER; PHOSPHORUS; REMOTE SENSING; TURBIDITY; WATER COLUMN; WATER QUALITY; WATERSHED;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COST EFFECTIVENESS ANALYSIS; ECOSYSTEM; ECOSYSTEM RESTORATION; ENVIRONMENTAL MONITORING; ENVIRONMENTAL PARAMETERS; GEOGRAPHIC DISTRIBUTION; METHODOLOGY; REMOTE SENSING; SEDIMENT; TURBIDITY; WATER ANALYSIS; WATER MANAGEMENT; WATER QUALITY; WATERSHED;

EVERGLADES; FLORIDA [UNITED STATES]; UNITED STATES;

EID: 84867332394     PISSN: 00496979     EISSN: 15732932     Source Type: Journal    
DOI: 10.1007/s11270-012-1243-0     Document Type: Article

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