Hybrid forward-selection method-based water-quality estimation via combining Landsat TM, ETM+, and OLI/TIRS images and ancillary environmental data

• Published in: PloS one Vol. 13; no. 7; p. e0201255
• Main Authors: Tu, Min-Cheng, Smith, Patricia, Filippi, Anthony M
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 30.07.2018; Public Library of Science (PLoS)
• Subjects: Accuracy; Biology and Life Sciences; Calibration; Chlorophyll; Control; Data processing; Earth Sciences; Ecology and Environmental Sciences; Environmental factors; Environmental management; Health aspects; Image acquisition; Image Processing, Computer-Assisted; Landsat; Landsat satellites; Mathematical analysis; Mathematical models; Measurement; Methods; Models, Theoretical; Physical Sciences; Reflectance; Remote sensing; Research and Analysis Methods; Satellite imagery; Solid suspensions; Surface temperature; Technology application; Temperature; Texas; Total suspended solids; Water analysis; Water pollution; Water Quality; Water quality monitoring stations; Water sampling; Water Supply; Water temperature; Watersheds; Wind speed; Texas; United States > US; Pennsylvania

A simple approach to enable water-management agencies employing free data to create a single set of water quality predictive equations with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor varia...