Abstract
Monitoring water body quality parameters with high spatial and temporal resolutions is crucial because mitigation of pollution is usually costlier than early prevention/intervention. The existing monitoring methods for irrigation ponds in Taoyuan, Taiwan, are based on field measurements that have low spatial and temporal resolutions. In this study, using Landsat 8 satellite imagery, a multiple regression-derived relationship between the satellite band reflectance and the concentration of total phosphorus (TP) was established. The satellite imagery was atmospherically corrected with ACOLITE based on shortwave infrared (SWIR) bands. This method was used to select predictor variables in the multiple regression-derived equation based on forward selection of variables using a p value and variation inflation factor (VIF) threshold. The derived equation yielded a coefficient of determination (R2) of 0.67. The near-infrared band (band 5) was found to be most significant. The Landsat 8 imagery retrieved for two of the three pond studies included only a few pixels from the ponds because parts of the pond surfaces are covered by floating photovoltaic power plants. The TP concentrations resulting from the derived equation indicate the feasibility of using satellite remote sensing methods to monitor the water quality. The derived relationships are potentially applicable to extend the availability of temporal and spatial water quality data for these irrigation ponds.
Highlights
Continuous water quality monitoring for human health and well-being and ecosystems are crucial to survival
The satellite imagery was atmospherically corrected with ACOLITE based on shortwave infrared (SWIR) bands
These findings suggest that multispectral satellite imagery can be used to use various methods to estimate water quality, and most of them use multiple regression analysis or artificial neural networks (ANNs) (Kloiber et al, 2002; Liu et al, 2003; Kishino et al, 2005)
Summary
Continuous water quality monitoring for human health and well-being and ecosystems are crucial to survival. The settlement of suspended sediment usually displays strong light after the spread (Liu et al, 2003), but the actual color depends on the origin of the land (Bukata, 2005) These findings suggest that multispectral satellite imagery can be used to use various methods to estimate water quality, and most of them use multiple regression analysis or artificial neural networks (ANNs) (Kloiber et al, 2002; Liu et al, 2003; Kishino et al, 2005). The applicability of the results is usually limited to the same water body because the spectral response of suspended sediments depends on their terrestrial origin, and the distribution of sediment particle size affects turbidity, even if the concentration of suspended sediments is the same (Liu et al, 2003; Bukata, 2005)
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