QUANTITATIVE REMOTE SENSING OF SURFACE WATER QUALITY IN SOUTHEAST TENNESSEE USING PLANET DOVE IMAGERY

Space-borne remote sensing technology has been used successfully for surface water quality studies for more than two decades as it provides an opportunity for synoptic and multi-temporal viewing of water quality. The optical properties (i.e. reflectance) of water depend on the concentration and characteristics of suspended sediments, phytoplankton, and dissolved organic matters. Sensors aboard satellites can measure the amount of solar radiation at various wavelengths reflected by surface water, which can be correlated to different water quality parameters. This constitutes an alternative means of estimating water quality, which offers three significant advantages over ground sampling. First, the near-continuous spatial coverage of satellite imagery allows for synoptic estimates over large areas. Second, the global coverage of satellites allows for the estimation of water quality in remote and inaccessible areas. Third, the relatively long record of archived imagery allows estimation of historical water quality, when no ground measurements can possibly be performed. Currently, no remote sensing based algorithm is available to study surface water quality at high spatial resolution in Southeast Tennessee. This study aims to investigate the potential of the PlanetScope Dove Imagery to study surface water quality in the watersheds of Southeast Tennessee using satellite observations coupled with field measurements. PlanetScope provides daily imagery across the globe at 3 meter spatial resolution, which promises to improve the temporal and spatial accuracy involved with water quality monitoring.

This is an ongoing research project, which is currently developing a series of numerical models to estimate Turbidity, Chlorophyll, Conductivity, pH, and Dissolved Oxygen (DO) in the Tennessee River and adjacent tributaries using recently acquired satellite imagery and concurrently obtained in situ measurements of corresponding water quality data. This paper presents the preliminary results of this research focusing the application of Planet Dove imagery.