ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W2, 73-79, 2015
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/73/2015/
doi:10.5194/isprsannals-II-4-W2-73-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
10 Jul 2015
Visualizing Water Quality Sampling-Events in Florida
M. D. Bolt Oak Ridge Institute of Science and Education /U.S. Environmental Protection Agency Sam Nunn Atlanta Federal Center 61 Forsyth Street, SW Atlanta, GA 30303, USA
Keywords: Water Quality, Visualization, Florida, R, GIS, Spatiotemporal, Communication Abstract. Water quality sampling in Florida is acknowledged to be spatially and temporally variable. The rotational monitoring program that was created to capture data within the state’s thousands of miles of coastline and streams, and millions of acres of lakes, reservoirs, and ponds may be partly responsible for inducing the variability as an artifact. Florida’s new dissolved-oxygen-standard methodology will require more data to calculate a percent saturation. This additional data requirement’s impact can be seen when the new methodology is applied retrospectively to the historical collection. To understand how, where, and when the methodological change could alter the environmental quality narrative of state waters requires addressing induced bias from prior sampling events and behaviors. Here stream and coastal water quality data is explored through several modalities to maximize understanding and communication of the spatiotemporal relationships. Previous methodology and expected-retrospective calculations outside the regulatory framework are found to be significantly different, but dependent on the spatiotemporal perspective. Data visualization is leveraged to demonstrate these differences, their potential impacts on environmental narratives, and to direct further review and analysis.
Conference paper (PDF, 925 KB)


Citation: Bolt, M. D.: Visualizing Water Quality Sampling-Events in Florida, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4/W2, 73-79, doi:10.5194/isprsannals-II-4-W2-73-2015, 2015.

BibTeX EndNote Reference Manager XML