Propagation of marine data through various spatial scales for the purpose of marine spatial planning
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Managing the marine environment can be difficult due to multiple changes through space and time and the many natural processes and activities that occur on the water surface, in the water column, and on the seafloor. Marine spatial planning is used to help coordinate development and expansion of the many uses of the marine environment. Managing these areas requires mapping the biophysical conditions with remote sensing and direct observational techniques to gain a better understanding of important elements. Much of the final mapping is done using Geographic Information Systems (GIS), but areas are often only mapped in relatively small sections even though marine ecosystems occur over larger areas. In this study, multibeam bathymetric data from seventeen subregions off the coast of South Carolina were analyzed to develop maps at two different scales. Statistics were calculated for the rugosity and the previously developed principal component analysis (PCA) data to examine and compare characteristics across different spatial scales. These results were used to determine the best way to transfer information from a finer scale to a coarser scale for the purposes of better data for marine system managers. The results from this analysis show that the maximum value statistic of the rugosity data best brings important data from raw data to a coarser scale. The standard deviation statistic of the rugosity data was also viable, but to a lesser extent. The process developed in this study is beneficial to managers and other decision makers since it provides a quick way to identify areas that may need to be examined at a finer scale and helps create management or recovery plans for many different fisheries and endangered species.