Online, On Demand Access to Coastal Digital Elevation Models

Process-based numerical models for coastal waves, water levels, and sediment transport are initialized with digital elevation models (DEM) constructed by interpolating and merging bathymetric and topographic elevation data. These gridded surfaces must seamlessly span the land-water interface and may cover large regions where the individual raw data sources are collected at widely different spatial and temporal resolutions. In addition, the datasets are collected from different instrument platforms with varying accuracy and may or may not overlap in coverage. The lack of available tools and difficulties in constructing these DEMs lead scientists to 1) rely on previously merged, outdated, or over-smoothed DEMs; 2) discard more recent data that covers only a portion of the DEM domain; and 3) use inconsistent methodologies to generate DEMs.

The objective of this work is to address the immediate need of integrating land and water-based elevation data sources and streamline the generation of a seamless data surface that spans the terrestrial-marine boundary. To achieve this, the U.S. Geological Survey (USGS) is developing a web processing service to format and initialize geoprocessing tasks designed to create coastal DEMs. The web processing service is maintained within the USGS ScienceBase data management system and has an associated user interface. Through the map-based interface, users define a geographic region that identifies the bounds of the desired DEM and a time period of interest. This initiates a query for elevation datasets within federal science agency data repositories. A geoprocessing service is then triggered to interpolate, merge, and smooth the data sources creating a DEM based on user-defined configuration parameters. Uncertainty and error estimates for the DEM are also returned by the geoprocessing service. Upon completion, the information management platform provides access to the final gridded data derivative and saves the configuration parameters for future reference. The resulting products and tools developed here could be adapted to future data sources and projects beyond the coastal environment.