Opportunistic Structure-from-Motion Production and Analysis of Digital Surface Models for NOAA Coastal Airborne Imagery from Alaska’s Beaufort Sea Coast

Relative to other US coastlines, Alaska’s northern coastline from the Canadian border to Kotzebue Sound is notably lacking in elevation data that are fundamental for estimating planimetric and volumetric change along coastal bluffs, modeling storm surge impacts, and updating shoreline positions. In 2017, NOAA’s Remote Sensing Division collected 50 cm resolution, oblique and nadir georeferenced RGB digital imagery along Alaska’s northern Beaufort Sea coastline. This acquisition was intended to serve as a baseline dataset to aid in navigation, determine pre-storm conditions, and facilitate in coastal-zone management. The imagery extends along approximately 800 km of Alaska’s remote North Slope coastline, includes an additional near-infrared (NIR) band and was collected with overlap sufficient for the application of Structure-from-Motion (SfM) photogrammetric techniques. SfM techniques allow for the production of Digital Surface Models (DSMs) of complex topography using overlapping imagery and minimal ground control. Resultant ground sampling distances can exceed the resolution of air-borne LiDAR. DSM production from this image collection fills a vital gap in elevation data for this region and, when combined with near-infrared (NIR) imagery, presents an opportunity to provide additional, higher-level data products such as land/water interfaces for hydro-flattening and land cover classification. The work presented here examines initial photogrammetric products created from this dataset using SfM techniques and compares these to other elevation data. Further, their utility as tools in producing higher-level mapping products such as coastal change assessments, land cover products, and proxy-based shoreline extractions are determined. Ultimately, this work strives to understand the strengths and weaknesses of this federal dataset and to optimize how NOAA collects and disseminates this data in a way that further facilitates the production of high quality and accurate DSMs and bolsters coastal zone management.