Journal
REMOTE SENSING OF ENVIRONMENT
Volume 229, Issue -, Pages 260-270Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2019.04.010
Keywords
Satellite images; Coastline; NDWI; Water classification
Funding
- U.S. National Science Foundation Office of Polar Programs [A005265701]
- NASA Cryosphere program
- Polar Geospatial Center under NSF-OPP [1043681, 1559691, 1542736]
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This paper presents a new coastline extraction method that improves water classification accuracy by benefitting from an ever-increasing volume of repeated measurements from commercial satellite missions. The widely-used Normalized Difference Water Index (NDWI) method is tested on a sample of around 12,600 satellite images for statistical analysis. The core of the new water classification method is the use of a water probability algorithm based on the stacking of repeat measurements, which can mitigate the effects of translational offsets of images and the classification errors caused by clouds and cloud shadows. By integrating QuickBird, WorldView-2 and WorldView-3 multispectral images, the final data product provides a 2 m resolution coastline, as well as a 2 m water probability map and a repeat-count measurement map. Improvements on the existing coastline (GSHHS-the Global Self-consistent, Hierarchical, High-resolution Shoreline Database, 50 m-5000 m) in terms of resolution (2 m) is substantial, thanks to the combination of multiple data sources.
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