Automated Workflows and Machine Learning Techniques for Coastline Extraction
Learn how to use ArcGIS automated workflows and machine learning techniques for coastline extraction.
Due to anthropogenic activities and natural processes—for example, sea level changes, sedimentation, and wave energy—coastlines are changing worldwide. Traditionally, coastlines were manually digitized, which is a time and labor-intensive way. Remote sensing is an excellent alternative to extract coastlines, using satellite imagery. Satellite imagery of visible range can be used for interpretation and easily obtained. But the imageries covering infrared wavelength is best to extract the boundary between land and water. The band ratio technique is easy to calculate and gives highly accurate results in less processing time. The workflow can be applied to any area using multispectral imagery, Landsat 8 or Sentinel-2.
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Additional Resources:
Presentation Deck
Map scale and raster resolution
Story map: Coastline extraction using Landsat-8 (Image Server) as source
Sample Notebook: Coastline extraction using Landsat-8 (Image Server) as source
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