Scientific article
OA Policy
English

Shoreline delineation service: using an earth observation data cube and sentinel 2 images for coastal monitoring

Publication date2022-05-07
First online date2022-05-07
Abstract

Coastal management has a critical role in estimating the coastal environmental and socio-economic dynamics, providing various vital regional and local services. Remote sensing earth observations are essential for detecting and monitoring shorelines. UAVs combined with satellite remote sensing address the shoreline delineation problems to detect the shoreline and identify the shoreline zones. The paper presents a shoreline delineation service utilizing UAV and Sentinel 2 images within a Data Cube environment for monitoring coastal areas. The BandRatio, McFeeters, MNDWI1, and MNDWI2 algorithms have been implemented in the service to analyze the accuracy of each algorithm by comparing satellite and UAV-derived shorelines. As a case study, the Lake Sevan shoreline delineation, as one of the most incredible freshwater lakes in Eurasia, has been studied using the service. MNDWI2 algorithm showed the best accuracy for Lake Sevan shoreline delineation.

Keywords
  • Unmanned aerial vehicle
  • Satellite remote sensing
  • Sentinel-2
  • Data cube
  • Shoreline
  • NDWI
  • MNDWI
  • Mixed pixels
  • Water extraction algorithms
  • Lake sevan
Funding
  • European Commission - National Initiatives for Open Science in Europe [857645]
Citation (ISO format)
ASTSATRYAN, Hrachya et al. Shoreline delineation service: using an earth observation data cube and sentinel 2 images for coastal monitoring. In: Earth science informatics, 2022. doi: 10.1007/s12145-022-00806-7
Main files (1)
Article (Published version)
accessLevelPublic
Identifiers
Additional URL for this publicationhttps://link.springer.com/10.1007/s12145-022-00806-7
Journal ISSN1865-0473
258views
287downloads

Technical informations

Creation09/05/2022 05:55:00
First validation09/05/2022 05:55:00
Update24/10/2025 13:28:39
Status update24/10/2025 13:28:39
Last indexation24/10/2025 13:33:03
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