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

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 addres...

Full description

Saved in:
Bibliographic Details
Published in:Earth science informatics 2022-09, Vol.15 (3), p.1587-1596
Main Authors: Astsatryan, Hrachya, Grigoryan, Hayk, Abrahamyan, Rita, Asmaryan, Shushanik, Muradyan, Vahagn, Tepanosyan, Garegin, Guigoz, Yaniss, Giuliani, Gregory
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Big Data
Case studies
Coastal management
Coastal zone
Coastal zone management
Coasts
Delineation
Earth and Environmental Science
Earth science
Earth Sciences
Earth System Sciences
Environmental monitoring
Freshwater lakes
Informatics
Information Systems Applications (incl.Internet)
Lakes
Monitoring
Ontology
Regional development
Regression analysis
Remote sensing
Research Article
Satellites
Shorelines
Simulation and Modeling
Space Exploration and Astronautics
Space Sciences (including Extraterrestrial Physics
Unmanned aerial vehicles
Water area
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1865-0473
1865-0481
DOI:10.1007/s12145-022-00806-7