Repository logo
 
Publication

Combining optical and SAR satellite data to monitor coastline changes in the Black Sea

dc.contributor.authorJiang, Dalin
dc.contributor.authorMarino, Armando
dc.contributor.authorIonescu, Maria
dc.contributor.authorGvilava, Mamuka
dc.contributor.authorSavaneli, Zura
dc.contributor.authorLoureiro, Carlos
dc.contributor.authorSpyrakos, Evangelos
dc.contributor.authorTyler, Andrew
dc.contributor.authorStanica, Adrian
dc.date.accessioned2025-07-04T09:04:29Z
dc.date.available2025-07-04T09:04:29Z
dc.date.issued2025-08
dc.description.abstractThe coastal environments of the Black Sea are of high ecological and socio-economic importance. Understanding changes along this extensive and complex coastline can help us comprehend the pressures from nature, society, and extreme events, providing valuable insights for more effective management and the prevention of future adverse changes. Current methods for monitoring coastal dynamics rely on the accurate extraction of coastlines from optical and/or Synthetic Aperture Radar (SAR) images, providing information only on the rate of change. This study developed a simple yet novel approach by combining Sentinel-1 SAR image for surface change detection and Sentinel-2 Multispectral Instrument (MSI) optical image for coastline detection, which provides data on both the rate and area of change. Coastlines were extracted from the Modified Normalised Difference Water Index (MNDWI) calculated from MSI images and rates of change were calculated from the extracted coastlines. SAR images for the same areas were stacked and differences during the analysis period were calculated, allowing the determination of the area of change. Another new method was developed to combine the changes detected from optical and SAR images, and only results in locations showed consistent change direction (erosion or accretion) were retained. The extracted coastlines were validated using in situ-measured coastlines along the Romanian and Georgian coasts. The validation analysis showed that the average difference between satellite-derived and in situ coastlines was 11.8 m. The method developed was then applied to the entire Black Sea coast, revealing 35.1 km2 of changes between 2016 and 2023. These observed changes include 23.9 km2 (68 %) coastal advance and 11.3 km2 (32 %) of retreat. A total of 54 % of the changes are estimated to be the result of natural coastline erosion or accretion, whilst 35 % can be attributed to artificial changes related to construction activity. Around 11 % are attributed to random occurrences due to boat/ship movement or land cover changes on adjacent land. Natural coastline changes were mainly observed in the vicinity of deltaic and estuarine system and along sandy shorelines, including along the Danube Delta, K & imath;z & imath;l & imath;rmak-Yes,il & imath;rmak deltas, Chorokhi-Rioni-Kodori River mouths and the coast from Dnieper-Bug Estuary to Karkinit Bay. Artificial changes were mainly found along the southern Black Sea coast, where airports, ports, harbours, and jetties have been constructed in recent years. The proposed method provides a simple, efficient and accurate way for coastline change monitoring, and findings in this study can support the sustainable coastal zone management in the Black Sea.eng
dc.description.sponsorshipCEECINST/00052/2021/CP2792/CT0011; LA/P/00069/2020;
dc.identifier.doi10.1016/j.isprsjprs.2025.05.003
dc.identifier.issn0924-2716
dc.identifier.urihttp://hdl.handle.net/10400.1/27352
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationCentre for Marine and Environmental Research (CIMA)
dc.relation.ispartofISPRS Journal of Photogrammetry and Remote Sensing
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBlack Sea
dc.subjectCoastline
dc.subjectErosion
dc.subjectArtificial shorelines
dc.subjectEarth observation
dc.titleCombining optical and SAR satellite data to monitor coastline changes in the Black Seaeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Marine and Environmental Research (CIMA)
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00350%2F2020/PT
oaire.citation.endPage115
oaire.citation.startPage102
oaire.citation.titleISPRS Journal of Photogrammetry and Remote Sensing
oaire.citation.volume226
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLoureiro
person.givenNameCarlos
person.identifier453264
person.identifier.ciencia-id011D-31BD-C6B6
person.identifier.orcid0000-0003-3117-3492
person.identifier.ridU-9863-2018
person.identifier.scopus-author-id23667861200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication0da09945-415f-4574-a444-268a1c05b544
relation.isAuthorOfPublication.latestForDiscovery0da09945-415f-4574-a444-268a1c05b544
relation.isProjectOfPublication62b4d568-8b21-464c-97ed-de826eab4136
relation.isProjectOfPublication.latestForDiscovery62b4d568-8b21-464c-97ed-de826eab4136

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1-s2.0-S0924271625001844-main.pdf
Size:
21.38 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.46 KB
Format:
Item-specific license agreed upon to submission
Description: