Publicação
Integrated Coastal Vulnerability Assessment along Cascais-Lisbon Coast Using AHP and Random Forest
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| datacite.subject.sdg | 11:Cidades e Comunidades Sustentáveis | |
| datacite.subject.sdg | 13:Ação Climática | |
| datacite.subject.sdg | 14:Proteger a Vida Marinha | |
| dc.contributor.advisor | Tang, Vicente de Azevedo | |
| dc.contributor.advisor | Granell-Canut, Carlos | |
| dc.contributor.advisor | Meyer, Hanna | |
| dc.contributor.author | Menoscal, Melanie Annabela Menoscal | |
| dc.date.accessioned | 2026-03-10T14:55:01Z | |
| dc.date.available | 2026-03-10T14:55:01Z | |
| dc.date.issued | 2026-02-27 | |
| dc.description | Master of Science in Geospatial Technologies | |
| dc.description.abstract | Coastal zones are the most vulnerable environments to climate change, particularly in highly urbanized coastal cities where socio-economic pressures have modified the shoreline. Recent studies have identified that low-lying municipalities along the Tagus Estuary (Portugal) present an extreme coastal vulnerability due to increasing sea level rise (SLR) trends and more frequent storm surges, which represent a significant hazard to coastal communities and ecosystem services. This study aims to assess the coastal vulnerability along Cascais-Lisbon coastline by integrating physical and socioeconomic components using index-based method (ICVI) and Random Forest model. The assessment integrated an expert-based approach with data-driven optimization to provide a more comprehensive framework for coastal vulnerability assessments. A total of 10 parameters were used to evaluate physical and socio-economic vulnerability within a 100 m coastal setback zone recommended by coastal management guidelines to preserve coastal systems and protect communities. Results revealed that approximately 40% of the Cascais-Lisbon coastline exhibits moderate to very high vulnerability in sectors with critical residential areas and transportation infrastructure. The RF model demonstrated to be effective in enhancing ICVI classifications using AHP, by improving spatial continuity and providing a more objective assessment. Population density, coastal geomorphology and coastal elevation are considered the main drivers of vulnerability highlighting the significant role of human intervention in coastal systems. The integration of AHP and RF demonstrated a robust and replicable framework for coastal vulnerability assessments that can support coastal urban planning and adaptation strategies highlighting the importance of regulations to protect coastlines and communities. | eng |
| dc.identifier.tid | 204231272 | |
| dc.identifier.uri | http://hdl.handle.net/10362/201216 | |
| dc.language.iso | eng | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Coastal cities | |
| dc.subject | Sea-level rise | |
| dc.subject | Socio-economic vulnerability | |
| dc.subject | Physical vulnerability | |
| dc.title | Integrated Coastal Vulnerability Assessment along Cascais-Lisbon Coast Using AHP and Random Forest | eng |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | Master of Science in Geospatial Technologies |