Publicação
Enhancing Ecosystem-based Disaster Risk Reduction Through Geoinformatics: Integrating Ecological Factors into Assessment Practices
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | |
| datacite.subject.sdg | 03:Saúde de Qualidade | |
| datacite.subject.sdg | 11:Cidades e Comunidades Sustentáveis | |
| datacite.subject.sdg | 12:Produção e Consumo Sustentáveis | |
| datacite.subject.sdg | 13:Ação Climática | |
| datacite.subject.sdg | 15:Proteger a Vida Terrestre | |
| dc.contributor.advisor | Cabral, Pedro da Costa Brito | |
| dc.contributor.advisor | Campos, Felipe Siqueira e | |
| dc.contributor.author | Broquet, Melanie | |
| dc.date.accessioned | 2026-02-27T16:36:58Z | |
| dc.date.available | 2026-02-27T16:36:58Z | |
| dc.date.issued | 2026-01-27 | |
| dc.description | A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management | |
| dc.description.abstract | Ecosystem-based Disaster Risk Reduction (Eco-DRR) leverages ecosystem conservation and restoration to mitigate natural disaster risks by providing regulatory services that reduce their intensity and lower the vulnerability of exposed communities and ecosystems. Despite growing recognition, especially after the 2004 Indian Ocean tsunami, Eco-DRR faces key barriers: limited consensus on ecosystem effectiveness, inconsistent methodologies, data scarcity, and the absence of standardized frameworks that integrate ecological factors into disaster risk assessments. This study addresses these gaps by using landslide hazard as a case study to strengthen the credibility and acceptance of Eco-DRR through empirical evidence and improved assessment practices. Three inter-connected objectives guided the work: (1) identifying ecological factors relevant for landslide susceptibility assessment (LSA) through literature review; (2) examining the relationship between Land Use/Land Cover (LULC) and habitat quality as indicators of hazard-prone landscapes using the InVEST Habitat Quality model; and (3) testing whether integrating ecological variables into LSA frameworks improves predictive performance using Random Forests. Findings show that eco-environmental factors, especially dynamic ones, remain underutilized in LSAs. LULC change was strongly correlated with ecological degradation, supporting the use of integrative indicators such as habitat quality for characterizing vulnerable landscapes. Integrated models combining structural and ecological variables, particularly dynamic ones, significantly outperformed conventional LSA models. These results confirm that eco-environmental variables play a critical role in shaping landslide susceptibility and should be systematically integrated into risk assessments. Overall, this research strengthens Eco-DRR’s scientific foundation by moving beyond static, hazard-centric approaches. It introduces evidence-based methodologies that are applicable even in data-scarce contexts, replicable across settings. By promoting cross-disciplinary integration and efficiency, the work helps bridge the knowledge–action gap, enhances policy relevance, and underscores ecosystems as critical assets whose protection and restoration are essential for breaking the cycle of degradation and disaster risk. | eng |
| dc.identifier.tid | 101784120 | |
| dc.identifier.uri | http://hdl.handle.net/10362/200784 | |
| dc.language.iso | eng | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Remote Sensing | |
| dc.subject | Geographic Information Systems | |
| dc.subject | Ecosystem-Based Disaster Risk Reduction | |
| dc.subject | Landslide Susceptibility Assessment | |
| dc.subject | Nature-based Solutions | |
| dc.title | Enhancing Ecosystem-based Disaster Risk Reduction Through Geoinformatics: Integrating Ecological Factors into Assessment Practices | eng |
| dc.type | doctoral thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | Doutoramento em Gestão de Informação |