Integrating landscape analysis and multicriteria decision-making to prioritize forest restoration areas in human-modified landscapes

• Ano de defesa: 2025
• Autor(a) principal: Morales, Milton Vinícius
• Orientador(a): Valente, Roberta Averna
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus Sorocaba
• Programa de Pós-Graduação: Programa de Pós-Graduação em Planejamento e Uso de Recursos Renováveis - PPGPUR-So
• Palavras-chave em Português: Restauração Florestal; Priorização de Áreas; Análise Multicriterial; Manejo de Bacias Hidrográficas; Análise da Paisagem
• Palavras-chave em Inglês: Forest Restoration; Area Prioritization; Multicriteria Analysis; Landscape Analysis; Watershed Management
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS; CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL
• Link de acesso: https://hdl.handle.net/20.500.14289/22109

This study proposes an integrated approach combining the analysis of the landscape's eco-logical, anthropical, and biophysical components with multicriteria decision-making meth-ods to prioritize forest restoration areas in human-modified landscapes. The research begins with a systematic literature review (Chapter I) that identifies and categorizes the primary spatial criteria employed in decision-making processes for restoration, highlighting method-ological gaps and the need for standardization in selecting and applying these criteria. Sub-sequently, a spatiotemporal analysis of the Sarapuí River Basin (Chapter II) reveals land-use dynamics and the phenomenon of forest cover rejuvenation, allowing for identifying areas with the potential to trigger successional processes and enhance ecological connectivity. Next, mapping the human footprint (Chapter III) integrates environmental and socioeconom-ic aspects, providing an accurate diagnosis of anthropogenic pressures on the landscape. Fi-nally, the proposed decision framework (Chapter IV) consolidates the previous results by establishing a robust and replicable multicriteria decision analysis (MCDA) method for pri-oritizing restoration areas, with potential applications in public policies and Payment for Environmental Services initiatives. The findings demonstrate that the convergence of spatial data, environmental dynamics, and structured decision processes can optimize the allocation of investments and efforts for the effective ecological restoration of degraded environments, ultimately contributing to biodiversity conservation, climate change mitigation, and sustain-able development.