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ORCID: https://orcid.org/0000-0002-9298-0178, Merino de Miguel, Silvia
ORCID: https://orcid.org/0000-0002-4764-5311, Uchôa, Jéssica
ORCID: https://orcid.org/0000-0001-6165-8381 and Gil, Artur
ORCID: https://orcid.org/0000-0003-4450-8167
(2024).
A Land Cover Change Detection Approach to Assess the Effectiveness of Conservation Projects: A Study Case on the EU-Funded LIFE Projects in São Miguel Island, Azores (2002–2021).
"Land", v. 13
(n. 5);
ISSN 2073-445X.
https://doi.org/10.3390/land13050666.
| Título: | A Land Cover Change Detection Approach to Assess the Effectiveness of Conservation Projects: A Study Case on the EU-Funded LIFE Projects in São Miguel Island, Azores (2002–2021) |
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| Autor/es: |
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| Tipo de Documento: | Artículo |
| Título de Revista/Publicación: | Land |
| Fecha: | 12 Mayo 2024 |
| ISSN: | 2073-445X |
| Volumen: | 13 |
| Número: | 5 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Remote sensing; oceanic islands; Python; Rao’s Q; land use; land cover; open data; Google Earth Engine; Google Colab |
| Escuela: | E.T.S.I. Montes, Forestal y del Medio Natural (UPM) |
| Departamento: | Ingeniería y Gestión Forestal y Ambiental |
| Licencias Creative Commons: | Reconocimiento |
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Small oceanic islands, such as São Miguel Island in the Azores (Portugal), face heightened susceptibility to the adverse impacts of climate change, biological invasions, and land cover changes, posing threats to biodiversity and ecosystem functions and services. Over the years, persistent conservation endeavors, notably those supported by the EU LIFE Programme since 2003, have played a pivotal role in alleviating biodiversity decline, particularly in the eastern region of São Miguel Island. This study advocates the application of remote sensing data and techniques to support the management and effective monitoring of LIFE Nature projects with land cover impacts. A land cover change detection approach utilizing Rao’s Q diversity index identified and assessed changes from 2002 to 2021 in intervention areas. The study analyzed the changes in LIFE project areas using ASTER, Landsat 8, and Sentinel 2 data through Google Earth Engine on Google Colab (with Python). This methodological approach identified and assessed land cover changes in project intervention areas within defined timelines. This technological integration enhances the potential of remote sensing for near-real-time monitoring of conservation projects, making it possible to assess their land cover impacts and intervention achievements.
| ID de Registro: | 89765 |
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| Identificador DC: | https://oa.upm.es/89765/ |
| Identificador OAI: | oai:oa.upm.es:89765 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/10221379 |
| Identificador DOI: | 10.3390/land13050666 |
| URL Oficial: | https://www.mdpi.com/2073-445X/13/5/666 |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 02 Jul 2025 09:36 |
| Ultima Modificación: | 23 Mar 2026 15:37 |
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