Spatially explicit modeling of the probability of land abandonment in the Spanish Pyrenees
Resumen: Many mountain regions in Europe have experienced massive migrations towards metropolitan areas, with far-reaching implications for societies and the environment, especially croplands and grasslands. In this work, we tailored a geospatial framework to envisage the probability of land abandonment in the Spanish Pyrenees at moderate spatial resolution. We predicted the likelihood of land abandonment combining machine learning algorithms, geospatial data and historical observations of land abandonment in the period 1980 to 2019. The model attained a high predictive performance (AUC = 0.85) at a moderate resolution (30 m), providing insights into the spatial behavior of the potential for both abandonment and its main driving forces. The highest rates of abandonment were found in rural settlements and towns in bottom valleys where tourism and recreational activities have proliferated over the years. Fast and comfortable connections between the main metropolitan areas (e.g. Barcelona and Zaragoza) and the mountain regions foster touristic activity and lead to the creation of new settlements. Ecotourism and mountain sports promote land abandonment as evidenced by the high probability predicted over the Central Pyrenees (from Pallars Jussà to Alto Gállego counties). Our results provide spatially explicit probability and uncertainty outputs, providing insights into site-specific abandonment potential and the influence of its drivers. These results can substantially assist land planners in decision-making, enabling assessments at local scale.
Idioma: Inglés
DOI: 10.1016/j.landurbplan.2022.104487
Año: 2022
Publicado en: LANDSCAPE AND URBAN PLANNING 226 (2022), 104487 [11 pp.]
ISSN: 0169-2046

Factor impacto JCR: 9.1 (2022)
Categ. JCR: ECOLOGY rank: 7 / 171 = 0.041 (2022) - Q1 - T1
Categ. JCR: ENVIRONMENTAL STUDIES rank: 11 / 128 = 0.086 (2022) - Q1 - T1
Categ. JCR: REGIONAL & URBAN PLANNING rank: 3 / 40 = 0.075 (2022) - Q1 - T1
Categ. JCR: URBAN STUDIES rank: 1 / 43 = 0.023 (2022) - Q1 - T1
Categ. JCR: GEOGRAPHY, PHYSICAL rank: 2 / 49 = 0.041 (2022) - Q1 - T1
Categ. JCR: GEOGRAPHY rank: 2 / 86 = 0.023 (2022) - Q1 - T1

Factor impacto CITESCORE: 14.4 - Social Sciences (Q1) - Environmental Science (Q1)

Factor impacto SCIMAGO: 2.065 - Ecology (Q1) - Urban Studies (Q1) - Nature and Landscape Conservation (Q1) - Management, Monitoring, Policy and Law (Q1)

Financiación: info:eu-repo/grantAgreement/ES/FECYT/IMAGINE CGL2016-80400-R
Tipo y forma: Artículo (Versión definitiva)
Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)

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