Unveiling soil degradation and desertification risk in the Mediterranean basin: a data mining analysis of the relationships between biophysical and socioeconomic factors in agro-forest landscapes
| Autor: | C. A. Karavitis, Miloud Chaker, Hasan Güngör, Rudi Hessel, Abdellah Laouina, Candan Gokceoglu, A. Kounalaki, Albert Solé-Benet, J. de Vente, Faruk Ocakoğlu, Mongi Sghaier, A. Belgacem, H. Taamallah, Orestis Kairis, Costas Kosmas, Luca Salvati, H. Khatteli, Sanem Acikalin, V. Fassouli, H. Sonmez, Coen J. Ritsema, L. Tezcan, Mohamed Ouessar |
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| Rok vydání: | 2014 |
| Předmět: |
Mediterranean climate
human pressure media_common.quotation_subject vulnerability Geography Planning and Development response assemblage system Management Monitoring Policy and Law computer.software_genre Mediterranean Basin land-use change Soil retrogression and degradation spain Land use land-use change and forestry CB - Bodemfysica en Landgebruik Mediterranean region General Environmental Science Water Science and Technology media_common Fluid Flow and Transfer Processes region Alterra - Soil physics and land use data mining erosion abandonment indicators Geography Desertification Land degradation Erosion Spatial ecology Data mining europe computer performance SS - Soil Physics and Land Use Alterra - Bodemfysica en landgebruik |
| Zdroj: | Journal of Environmental Planning and Management, 58(10), 1789-1803 Journal of Environmental Planning and Management 58 (2015) 10 |
| ISSN: | 1360-0559 0964-0568 |
| Popis: | Soil degradation and desertification processes in the Mediterranean basin reflect the interplay between environmental and socioeconomic drivers. An approach to evaluate comparatively the multiple relationships between biophysical variables and socioeconomic factors is illustrated in the present study using the data collected from 586 field sites located in five Mediterranean areas (Spain, Greece, Turkey, Tunisia and Morocco). A total of 47 variables were chosen to illustrate land-use, farm characteristics, population pressure, tourism development, rainfall regime, water availability, soil properties and vegetation cover, among others. A data mining approach incorporating non-parametric inference, principal component analysis and hierarchical clustering was developed to identify candidate syndromes of soil degradation and desertification risk. While field sites in the same study area showed a substantial similarity, the multivariate relationship among variables diverged among study areas. Data mining techniques proved to be a practical tool to identify spatial determinants of soil degradation and desertification risk. Our findings identify the contrasting spatial patterns for biophysical and socioeconomic variables, in turn associated with different responses to land degradation. |
| Databáze: | OpenAIRE |
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