Are there common features in land cover and pattern changes in Mediterranean periurban areas ?
Notice bibliographique
Résumé
Agri-urban systems provide agro-environmental and feeding services to the cities (Zasada, 2011; De Bon et al., 2010). However, peri-urban areas are complex systems because of their geographical and productive characteristics (Van Veenhuizen, 2006; Moustier and Fall, 2004) and also for its stakeholder’s diversity (Allen, 2003; Dossa, et al., 2011). So, the dynamics of land cover features and patterns can vary according to stakeholder’s behaviour or local trends. Are there common features over scales in highly heterogeneous areas? Although case studies has been developed to identify the main landscape dynamics in the peri-urban areas (York et al., 2011; Hudalah et al., 2007), only a few of them concerned specifically the Mediterranean basin. In this context, how to quantify land cover and patterns changes in order to find common features? \nWe propose a two steps method to analyse the land cover and pattern changes occurring in Mediterranean areas. We firstly analysed land cover in urban regions during the last 30 years using a semi-supervised classification of Landsat images. We quantified changes on urban, agricultural, natural/wood, bare soil and water land cover classes and calculated a transition matrix. Secondly, we analysed the patterns of land cover using some non-correlated landscape and class metrics, also analysing the shape diversity through the method of moving windows and the optimal window size (Zhang et al., 2012). The case studies are located in the north and south of the Mediterranean basin (Montpellier-France, Pisa-Italy, Lisbon-Portugal, Meknes-Morocco, and Constantine-Algeria) (Table 1). \nThe analysis of the land cover changes suggests continuities over scales and local trends. In our case studies, the transition matrix suggested that the urban growth is associated to a decrease of the agricultural areas and an increase in the natural ones. Moreover, metrics suggests a general increase of the agricultural landscape fragmentation both for composition and configuration. Trend differences arise among case studies for the extent of urban growth, increasing of more than 10% in Montpellier and Constantine, and around 5% in the others cases. Decrease and fragmentation of agricultural spaces over long-distance area surrounding cities, coupled with an increase of natural areas, is typically a Mediterranean trend that must be compared with feeding and agro-environmental services in a currently climate change process. In addition, trends differences are not in contrast in north and south of Mediterranean basin but seem to depend on public choices about urban growth control. \nOur work is part of a project (ANR-DAUME) on the agri-urban systems dynamics to understand the changes of farmers’ managements and practices and to analyze their impact on ecosystem services. Hence, these results are a first step in building scenarios of land use change in urban Mediterranean regions and can be useful to support policy-makers at local and regional levels. \nReferences: \nAllen A., 2003. Environmental planning and management of the peri-urban interface: perspectives on an emerging field. Environment and Urbanization, 15 (1): 135-148. \nDe Bon H., Parrot L., Moustier P., 2010. Sustainable urban agriculture in developing countries. A review. Agronomy for Sustainable Development 30: 21-32. \nDossa L.H., Abdulkadir A., Amadou H. Sangare S., Schlecht E., 2011. Exploring the diversity of urban and peri-urban agricultural systems in Sudano-Sahelian West Africa: An attempt towards a regional typology. Landscape and Urban Planning, 102(3): 197-206. \nHudalah D., Winarso H., Woltier J., 2007. Peri-urbanisation in East-Asia – A new challenge for planning? International Development Planning Review 26(4): 503-519. \nMoustier P. and Fall S.A., 2004. Les dynamiques de l’agriculture urbaine: caractérisation et évaluation. In: Olanrewaju B. Smith, Moustier P., Mougeot A.J.L., Fall A., (Eds), CIRAD/CRDI, Montpellier, France, pp. 23-43. \nVeenhuizen R. van, 2006. Cities farming for the future, in: van Veenhuisen René (Ed.), Cities farming for the future: Urban agriculture for green and productive cities, RUAF Foundation, IIRR, IDRC, Ottawa, Canada, pp. 1–17. \nYork A.M., Shrestha M., Boone C.G., Zhang S.A., Harrington J.A., Prebyl T.J., Swann A., Agar M., Antolin M.F., Nolen B., Wright J.B., Skaggs R., 2011. Land fragmentation under rapid urbanization: A cross-site analysis of Southwestern cities. Urban Ecosystems 14(3): 429-455 \nZasada I., 2011. Multifunctional peri-urban agriculture – A review of societal demands and the provision of goods and services by farming. Land Use Policy 28: 639-648. \nZhang S. A., Boone C. G., York A. M., Shrestha M., 2012. Methodological Advances in the Spatial Analysis of Land Fragmentation. The Professional Geographer.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».