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Modelling the impact of urban growth on agriculture and natural land in Italy to 2030

Author:
Martellozzo, F., Amato, F., Murgante, B., Clarke, K.C.
Source:
Applied geography 2018 v.91 pp. 156-167
ISSN:
0143-6228
Subject:
agricultural land, cities, climate, geography, issues and policy, land use change, markets, models, regional planning, socioeconomics, sustainable land management, towns, urban areas, urbanization, Italy
Abstract:
The uncontrolled spread of towns and cities into their surrounding rural and natural land, and the consequent increasing demand for new natural resources are among the most important drivers of global climate and environmental change. This study investigated the loss of natural and agricultural land in Italy in the last decades, during which urban areas have undergone significant expansion. The study underlines the negative consequences of past uncoordinated urban and regional planning in Italy which often featured adaptive ex-post strategies favouring real estate market returns, rather than avoiding ex-ante the unsustainable threats. The aim is to show that only through a recalibration of priorities in planning, by adding policies that favour ecological conservation, it is possible to better foster sustainable land use practices. To this end, the research features a comparison of forecasts of land-use/cover changes (LUCC) corresponding to different policy-oriented scenarios, using a combination of multi criteria analysis and cellular automata modelling. In the planning literature there are many applications of land-use change modelling at the regional/local scale, however to the best of our knowledge, none does it at high resolution and at the full country scale. This sort of analysis is important for policy makers because it allows investigation of the combined relevance of local and global criteria in influencing urbanization for the future. Thus it couples locally relevant findings with a comprehensive vision of the phenomenon at a national scale. We conclude by discussing some critical socio-economic implications of the modelled scenarios in order to provide policy makers with useful tools and information to develop resilient and sustainable planning strategies.
Agid:
5895701