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Mapping, monitoring and modelling land use and land cover change in the Mediterranean region using remote sensing and ancillary data in a GIS framework


Alterations in the Earth's surface hold major implications for the global radiation balance and energy fluxes, contribute to changes in biogeochemical cycles, alter hydrological cycles, and influence ecological balances and complexity. It is widely recognized that an understanding of land use and land cover (LULC) changes is central to the debate of sustainability. In terms of the Mediterranean region, it has been widely documented that, over the last decades, the area has been subjected to a large number o f changes. These have often been linked to the increase in erosion, desertification and land degradation observed in large parts of the region and a need for continuous observation and monitoring has been identified.

However, for all its importance to scientists and policy-makers confronting the complexities of environmental change, LULC change is still poorly understood. Remote sensing (RS) provides cost-effective multi-spectral and multi-temporal data, valuable for understanding and monitoring land development patterns and processes and for building LULC data sets in a GIS framework which provides a flexible environment for storing, analysing, and displaying digital data necessary for change detection and database development. Nevertheless, although the linkage between RS and GIS techniques has become mature over the last years, only a few LULC change studies have attempted to link RS and GIS to modelling methods, such as Markov chains, cellular automata, neural networks or statistical logistic regression.

This missing linkage has hindered modelling and assessing the dynamics of LULC change, and significantly impeded progress towards understanding of earth' atmosphere interactions, biodiversity loss, and global environmental change. This project will seek to develop an operational procedure that integrates the techniques of RS and GIS on the one hand, and modelling methods on the other, for monitoring LULC changes and predicting future trends and potential risks.

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