The analysis of changes in land cover and land use over time as sources of information and geographical diagnosis at a regional scale, is primary to improving knowledge of land cover and land use modelling in Mediterranean environments. The study area is located in the Marina Baixa (MB) county and catchment (680 km2; Alicante, Spain). It comprises 18 municipalities which for the period under study present a landscape mosaic, Benidorm is the capital city of the county. In its turn, this region has undergone great socio-economic changes over recent decades, which can be attributed to tourism development and agricultural intensification. The main driving forces of landscape change are economic and social (tourism development, agriculture) but urban planning is also a key element to take into account in the land use model. The main change attractors can be described as coastal proximity and water availability factors, that are responsible for the transformation from traditional land uses to new land uses with higher water demand and sea-shore zones highly urbanized. Analysis of aerial photographs for the years 1956, 1978 and 2000 in MB revealed an increment of artificial surfaces mostly near the shoreline; an augment of irrigated crops surface; and a significant decline in traditional dry crops due to the abandonment because of their low productivity, therefore it is a growth of natural areas. We have studied the evolution of land cover and land use in MB catchment through time (1956-1978-2000). However, in this study we test the hypothesis that landscape changes in Marina Baixa in 2000 could be predicted from 1956-1978 land use changes. In order to generate land use and land cover map of 2000, we use a combined Cellular Automata, Markov Chain and Multi-Criteria land cover prediction procedure. The application of multiple models is powerful to represent the spatial contiguity as well as knowledge of the likely spatial distribution of transitions to Markov chain analysis. The span between two studied periods is 22 years. The goal is to calibrate the model to predict, as well as possible, the land use changes in 2000, with the purpose to predict the long-term changes beyond.
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