Predicting land use change on a broad area: Dyna-CLUE model application to the Litorale Domizio-Agro Aversano (Campania, South Italy)

The long-standing awareness of the environmental impact of land-use change (LUC) has led scientific community to develop tools able to predict their amount and to evaluate their effect on environment, with the aim supporting policy makers in their planning activities. This paper proposes an implementation of the Dyna-CLUE (Dynamic Conversion of Land Use and its Effects) model applied to the Litorale Domizio-Agro Aversano, an area of Campania region, which needs interventions for environmental remediation. Future land use changes were simulated in two different scenarios developed under alternative strategies of land management: scenario 1 is a simple projection of the recent LUC trend, while scenario 2 hypothesises the introduction of no-food crops, such as poplar (Populus nigra L.) and giant reed (Arundo donax L.), in addition to a less impactful urban sprawl, which is one of the main issues in the study area. The overall duration of simulations was 13 years, subdivided into yearly time steps. CORINE land cover map of 2006 was used as baseline for land use change detection in the study area. Competition between different land use types is taken into account by setting the conversion elasticity, a parameter ranging from 0 to 1, according to their capital investment level. Location suitability for each land use type is based on logit model. Since no actual land use already exists for the alternative crops investigated in scenario 2, a suitability map realised through a spatial multicriteria decision analysis was used as a proxy for its land use pattern. The comparison of the land use in 2012 and scenario 1, evaluated through the application of Kappa statistics, showed a general tendency to expansion of built-up areas, with an increase of about 2400 ha (1.5% of the total surface), at the expense of agricultural land and those covered by natural vegetation. The comparison of the land use in 2012 and scenario 2 showed a less significant spread of built-up areas, affecting approximately 750 ha (0.5% of the total surface). Moreover, the introduction of alternative crops on about 10,000 ha, that is 6.8% of the total surface, would result in a significant decrease of arable land and a lower decrease of permanent crops, respectively equal to 6800 ha and 2900 ha. This work highlighted the importance and the potential of predicting land-use change models as valid tools supporting decisions, especially in those regions needing interventions aimed to environmental remediation, as in the case study examined in this paper.