Integrating periurban agrarian ecosystem services into spatial planning to cope with urban pressure

According to Corine Land Cover databases, in Europe between 1990 and 2000,77% of new artificial surfaces were built on previous agrarian areas. Urban sprawl ¡s far from being under control, between 2000 and 2006 new artificial land has grown in larger proportion than the decade before. In Spain, like in most countries, the impact of urban sprawl during the last decades has been especially significant in periurban agrarian spaces: between 2000 and 2006, 73% of new artificial surfaces were built on previous agrarian areas. The indirect impact of this trend has been even more relevant, as the expectations of appreciation in the value of land after new urban developments reinforce the ongoing trend of abandonment of agricultural land. In Madrid between 1980 and 2000 the loss of agricultural land due to abandonment of exploitation was 2-fold that due to transformation into urban areas. By comparing four case studies: Valladolild, Montpellier.Florence and Den Haag, this paper explores if urban and territorial planning may contribute to reduce urban pressure on the hinterland. In spite of their diversity, these regions have in common a relative prosperity arising from their territorial endowments, though their landscapes are still under pressure. The three last ones have been working for years on mainstream concepts like multifunctional agriculture. The systematic comparison and the analysis of successful approaches provide some clues on how to reconsider urban planning in order to preserve agricultural land. The final remarks highlight the context in which public commitment, legal protection instruments and financial strategies may contribute to the goals of urban, peri-urban or regional planning about fostering agrarian ecosystem services

Modelling spatial decisión support systems focused on the development of a data warehouse: applying software engineering

Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.

Foreground segmentation in depth imagery using depth and spatial dynamic models for video surveillance applications

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.