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The present study aims to develop an integrated methodology using multi-criteria decision-making methods and geographical information systems for a renewable energy spatial planning model. This methodology has been applied to the province of Malaga (Southern Spain), which is characterised by high energy demand for both residential and touristic use. Criteria and restrictions are defined, weighed and combined in order to identify high potential areas for the construction of single- or combined wind power, solar power and biomass generation facilities. Finally, a cluster analysis is carried out in order to classify municipalities within the province according to the availability of medium and high potential land for the construction of these facilities. Results suggest that for the three types of energy analysed (wind, solar and biomass), single- or combined solar and wind power facilities are the best options in the province of Malaga. The breakdown of these results at the municipality level is of great interest from the point of view of spatial planning. For instance, in some municipalities less than 1 km2 is regarded as having a medium-to-high potential in terms of renewables. Some of these municipalities, situated on the Costa del Sol, must meet high current- and future energy demands, owing both to population density and the volume of touristic demand, which is the highest in the region of Andalusia. The methodology used can be applied to other regions and will be of interest for planners, managers and investors, all of whom can use this information for spatial- and energy planning, and the definition of targets and strategies, and, therefore, as and to aid decision-making.Graphic abstract

The present study aims to develop an index composed of different spatial variables to measure the urban sprawl levels of a municipality located in Southern Spain. According to the findings, urban sprawl can be measured not only on the metropolitan level but also on a more detailed and precise level, such as sub-municipal. A group of experts chosen for their suitability in measuring urban sprawl select six spatial variables (population density, net residential density, coverage ratio, land use types, percentage of residential land use, and average year of construction). These variables are aggregated using Choquet integral, a technique that combines interactions between those variables providing greater coherence to the complexity that is inherent in the creation of composite sprawl indexes. This methodology has been demonstrated to be valid and appropriate in evaluating urban expansion at sub-municipal level, but can also be applied to other scales once it is clearly a phenomenon in which interaction between criteria exists. The resulting composite index allows the assignment of different levels of sprawl to the urban areas consistent with their morphology and landscape.

This work aims to develop a methodology for selecting optimum locations for the construction of photovoltaic power plants. In order to achieve this, a data model is defined and a multi-criteria decision methodology, based on an analytical hierarchy process, is applied. In contrast to the previous studies, in which the spatial analysis was undertaken by a GIS managing different layers of information (grids, shapefiles, etc.), in this work the spatial analysis is carried out by means of an open-code spatial database management system: PostgreSQL-PostGIS. This system uses Structure Query Language to manage different tables in the context of relational spatial databases. The case study is the province of Seville (southern Spain), where this sort of facility already exists. The empirical analysis concludes that a large percentage of the province of Seville has an excellent potential for the installation of photovoltaic plants. The methodology allows the dynamic updating of criteria and parameters, as well as the reproducibility, scalability and automating of analyses carried out in other fields.

This work calculates the current heating and cooling degree days and also examines heating and cooling degree days in relation to three subdivisions of the twenty-first century. On the basis of these data, we were able to calculate the heating and cooling degree months and degree years. After examining both sets of data, we studied the total needs of air conditioning—also referred to in the current paper as climatization needs——for Andalusia as a whole. The results indicate an increase in air conditioning needs, and we also noted that the areas adversely affected by this increase were more numerous than those which benefited, at the end of the century. It should be noted that climate change will also necessitate the gradual replacement of heating with cooling, which will require profound changes in the energy, land planning, and housing policies of the region. The true magnitude of the challenge becomes clear when the climatization degree days are related to the population which they affect; the majority of the population is located in areas where the climatization needs will increase over the course of the century. Undoubtedly, this issue is a major protagonist in the climate change adaptation process in Andalusia.