On 2002, a novel initiative was undertaken by the local water administration of Catalonia (the Agència Catalana de l'Aigua) and the Universitat Autònoma de Barcelona, leading to a ten-year project where a high number of medium resolution satellite images (MODIS and Landsat) were integrated to the daily water management to improve decision making effectiveness. This paper describes the methodology followed in the successful application of remote sensing, as well as the main problems that had to be overcome during its execution. It also presents the products that have been calculated. These are integrated into the Agency's corporate GIS and immediately available via the intranet for the staff, and a selection is available on the Internet.

The regulatory framework established by the new European Directive on Building Energy Efficiency requires the implementation of measures to reduce energy consumption and increase the use of renewable sources. Therefore, efficiency improvement implies a reduction of energy demand in buildings, combined with improved performance of passive systems that provide smarter energy saving solutions. These actions have the potential to improve the benchmark of the entire performance, particularly when prioritizing renewable energy sources. At the regional scale, it is necessary to consider environmental conditions during the initial building design to develop smarter buildings with smaller carbon emissions. To address this issue, some Sustainable Building Strategies are proposed on regional scale, methodologically applied to Valencian Community (Spain). This methodology is the outcome of considering local and regional environmental conditions with comfort climograms, allowing designers to recommend passive strategies for correcting thermal discomfort inside buildings. The recommendation process depends on the detailed analysis of the local conditions of each site, i.e. sunlight exposure, radiation values, wind patterns, existence of obstacles, etc. In summary, the here described methodology allows designers to select the best strategies according to the climatic and geographical conditions of each location, thus, helping them to plan smarter buildings.