One of the sources of data most utilized in Europe by planners, policy makers and researchers is CORINE Land Cover (CLC) because of its wide territorial coverage. However, the users of this spatial database do not have information on its quality for analysing urban land and its evolution. This study analyses the limitations of CLC for monitoring urban land use dynamics, using Madrid Land Use as a mapping reference. This is a local geographical database with higher resolution for the Madrid region that coincides with CLC at the years of reference (2000, 2006). The results show that with respect to the total urban land area in 2000 and 2006 and the area converted to urban land between 2000 and 2006, CLC is relatively reliable. However, the confusion matrices show very high error rates, especially in dynamic analyses (changes between 2000 and 2006) and when there is differentiation between different types of land use. Researchers, planners and decision-makers should therefore exercise considerable caution when using this source for analysing urban land use and its dynamics for local approaches.

The middle of 2007 saw the beginning of a worldwide financial crisis that led to a sharp reduction in investment based on construction and urban development. This new situation is generating a new process, characterised by a slowdown that has almost reached a standstill when compared with the frenzied development of previous decades. In order to analyse these processes, this study examines urban land use changes and the urban growth rate and spatial dynamics of the metropolitan region of Madrid. The analysis has been carried out on a large scale between two periods (2000–2006 and 2006–2009) using a regional land use geodatabase. The results show the changes in the urban land use dynamics that took place over these two periods that could characterise the cities of Mediterranean Europe, where contrarily to the general pattern in Europe built-up areas are combining scattered built-up areas with new aggregated compact developments.

Many small islands base their economy on tourism. This activity, based to a large extent on the movement of millions of people by air transport, depends on the use of fossil fuels and, therefore, generates a large amount of greenhouse gas (GHG) emissions. In this work, these emissions are evaluated by means of various carbon calculators, taking the Canary Islands as an example, which is one of the most highly developed tourist archipelagos in the world. The result is that more than 6.4 million tonnes (Mt) of CO₂ are produced per year exclusively due to the massive transport of tourists over an average distance of more than 3000 km. The relative weight of these emissions is of such magnitude that they are equivalent to more than 50% of the total amount produced by the socioeconomic activity of the archipelago. Although, individually, it is travelers from Russia and Nordic countries who generate the highest carbon footprint due to their greater traveling distance, the British and German tourists account for the greatest weight in the total, with two-thirds of emissions.

Coastal spaces exploited for tourism tend to be developed rapidly and with a desire to maximise profit, leading to diverse environmental problems, including flooding. As the origin of flood events is usually associated with intense precipitation episodes, this study considers the general rainfall characteristics of tourist resorts in two islands of the Canary Archipelago (Spain). Days of intense rainfall were determined using the 99th percentile (99p) of 8 daily precipitation data series. In addition, the weather types that generated these episodes were identified, the best-fitting distribution functions were determined to allow calculation of probable maximum daily precipitation for different return periods, and the territorial and economic consequences of flood events were analysed. The results show highly irregular rainfall, with 99p values ranging 50–80 mm. The weather types associated with 49 days of flooding events were predominantly cyclonic and hybrid cyclonic. The Log Pearson III distribution function best fitted the data series, with a strong likelihood in a 100-year return period of rainfall exceeding 100 mm in a 24 h period. However, values below 30 mm have already resulted in significant flood damage, while intense rainfall events in the period 1998–2016 saw over 11.5 million euros paid out in damages for insured goods. Such flood-induced damages were found to be caused more by inadequate urban planning than by rainfall intensity.