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Green infrastructure (GI), a network of nature, semi-natural areas and green space, delivers essential ecosystem services which underpin human well-being and quality of life. Maintaining ecosystem services through the development of GI is therefore increasingly recognized by policies as a strategy to cope with potentially changing conditions in the future. This paper assessed how current trends of land-use change have an impact on the aggregated provision of eight ecosystem services at the regional scale of the European Union, measured by the Total Ecosystem Services Index (TESI8). Moreover, the paper reports how further implementation of GI across Europe can help maintain ecosystem services at baseline levels. Current demographic, economic and agricultural trends, which affect land use, were derived from the so called Reference Scenario. This scenario is established by the European Commission to assess the impact of energy and climate policy up to 2050. Under the Reference Scenario, economic growth, coupled with the total population, stimulates increasing urban and industrial expansion. TESI8 is expected to decrease across Europe between 0 and 5 % by 2020 and between 10 and 15 % by 2050 relative to the base year 2010. Based on regression analysis, we estimated that every additional percent increase of the proportion of artificial land needs to be compensated with an increase of 2.2 % of land that qualifies as green infrastructure in order to maintain ecosystem services at 2010 levels.

While the driving factors of urban growth and urban sprawl have repeatedly been studied, the implications for residential densities presumably differ in growing and shrinking regions. Thus far, those differences have received little attention. This paper examined the dynamics of urban growth and shrinkage across EU regions, using residential densities as an explanatory factor to analyse the underlying dynamics. To do so, detailed spatial data on various potentially relevant factors were used in regression methods to establish the relevance of those factors for residential expansion and densification in growing and shrinking EU regions between the years 2000 and 2010. We found that expansion and densification processes are affected by population size, prior residential density, land supply, accessibility, agricultural land rent, physical factors, public regulation, and regional characteristics. The results of this study can confirm that residential expansion is driven differently in declining regions than in regions with population growth. Models explaining residential density changes also yield different results in declining regions.

One argument for containing urban densities is that cities need a critical population density to sustain sufficiently available public transportation. However, the question of whether denser cities foster shorter public transport networks empirically is problematic because real-world transport nets are a product of many additional factors presumably not related to urban form. This paper adopts a network expansion simulation approach to generate and analyze counterfactual data on network lengths for 36 world cities, in which all networks are generated with similar expansion restrictions and objectives. Denser cities are found to have shorter simulated public transport networks, regardless of the tested model parameters. This provides additional proof that densities are needed to facilitate the provision of proximate public transport infrastructure, with potentially self-reinforcing effects.

Purpose In the last decade or so several studies have looked into the impacts of transport infrastructure improvements on decreasing territorial disparities. In those studies population levels are usually assumed static, although future population levels likely change in response to changing accessibility levels as well as to other factors. To test how much accessibility impacts may be affected by changes in population levels, this study explores the effects of foreseeable population changes on the accessibility improvements offered by large scale transport infrastructure investments. Methods In this study we compare accessibility measures from four cases, namely the current situation; one case in which only transport investments are taken into account; and two cases that include transport investments and two scenarios with differing future population distributions that in turn are simulated by the LUISA land-use model. The modelled transport investments are assumed to improve travel times. The study concentrates on accessibility effects in Austria, Czech Republic, Germany and Poland. To provide a reference to the found results, the same computations are repeated with historical population and road network changes. Results The results indicate that differences in local population levels have a limited effect on average accessibility levels, but may have a large impact on territorial inequalities related to accessibility. Conclusions The findings in this study underpin the importance of incorporating future local population levels when assessing the impacts of infrastructure investments on territorial disparities.

Spatial models jointly simulating population and land-use change provide support for policy-making, by allowing to explore territorial developments under alternative scenarios and resulting impacts in the environment, economy and society. However, their ability to reproduce observed spatial patterns is rarely evaluated through model validation. This lack of insight prevents researchers and policy-makers of fully grasping the ability of existing models to provide sensible projections of future land use and population density. In this article, we address this gap by performing a model validation of the LUISA Territorial Modelling Platform, a spatial model jointly simulating population and land use at a fine resolution (100 m) in the European Union and United Kingdom. In particular, we compare observed and simulated patterns of population and urban residential land-use change for the period of 1990–2015, and evaluate the model performance according to different degrees of urbanisation. The results show that model performance can vary depending on the context, even when the same data and methods are uniformly applied. The model performed consistently well in urban areas characterized by compact urban growth, but poorly where residential development occurred predominantly in scattered patterns across rural areas. Overall, the model tends to favour the formation of densely populated, highly accessible urban conglomerations, which often do not entirely correspond to the observed patterns. Based on the validation results, we propose directions for further model improvement and development. Model validation should be regarded as a critical step, and an integral part, in the process of developing models for policy support.

This study proposes a sequence of methods to obtain geolocated estimates of primary school provision, costs, and access. This sequence entails: (1) location-allocation, an approach that mimics school location patterns in case of decentralised governance, such as exists in the EU and UK; (2) balanced floating catchment areas, an approach to assign pupils to schools assuming free school choice; and (3) school costs estimates, which are induced from pupil counts and the distributional properties of observed school costs. The method is fine-tuned using observed school locations and school-level costs data. It is developed to assess how much local population densities and demography affects school access and schooling costs across Europe. Its results can be aggregated by degree of urbanisation to quantify the differences across human settlements ranging from mostly uninhabited areas to densely populated cities.

This report shows the results of fine-grained data analyses of residential property transactions and private rental supply in the municipality of Amsterdam. The analyses follow from a collaboration between the Joint Research Centre’s (JRCs) LUISA team, and the City of Amsterdam. The study provides insight in the spatial dynamics of Amsterdam’s housing market, uncovering the driving factors behind the city’s spiraling-up house prices, providing empirical support to a further development of an inclusive and accessible housing market for all. The analyses indicate that closer proximity to the city centre, older buildings, and companies as buyers, are the main determinants behind higher prices. Another main finding is that looking at asking prices, Amsterdam's middle income households would need to spend a higher share of their incomes on long-term rents, in comparison to middle class income households at country level. Furthermore, for Amsterdam's middle incomes, asking prices reflect private rents that would be well above the EU housing cost overburden rate. This suggests that middle income households looking for alternative rental housing are less likely to find affordable housing in the city, and more likely to move out. Depending on data availability, similar analyses can be made for other cities and urban areas, enabling comparison and providing additional case studies, shedding more light on housing market dynamics and affordability across the EU.

Changes in land use patterns do not occur homogeneously throughout Europe. Many environmental, economic and social phenomena take place at local scale. In this study a land use indicator is being proposed to illustrate the likely land evolution in the EU within 2015-2030 based on the projections in the JRC-LUISA Territorial Modelling Platform and its Reference Scenario 2017. The indicator is further disaggregated for built-up and forest & natural vegetated areas.

In the period 2015-2030 about 11% (more than 20 million ha) of agricultural land in the EU are under high potential risk of abandonment due to factors, related to biophysical land suitability, farm structure and agricultural viability, population and regional specifics. The risk for around 800 thousand ha (0.4%), located in Southern and Eastern Romania, Southwestern France, Southern and central Spain, Portugal, Cyprus, Poland, Latvia and Estonia, is particularly severe. Economic factor and market instruments (including the EU Common Agricultural Policy) could largely mitigate those potential risks in a number, mostly Eastern countries and regions – Estonia, Latvia, Romania, Cyprus. The incremental abandonment within 2015-2030 is nevertheless projected to reach 4.2 million ha net (about 280 thousand ha per year on average) of agricultural land, bringing the total abandoned land to 5.6 million ha by 2030, the equivalent of 3% of total agricultural land.

In 2015 agricultural land is estimated to cover 42% of all EU land area. The arable land accounts for the largest share – 56%, followed by livestock grazing (25%), mixed crops (13.5%) and various permanent crops (5.5%). Within 2015-2030 the EU agricultural land is projected to shrink by 1.1%, chiefly driven by the decline in the two principal groups – arable land and livestock grazing – by 4.0% and 2.6% respectively. Mixed crops are expected to expand by 11%. In the group of permanent crops, olive trees are likely to grow at the expense of vineyards.