European cities: territorial analysis of characteristics and trends - An application of the LUISA Modelling Platform (EU Reference Scenario 2013 - Updated Configuration 2014)

Cities and towns are at the core of the European economy but they are often also the places where problems related to the quality of life of citizens such as unemployment, segregation and poverty are most evident. To curtail the negative impacts and foster the positive effects of ongoing urban processes in Europe, policies have to be adjusted and harmonised to accommodate future urbanization trends. Such an analysis of the evolution of European cities requires the evaluation of impacts of continent-wide drivers and, at the same time, assessment of the effect of national and local strategies. As a contribution to this analysis of the current and future evolution of European territories (countries, macro-regions, regions or urban areas), the Directorate-General Joint Research Centre (DG JRC) of the European Commission (EC) has developed the Land-Use-based Integrated Sustainability Assessment (LUISA) Modelling Platform. Based on the concept of ‘dynamic land functions’, LUISA has adopted a novel approach towards activity-based modelling and endogenous dynamic allocation of population, services and activities. This report illustrates how European cities could potentially evolve over the time period 2010-2050, according to the reference configuration of the LUISA modelling platform, on the basis of a collection of spatial indicators covering several thematic fields. These spatial indicators aim to improve our understanding of urbanization and urban development processes in Europe; explore territorial dimensions of projected demographic and economic changes, and finally examine some key challenges that urban areas are or may be exposed to. Some of the key findings of this report are given below: - The proportion of the population living in cities, towns and suburbs is higher in the EU than in the rest of the world. According to the LUISA forecasts, the urban proportion will continue to increase up to 2030; subsequently slow down, and reach a relatively steady state by 2050. - In 2010, 65% of the EU population were living in Functional Urban Areas (FUA, the city and its commuting zone). This figure is expected to reach 70% by 2050. The total EU-28 population is expected to grow by 4.6%. Most of this population growth will occur particularly in FUA which will grow by an average 14%. - As of 2010, the amount of artificial areas per inhabitant in the EU-28 was estimated as 498 m2: it becomes 539 m2 in 2050 with an 8% increase. Although there is not a unique spatial pattern, land take tends to start peak at 5 km distance from the city centre. This is due to the fact that land is often less available for development within city centres and that the majority of land take therefore will occur firstly in the suburbs and then in rural areas. - By 2050, potential accessibility – as measure of economic opportunities - will be higher in the urban areas of north-western Europe, while it will not improve in lagging European regions. Urban form has a considerable impact on average travelled distances and thus potentially on the energy dependence of transport. - Green infrastructure is mainly located at the periphery of urban areas. Its share per person is generally low or very low in most of the European cities, with few exceptions. Green infrastructure per capita in FUA shows a general trend towards a decrease across the EU-28 (by approximately 13%) between 2010 and 2050. - Larger cities tend to have higher average flood risk, especially due to the higher sensitivity in terms of potential human and physical losses. The analysis herein presented is part of a wider initiative of DG JRC and DG REGIO aiming to improve the management of knowledge and sharing of information related to territorial policies, such as those concerning urban development. In this framework, the work will be further developed, covering the following main elements: - Development of the European Urban Data Platform, providing a single access point for data and indicators on the status and trends of European urban areas; - Updates of the LUISA configuration, to account for new socio-economic projections; - Support to the development of the EU Urban Agenda and related initiatives; - Provision of evidence-based support for the evaluation of territorial policies in particular to proof the role of cities in the implementation of EU priorities.JRC.H.8-Sustainability Assessmen

LUISA Dynamic Land Functions: Catalogue of Indicators – Release I: EU Reference Scenario 2013 LUISA Platform - Updated Configuration 2014

The concept of ‘dynamic land function’ is a new notion for cross-sector integration and for the representation of complex system dynamics. A land function can be societal (e.g. provision of housing, leisure and recreation), economic (e.g. provision of production factors - employment, investments, energy – or provision of manufacturing products and services – food, fuels, consumer goods, etc.) or environmental (e.g. supply of ecosystem services). Land functions are temporally and spatially dynamic, and are constrained and driven by natural, socio-economic, and techno-economic processes. Based on the concept of ‘land function’ and beyond a traditional land use model, the Land-Use based Integrated Sustainability Assessment (LUISA) modelling platform adopts a new approach towards activity-based modelling based upon the endogenous dynamic allocation of population, services and activities. The ultimate product of LUISA is a set of territorial indicators that can be grouped and combined according to the ‘land function’ of interest and/or to the sector under assessment. The herein presented indicators measure the provision of land functions in the period 2010-2050, according to the EU Reference Scenario (LUISA, updated configuration 2014), consistent with settings (economic and demographic in particular) and policies in place in 2013 (hence including the 2020 renewable energy targets). The indicators are aggregated by Member States and Regions (Administrative Units NUTS-2) and can be employed as benchmark to monitor sectorial and territorial evolutions of alternative scenarios (e.g. to simulate policy options or specific measures), and for future updates of the reference scenario, to capture policy impacts (for example when changing energy targets) and their territorial effects. This catalogue aims to provide the description of the land functions and the list of related indicators and an indicator factsheet (metadata). 30 indicators, out of the more than 50 currently produced by LUISA, are included in the first release of the catalogue. The catalogue is periodically up-dated, following the updates of the configurations of the LUISA modelling platform and the definition, computation and validation of new indicators. Indicators and basic spatial layers used for the simulations will be made available in the frame of the framework for the management of knowledge and dissemination of information being set up by the Pilot Knowledge Centre on Territorial Policies.JRC.H.8-Sustainability Assessmen

European Territorial Trends - Facts and Prospects for Cities and Regions Ed. 2017

This report analyses a set of territorial trends at continental and sub-national scale, looking at patterns and determinants of regional growth, while considering pan-European and national characteristics. Past and prospective demographic and economic trends are analysed to provide a picture of ‘what, where, when and how’ things happen in European cities and regions. Specific emphasis is placed on urban areas since acknowledged sources of both opportunities and challenges. The indicators used in the analysis herein presented are freely and openly accessible in the Territorial Dashboard of the Knowledge Centre for Territorial Policies at: http://urban.jrc.ec.europa.eu/t-board/index.htmlJRC.B.3-Territorial Developmen

The Future of Cities

This report is an initiative of the Joint Research Centre (JRC), the science and knowledge service of the European Commission (EC), and supported by the Commission's Directorate-General for Regional and Urban Policy (DG REGIO). It highlights drivers shaping the urban future, identifying both the key challenges cities will have to address and the strengths they can capitalise on to proactively build their desired futures. The main aim of this report is to raise open questions and steer discussions on what the future of cities can, and should be, both within the science and policymaker communities. While addressing mainly European cities, examples from other world regions are also given since many challenges and solutions have a global relevance. The report is particularly novel in two ways. First, it was developed in an inclusive manner – close collaboration with the EC’s Community of Practice on Cities (CoP-CITIES) provided insights from the broader research community and city networks, including individual municipalities, as well as Commission services and international organisations. It was also extensively reviewed by an Editorial Board. Secondly, the report is supported by an online ‘living’ platform which will host future updates, including additional analyses, discussions, case studies, comments and interactive maps that go beyond the scope of the current version of the report. Steered by the JRC, the platform will offer a permanent virtual space to the research, practice and policymaking community for sharing and accumulating knowledge on the future of cities. This report is produced in the framework of the EC Knowledge Centre for Territorial Policies and is part of a wider series of flagship Science for Policy reports by the JRC, investigating future perspectives concerning Artificial Intelligence, the Future of Road Transport, Resilience, Cybersecurity and Fairness Interactive online platform : https://urban.jrc.ec.europa.eu/thefutureofcitiesJRC.B.3-Territorial Developmen

Development of European NO2 Land Use Regression Model for Present and Future Exposure Assessment: Implications for Policy Analysis

A new Land Use Regression model was built to develop pan-European 100 m resolution maps of NO2 concentrations. The model was built using NO2 concentrations from routine monitoring stations available in the Airbase database as dependent variable. Predictor variables included land use, road traffic proxies, population density, climatic and topographical variables, and distance to sea. In order to capture international and inter regional disparities not accounted for with the mentioned predictor variables, additional proxies of NO2 concentrations, like levels of activity intensity and NOx emissions for specific sectors, were also included. The model was built using Random Forest techniques. Model performance was relatively good given the EU-wide scale (R2 = 0.53). Output predictions of annual average concentrations of NO2 were in line with other existing models in terms of spatial distribution and values of concentration. The model was validated for year 2015, comparing model predictions derived from updated values of independent variables, with concentrations in monitoring stations for that year. The algorithm was then used to model future concentrations up to the year 2030, considering different emission scenarios as well as changes in land use, population distribution and economic factors assuming the most likely socio-economic trends. Levels of exposure were derived from maps of concentration. The model proved to be a useful tool for the ex-ante evaluation of specific air pollution mitigation measures, and more broadly, for impact assessment of EU policies on territorial development.JRC.B.3-Territorial Developmen

Mapping ecosystem service capacity, flow and demand for landscape and urban planning: a case study in the Barcelona metropolitan region

Ecosystem services (ES) mapping is attracting growing interest from landscape and urban planning, but its operationalization in actual decision-making is still limited. A clear distinction between ES capacity, flow and demand can improve the usefulness of ES mapping as a decision-support tool by informing planners and policy-makers where ES are used unsustainably and where ES flow is failing to meet societal demand. This paper advances a framework for mapping and assessing the relationships between ES capacity, flow and demand with a focus on the identification of unsatisfied demand. The framework was tested in the Barcelona metropolitan region, Spain, considering two ES of critical relevance for the urban population: air purification and outdoor recreation. For both ES, spatial indicators of capacity, flow, demand and unsatisfied demand were developed using proxy- and process-based models. The results show a consistent spatial pattern of all these components along the urban-rural gradient for the two ES assessed. The flow of both ES mainly takes place in the periurban green areas whereas the highest capacity values are mostly found in the protected areas located on the outskirts of the metropolitan region. As expected, ES demand and particularly unsatisfied demand are mostly situated in the main urban core (i.e., Barcelona and adjacent cities). Our assessment also reveals that the current landscape planning instrument for the metropolitan region mostly protects areas with high capacity to provide ES, but might lead to declining ES flows in periurban areas due to future urban developments. We contend that the mapping of ES capacity, flow and demand can contribute to the successful integration of the ES approach in landscape and urban planning because it provides a comprehensive picture of the ES delivery process, considering both ecological and social underlying factors. However, we identify three main issues that should be better addressed in future research: (1) improvement of ES demand indicators using participatory methods; (2) integration of ecological thresholds into the analysis; and (3) use of a multi-scale approach that covers both the local and regional planning levels and cross-scale interactions between them.JRC.D.3-Land Resource

Adaptación transcultural al español del cuestionario Patient empowerment in long-term conditions

Resumen: Objetivo: Describir el proceso de traducción y adaptación transcultural del instrumento Patient empowerment in long-term condition al español. Diseño: Traducción, adaptación transcultural y análisis de la comprensibilidad mediante entrevistas cognitivas. Emplazamiento: Asistencia primaria y hospitalaria. Participantes: Diez pacientes ingresados en un servicio de cardiología de un hospital universitario. Mediciones principales: 1) Traducción directa; 2) síntesis y conciliación de las versiones por un comité de expertos; 3) traducción inversa; 4) conciliación de la traducción inversa con la autora del cuestionario original, y 5) análisis de la comprensibilidad mediante entrevistas cognitivas a una muestra de pacientes. Resultados: Las versiones de traducción directa no presentaron grandes diferencias entre ellas. De los 47 ítems que componen el cuestionario, el comité de expertos introdujo cambios en 23 ítems. La versión de la traducción inversa fue aceptada por la autora del cuestionario original. En las entrevistas cognitivas, los pacientes señalaron una dificultad alta en un ítem y baja en 4. Conclusiones: La versión española del cuestionario Patient Empowerment in long-term conditions es equivalente semántica y conceptualmente al instrumento original. En una fase posterior se procederá a un proceso de validación en el que se establecerán las propiedades psicométricas. Abstract: Purpose: To describe the process of translation and cultural adaptation of the Patient empowerment in long-term condition to the Spanish language. Design: Translation, cross-cultural adaptation, and pilot testing (cognitive debriefing) Location: Primary and Hospital care. Participants: Ten patients admitted to a cardiology department of a University Hospital Main measurements: 1) Direct translation, 2) conciliation and synthesis of the versions by expert panel, 3) back- translation, 4) agreement on the back-translated version with the author of the original version, 5) analysis of comprehensibility through cognitive interviews. Results: There were no differences between the direct-translated versions. The expert panel introduced changes in 23 out of the 47 items of the questionnaire. The author of the original version agreed with the version of the back-translation. In the cognitive interviews, patients reported high difficulty in one item and low difficulty in 4. Conclusions: The Spanish version of the Patient Empowerment in long-term conditions questionnaire is semantically and conceptually equivalent to the original tool. The assessment of the psychometric properties of the Spanish version of the questionnaire will be carried out at a later stage. Palabras clave: Comparación transcultural, Encuestas y cuestionarios, Participación del paciente, Autoeficacia, Keywords: Cross-cultural comparison, Surveys and questionnaires, Patient participation, Self efficac

Adaptación transcultural al español del cuestionario Patient empowerment in long-term conditions

Altres ajuts: También recibió un Premio Esteve a la Innovación en Salud en 2015.Describir el proceso de traducción y adaptación transcultural del instrumento Patient empowerment in long-term condition al español. Traducción, adaptación transcultural y análisis de la comprensibilidad mediante entrevistas cognitivas. Asistencia primaria y hospitalaria. Diez pacientes ingresados en un servicio de cardiología de un hospital universitario. 1) Traducción directa; 2) síntesis y conciliación de las versiones por un comité de expertos; 3) traducción inversa; 4) conciliación de la traducción inversa con la autora del cuestionario original, y 5) análisis de la comprensibilidad mediante entrevistas cognitivas a una muestra de pacientes. Las versiones de traducción directa no presentaron grandes diferencias entre ellas. De los 47 ítems que componen el cuestionario, el comité de expertos introdujo cambios en 23 ítems. La versión de la traducción inversa fue aceptada por la autora del cuestionario original. En las entrevistas cognitivas, los pacientes señalaron una dificultad alta en un ítem y baja en 4. La versión española del cuestionario Patient Empowerment in long-term conditions es equivalente semántica y conceptualmente al instrumento original. En una fase posterior se procederá a un proceso de validación en el que se establecerán las propiedades psicométricas

Increasing the detail of European land use/cover data by combining heterogeneous data sets

Data on land use and land cover (LULC) are a vital input for policy-relevant research, such as modelling of the human population, socioeconomic activities, transportation, environment, and their interactions. In Europe, CORINE Land Cover has been the only data set covering the entire continent consistently, but with rather limited spatial detail. Other data sets have provided much better detail, but either have covered only a fraction of Europe (e.g. Urban Atlas) or have been thematically restricted (e.g. Copernicus High Resolution Layers). In this study, we processed and combined diverse LULC data to create a harmonised, ready-to-use map covering 41 countries. By doing so, we increased the spatial detail (from 25 to one hectare) and the thematic detail (by seven additional LULC classes) compared to the CORINE Land Cover. Importantly, we decomposed the class ‘Industrial and commercial units’ into ‘Production facilities’, ‘Commercial/service facilities’ and ‘Public facilities’ using machine learning to exploit a large database of points of interest. The overall accuracy of this thematic breakdown was 74%, despite the confusion between the production and commercial land uses, often attributable to noisy training data or mixed land uses. Lessons learnt from this exercise are discussed, and further research direction is proposed. JRC.B.3-Territorial Developmen

Adaptación transcultural al español del cuestionario Patient empowerment in long-term conditions

Altres ajuts: También recibió un Premio Esteve a la Innovación en Salud en 2015.Describir el proceso de traducción y adaptación transcultural del instrumento Patient empowerment in long-term condition al español. Traducción, adaptación transcultural y análisis de la comprensibilidad mediante entrevistas cognitivas. Asistencia primaria y hospitalaria. Diez pacientes ingresados en un servicio de cardiología de un hospital universitario. 1) Traducción directa; 2) síntesis y conciliación de las versiones por un comité de expertos; 3) traducción inversa; 4) conciliación de la traducción inversa con la autora del cuestionario original, y 5) análisis de la comprensibilidad mediante entrevistas cognitivas a una muestra de pacientes. Las versiones de traducción directa no presentaron grandes diferencias entre ellas. De los 47 ítems que componen el cuestionario, el comité de expertos introdujo cambios en 23 ítems. La versión de la traducción inversa fue aceptada por la autora del cuestionario original. En las entrevistas cognitivas, los pacientes señalaron una dificultad alta en un ítem y baja en 4. La versión española del cuestionario Patient Empowerment in long-term conditions es equivalente semántica y conceptualmente al instrumento original. En una fase posterior se procederá a un proceso de validación en el que se establecerán las propiedades psicométricas