Rethinking urban planning and health

The research starts from the observation that the disciplines of urban planning and public health are disconnected, partly due to an ongoing institutionalization of health criteria in formal laws and regulations. As such urban planning has difficulties to deal with the growing awareness of environmental impacts and the empowerment and engagement of citizens in health related issues. The research aims to move beyond this lock-in and explores a more context-dependent and adaptive urban planning perspective regarding environmental health. It builds on a matrix of planning management approaches, reflecting recent ideas of co-evolutionary and adaptive planning in a complex network society. To verify whether these academic and theoretical insights are useful in analyzing and solving urban environmental health conflicts, the matrix will be tested in several case studies in the city of Ghent. These are selected by means of an environmental justice approach, using a GIS analysis to compare the distribution of environmental impacts (air pollution and noise) with vulnerability (socio-economic characteristics) and responsibility (e.g. car ownership) indicators, allowing the detection of spatial inequalities. In the cases more detailed information about the context will be assembled, including bottom-up, subjective aspects, and the processes behind the inequalities. Consequently the justice of the situation can be assessed, and if deemed necessary, a redevelopment track can be devised making use of a combination of the four planning management approaches. Based on the case study results the research will formulate some recommendations how the use of the matrix could practically support a change in paradigm

The recurrence of health in urban planning: towards an integration of environmental health aspects

While urban planning and health were initially interlinked, in the twentieth century planning practice slowly moved away from its public health origins. In recent years however there is a growing interest in the health effects of our spatial organization. Although the direct impact of the physical environment on health has decreased – due to better standards of living, sanitary developments, improved housing – environmental quality still deserves our attention. First, the focus has shifted from life expectancy to health expectancy and quality of life. Public health impact no longer predominantly involves clear mortality risks, but rather comprises aspects of human well-being in a broad sense. Several direct impacts, like noise or air pollution, do not immediately kill people, but cause physical or mental disorders on the long term or severely reduce the quality of life of people. Second, the physical environment has many indirect effects on lifestyle and health, for example a reduced physical activity caused by a lack of walkable neighborhoods. A final important reason to justify this research is the aspect of environmental justice. The spatial characteristics responsible for direct and indirect health effects are spatially heterogeneously distributed, causing important differences in health status and healthy life expectancy between various residential neighborhoods. Today a lot of research exists on different health impacts caused by aspects of the physical environment. Most of this research focuses on one single impact (e.g. noise) or one spatial aspect (e.g. a road). An integrated approach, in which all the impacts and aspects are combined, seems to be lacking. However, there is a giant need for a better understanding of this issue, to inform community leaders and spatial planners about which community design and land-use choices are most effective in improving the physical, mental and social well-being of people. In this paper an attempt is made to give an overview of the main environmental characteristics with an effect on people’s health and well-being. The aim is to evaluate the evidence of the existing research output and to explore the relevance for spatial planning. Finally the results are discussed and recommendations for urban planning policy are formulated. Here the aspect of environmental justice comes into view, the right on a healthy living environment for every citizen regardless of social and economic status

Auxiliary Guided Autoregressive Variational Autoencoders

Generative modeling of high-dimensional data is a key problem in machine learning. Successful approaches include latent variable models and autoregressive models. The complementary strengths of these approaches, to model global and local image statistics respectively, suggest hybrid models that encode global image structure into latent variables while autoregressively modeling low level detail. Previous approaches to such hybrid models restrict the capacity of the autoregressive decoder to prevent degenerate models that ignore the latent variables and only rely on autoregressive modeling. Our contribution is a training procedure relying on an auxiliary loss function that controls which information is captured by the latent variables and what is left to the autoregressive decoder. Our approach can leverage arbitrarily powerful autoregressive decoders, achieves state-of-the art quantitative performance among models with latent variables, and generates qualitatively convincing samples.Comment: Published as a conference paper at ECML-PKDD 201

Measuring fragmentation of open space in urbanised Flanders: an evaluation of four methods

The open space in Flanders, the northern part of Belgium, can hardly be seen as really open. From the Middle Ages onward this area has been known for its spread out development pattern, which has even strengthened in recent decades. Especially the residential ribbon development and the omnipresent infrastructure are widely recognised. These developments have led to an intense fragmentation of open space. In this paper we present two new methods to analyse and quantify this fragmentation of open space from a spatial planning perspective, and compare them with two existing methods. This comparative analysis evaluates the differentmethods and connects them to different definitions of fragmentation. The average patch size method is more appropriate to describe general fragmentation if the focus is on major line infrastructures, whereas the density of fragmenting structures method matches with the interpretation of fragmentation as spatial heterogeneity. The two described methods to detect enclosed open space fragments as signs of fragmentation give different results depending on the data and methods used. The ribbon method however is more appropriate to detect open space fragments under threat of privatisation, since it works with a stricter definition of continuous ribbon development. All four methods are relevant for Flemish spatial planning policy, as they indicate where actions are needed to safeguard open space from further urbanisation tendencies. Furthermore, they can support a differentiated spatial policy and add to the scientific basis of the debate on alternative interpretations of Flemish open space

The countryside in urbanized Flanders: towards a flexible definition for a dynamic policy

The countryside, the rural area, the open space, … many definitions are used for rural Flanders. Everyone makes its own interpretation of the countryside, considering it as a place for living, working or recreating. The countryside is more than just a geographical area: it is an aggregate of physical, social, economic and cultural functions, strongly interrelated with each other. According to international and European definitions of rural areas there would be almost no rural area in Flanders. These international definitions are all developed to be used for analysis and policy within their specific context. They are not really applicable to Flanders because of the historical specificity of its spatial structure. Flanders is characterized by a giant urbanization pressure on its countryside while internationally rural depopulation is a point of interest. To date, for every single rural policy initiative – like the implementation of the European Rural Development Policy – Flanders used a specifically adapted definition, based on existing data or previously made delineations. To overcome this oversupply of definitions and delineations, the Flemish government funded a research project to obtain a clear and flexible definition of the Flemish countryside and a dynamic method to support Flemish rural policy aims. First, an analysis of the currently used definitions of the countryside in Flanders was made. It is clear that, depending on the perspective or the policy context, another definition of the countryside comes into view. The comparative study showed that, according to the used criteria, the area percentage of Flanders that is rural, varies between 9 and 93 per cent. Second, dynamic sets of criteria were developed, facilitating a flexible definition of the countryside, according to the policy aims concerned. This research part was focused on 6 policy themes, like ‘construction, maintenance and management of local (transport) infrastructures’ and ‘provision of (minimum) services (education, culture, health care, …)’. For each theme a dynamic set of criteria or indicators was constructed. These indicators make it possible to show where a policy theme manifests itself and/or where policy interventions are possible or needed. In this way every set of criteria makes up a new definition of rural Flanders. This method is dynamic; new data or insights can easily be incorporated and new criteria sets can be developed if other policy aims come into view. The developed method can contribute to a more region-oriented and theme-specific rural policy and funding mechanism

Unequal residential exposure to air pollution and noise : a geospatial environmental justice analysis for Ghent, Belgium

Following the growing empirical evidence on the health effects of air pollution and noise, the fair distribution of these impacts receives increasing attention. The existing environmental inequality studies often focus on a single environmental impact, apply a limited range of covariates or do not correct for spatial autocorrelation. This article presents a geospatial data analysis on Ghent (Belgium), combining residential exposure to air pollution and noise with socioeconomic variables and housing variables. The global results show that neighborhoods with lower household incomes, more unemployment, more people of foreign origin, more rental houses, and higher residential mobility, are more exposed to air pollution, but not to noise. Multiple regression models to explain exposure to air pollution show that residential mobility and percentage of rental houses are the strongest predictors, stressing the role of the housing market in explaining which people are most at risk. Applying spatial regression models leads to better models but reduces the importance of all covariates, leaving income and residential mobility as the only significant predictors for air pollution exposure. While traditional multiple regression models were not significant for explaining noise exposure, spatial regression models were, and also indicate the significant contribution of income to the model. This means income is a robust predictor for both air pollution and noise exposure across the whole urban territory. The results provide a good starting point for discussions about environmental justice and the need for policy action. The study also underlines the importance of taking spatial autocorrelation into account when analyzing environmental inequality

Living cities : reconnecting environmental health and urban planning

While public health and urban planning were closely linked in the past, the relation has turned into a lock-in of two procedurally interrelated, but in fact disconnected domains of knowledge and action. In most cases, health intersects with spatial planning processes only through obligatory evaluations or restrictive environmental legislation. This institutionalization of health criteria in most western countries has difficulty in dealing with the rapidly changing spatial conditions of our complex society, the growing awareness of environmental impacts and the increasing empowerment and engagement of citizens. This dissertation aims to move beyond this lock-in and explores new approaches to deal with environmental health concerns in planning practice. Building on complexity theory, an environmental justice framework is proposed to localize environmentally unhealthy situations, and a matrix of planning strategies is presented to address these situations. To verify whether these theoretical insights could help to solve urban environmental health conflicts, an empirical research methodology was developed consisting of interviews, spatial data analysis, documentary analysis and a residents' survey. This research framework was applied to the city of Ghent (Belgium) in close collaboration with the city administrations and a local citizen initiative. By combining quantitative with qualitative results, case-specific and general policy recommendations were formulated that can lead to a more central place for health in urban planning