Space-time patterns of urban sprawl, a 1D cellular automata and microeconomic approach

We present a theoretical model of residential growth that emphasizes the path-dependent nature of urban sprawl patterns. The model is founded on the monocentric urban economic model and uses a cellular automata (CA) approach to introduce endogenous neighbourhood effects. Households are assumed to both like and dislike the density of their neighbourhood, and trade-off this density with housing space consumption and commuting costs. Discontinuous spatial patterns emerge from that trade-off, with the size of suburban clusters varying with time and distance to the centre. We use space-time diagrams inspired from 1D elementary CA to visualize changes in spatial patterns through time and space, and undertake sensitivity analyses to show how the pattern and timing of sprawl are affected by neighbourhood preferences, income level, commuting costs or by imposing a green belt.urban sprawl, open space, neighbourhood externalities, cellular automata, residential dynamics.

Urban Interventions to Reduce Pollution Exposure and Improve Spatial Equity

peer reviewedAir pollution is of increasing concern to urban residents and urban planners are struggling to find interventions which tackle the trade-off between environmental, health, and economic impacts arising from this. We analyze within a spatially explicit theoretical residential choice model how different urban interventions can reduce exposure to endogenous traffic-induced air pollution at residential locations. We model a city of fixed population size, where households are averse to localized pollution and examine how a flat commuting tax, an urban growth boundary, a cordon toll, and the optimal distance-based tax compare to an urban scenario without any planner's intervention. We find that an urban intervention to optimally address exposure concerns needs to achieve steep density gradients near the urban fringe and flat gradients near the center. We show the deficiencies of the alternative interventions to achieve optimal population distributions within the city and in a scenario where peoples' aversion to pollution increases. We then discuss these interventions in light of resulting spatial patterns of exposure and spatial equity that is households' assessment of their own exposure to air pollution relative to their responsibility for the exposure of others depending on their spatial location within the city. Our results show that, when equity is also a concern, compensations are needed from households who live in the periphery and our simulations suggest that a cordon toll can then achieve a more balanced outcome

Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model

This paper studies the relationship between activity pattern complexity and car use using two multi-day surveys involving the same participants but collected just before and about one year after they relocated their workplace. Measurable characteristics related to two latent variables, namely activity pattern complexity, or trip chaining (e.g., number of activities done within and outside the home–work tour), and to car use (e.g., usage rate, distance travelled by car) were selected. The study shows that the methodology adopted, partial least square structural equation modelling, quantifies the relation between the two variables, and is robust towards changes in important contextual characteristics of the individuals, namely workplace location. The findings indicate that the number of activities chained to commuting travels strongly impact mode choice and, in particular, car use. The paper also shows that chaining non-work-related activities has a stronger impact on car use. The results of this study suggest that planning and management solutions aimed at reducing car use, but focusing only on the commuting trip while neglecting the impact of other daily activities, may be less effective than expected

On the heterogeneity of urban expansion profiles in Europe

The difference of a city's artificial land use (ALU) radial profile to the average ALU profile is examined for 585 European cities. Using Urban Atlas 2012 data, a radial (or monocentric) approach is used to calculate a city's land use profile in relation to distance to the city centre. A scaling law is used which controls for city size and population. As a consequence, cities of varying degrees of size can be contrasted in a comparable way. Utilising the mean ALU profile for the entire sample of 585 cities, the difference to the mean profile is calculated for each city. Using these differences allows us to examine heterogeneity of the ALU across European cities but also examine these differences within cities. We utilise city groupings by city size and country to attempt to understand these differences. Combining Urban Atlas and Corine Land Cover data, the impact of water on the ALU profiles is examined. A city classification is also introduced which considers the difference to the average curve. Ordering methods are used to visualise cities within these classifications. Results highlight the level of heterogeneity between cities. Removing water, we can see that the cities with the highest levels of water have a higher level of ALU on average. Spain and France are found to have contrasting levels of ALU, Spanish cities having below average ALU and France above average. Using seriation techniques enables us to group and order cities into a typology which can be used to benchmark cities

Gibrat’s law and the change in artificial land use within and between European cities

editorial reviewedSeen from a satellite, observing land use in the daytime or at night, most cities have circular shapes, organised around a city centre. A radial analysis of artificial land use growth is conducted in order to understand what the recent changes in urbanisation are across Europe and how it relates to city size. We focus on the most fundamental differentiation regarding urban land use: has it been artificialised for human uses (residence or roads for instance) or is it natural, or at least undeveloped? Using spatially detailed data from the EU Copernicus Urban Atlas, profiles of artificial land use (ALU) are calculated and compared between two years, 2006 and 2012. Based on the homothety of urban forms found by Lemoy and Caruso (2018), a simple scaling law is used to compare the internal structure of cities after controlling for population size. We firstly show that when using the functional urban area (FUA) definition of cities, a kind of Gibrat’s law for land use appears to hold. However, when we examine cities internally, this is no longer clear as there are differences on average between city size categories. We also look at further city groupings using regions and topography to show that artificial land use growth across European cities is not homogeneous. Our findings have important implications relative to the sustainability of cities as this evidence is pointing towards increasing urban sprawl and stagnant growth in urban centres across cities of all sizes. It also has theoretical implications on the nature of sprawl and its scaling with city size

Road network distances and detours in Europe: Radial profiles and city size effects

peer reviewedThe form and the size of cities influence their social, economic and environmental outcomes. The form of a city is itself influenced by the shape of its road network, but this relationship and how it is affected by city size are unclear. We analyse how road distances to the main centre vary across 300 European cities and how radial physical detours (i.e. the distance on the road network compared to the Euclidean distance) are affected by city size and extent. We use landuse and population data to sample potential residences and compute the fastest routes to the main centre. We find a linear relationship between road and Euclidean distances, and for the first time document an average radial physical detour of 1.343 across Europe. We then rescale distance bands so to make cities of different population size comparable and show the effect of different urban delineations. We find that physical detour ratios increase when core cities only are considered without suburbs. At the urban region scale, radial physical detours increase with city size, especially when other significant geographical factors (latitude, longitude, elevation change and proximity to coast) are controlled for. When the central part of cities only is considered, larger cities have smaller radial physical detours

Bee Species Richness in Europe

This map portfolio compares maps of bee species richness in Europe automatically aggregated per country from the IUCN Red List with national numbers obtained from various other sources

The provision of urban green space and its accessibility: Spatial data effects in Brussels

Urban green space (UGS) has many environmental and social benefits. UGS provision and access are increasingly considered in urban policies and must rely on data and indicators that can capture variations in the distribution of UGS within cities. There is no consensus about how UGS, and their provision and access, must be defined from different land use data types. Here we identify four spatial dimensions of UGS and critically examine how different data sources affect these dimensions and our understanding of their variation within a city region (Brussels). We compare UGS indicators measured from an imagery source (NDVI from Landsat), an official cadastre-based map, and the voluntary geographical information provided by OpenStreetMap (OSM). We compare aggregate values of provision and access to UGS as well as their spatial distribution along a centrality gradient and at neighbourhood scale. We find that there are strong differences in the value of indicators when using the different datasets, especially due to their ability to capture private and public green space. However we find that the interpretation of intra-urban spatial variations is not affected by changes in data source. Centrality in particular is a strong determinant of the relative values of UGS availability, fragmentation and accessibility, irrespective of datasets