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Commuting, the spatial mismatch between work and residential locations, necessitates integrated urban and transport policies to mitigate its societal impacts. While cross-border commuting (CBC) is increasing and governance of border regions is on the rise beyond national borders, no systemic review of this specific commuting pattern exists. We aim to consolidate the CBC literature accumulated over the years into a coherent and synthetic framework. Our systematic review assembles an inaugural comprehensive corpus of cross-border commuting literature. It reveals three transversal key topics (transport-oriented topic, qualitative approaches versus a lack of quantitative data, and a large majority of European papers) and four sub-topics (patterns, determinants, impacts and policies). Moreover, we consolidate findings through meticulous mapping of evidence, where most links are traced between the determinants and the level of flows across borders. Finally, the discussion offers directions for future research, with an exhortation to explicitly link policies to sustainability and social concerns, and the necessity for standardised datasets for methodological comparability across cases and in alignment with general commuting research. [ABSTRACT FROM AUTHOR]

Aim: Wild bees still face striking shortfalls in knowledge of biodiversity in key regions of the world. This includes Europe, where despite a long tradition of data gathering, the continental scale distribution patterns of wild bees have not been systematically analysed to date. This study aims to characterise large‐scale biodiversity patterns to: (i) understand spatial–temporal heterogeneity in large‐scale databases, (ii) locate genuine diversity hotspots and their relationship with biogeographical patterns or habitats of interests and (iii) identify understudied species and areas to further design conservation actions for most at risk species in key regions. Location: Europe. Taxon: Bees. Methods: We present a continental and standardised study of bee taxonomic and phylogenetic diversity patterns in Europe, using a large compilation of occurrence records of nearly three million validated occurrence records for 1515 wild bee species. Results: Southern and eastern Europe suffer from the largest gaps in data availability while northern and western regions benefit from better historical coverage. Our models show that higher wild bee diversity in Europe is hosted in xeric, warm areas, as highlighted by a clear latitudinal gradient. However, phylogenetic diversity is predicted to be more homogenous across Europe than taxonomic diversity, suggesting that policies and strategies targeted to protect species richness may differ from those targeting greater phylogenetic diversity. Main conclusions: This study represents a significant advance in the characterisation of wild bee distribution patterns across Europe and is an important stepping stone towards the design of more targeted survey efforts and conservation actions of this key group of pollinators. This, in turn, will provide the data necessary to improve the spatiotemporal coverage in a context of ongoing and future Europe‐wide monitoring schemes, to ultimately develop cost‐effective, coordinated and evidence‐based conservation actions and tailored habitat management actions that can be implemented on a smaller scale. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.regsciurbeco.2007.01.005 Byline: Geoffrey Caruso (a)(b), Dominique Peeters (a)(c), Jean Cavailhes (d), Mark Rounsevell (a) Keywords: Urban sprawl; Open space; Neighbourhood externalities; Cellular automata; Residential dynamics Abstract: This paper presents a microeconomic model of residential location that explores the emergence of a mixed belt where residents and farmers coexist beyond a city. The model is based on integrating urban economics with cellular automata in order to simulate equilibrium patterns in 2D and through time. Households commute to a CBD and enjoy neighbourhood externalities that are a function of both local residential density and farmland, or open space. They bid on the competitive land market and locate so as to maximize utility. Incremental population growth changes the neighbourhood and leads to rent adaptations. With appropriate parameter values a mixed belt may emerge between the urban and agricultural specialized areas. Settlements within this mixed area are more or less clustered or scattered depending on preferences and neighbourhood size. Author Affiliation: (a) Department of Geography, Universite catholique de Louvain, Louvain-la-Neuve, Belgium (b) Fonds national de la recherche scientifique (FNRS), Brussels, Belgium (c) Center for operations research and econometrics (CORE), Universite catholique de Louvain, Louvain-la-Neuve, Belgium (d) UMR CESAER, Institut national de recherche agronomique (INRA), Dijon, France Article History: Accepted 15 January 2007

Air 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. [ABSTRACT FROM AUTHOR]

The behavioural ecological approach to anthropology states that the density and distribution of resources determines optimal patterns of resource use and also sets its constraints to grouping, mobility and settlement choice. Central place foraging (CPF) models have been used for analyzing foraging behaviours of hunter-gatherers and drawing a causal link from the volume of available resources in the environment to the mobility decisions of hunter-gatherers. In this study, we propose a spatially explicit agent-based CPF model. We explore its potential for explaining the formation of settlement patterns and test its robustness to the configuration of space. Building on a model assuming homogeneous energy distributions, we had to add several new parameters and an adaptation mechanism for foragers to predict the length of their stay, together with a heterogeneous environment configuration. The validation of the model shows that the spatially explicit CPF is generally robust to spatial configuration of energy resources. The total volume of energy has a significant effect on constraining sedentism as predicted by aspatial model and thus can be used on different environmental conditions. Still the spatial autocorrelation of resource distribution has a linear effect on optimal mobility decisions and needs to be considered in predictive models. The effect on settlement location choice is not substantial and is more determined by other characteristics of settlement location. This limits the CPF models in analyzing settlement pattern formation processes. [ABSTRACT FROM AUTHOR]

How urban characteristics change with total population, their scaling behavior, has become an important research field since one needs to better understand the challenges of urban densification. Yet urban scaling research is largely disconnected from intra‐urban structure, and this seriously limits its operationalization. In contrast, the monocentric model of Alonso provides a residential choice‐based theory to urban density profiles. However, dedicated comparative static analyses do not completely solve how the model scales with population. This article bridges this gap by simultaneously introducing power laws for land, income and transport cost in the Alonso model. We show that the equilibrium urban structure of this augmented model matches recent empirical findings about the scaling of European population density profiles and satisfactorily represents European cities. This result is however not compatible with the observed scaling power of housing land profiles, and challenges current empirical understanding of wage and transport cost elasticities with population. Our results call for revisiting theories about land development and housing processes as well as the empirics of agglomeration benefits and transport costs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper stresses the lack of attention paid to the geographical definitions of cities in LUTI models as one key detrimental aspect to transferring and generalising LUTI results. First, the argumentation develops from a meta-analysis of peer-reviewed publications about LUTI applications in European cities. We show that most authors do not assess findings against potential geographical biases. Second, theoretical simulations are conducted withUrbanSimapplied to a synthetic urban area. By varying the geographical limits of the system and population endowments, our simulations confirm that the absence of control on city delineation weakens the results. Finally, the paper suggests methodological guidelines to improve the comparability of LUTI applications and push forward their theoretical agenda. [ABSTRACT FROM PUBLISHER]

The article introduces papers on transport research and policy within the BENELUX countries published within the issue.

ABSTRACT Leapfrog development is a typical form of sprawl. This paper aims at analyzing the existence, size, and persistence of leapfrogging in a dynamic urban economic model with endogenous green amenities. We analyze whether incoming households choose to settle at the fringe of the city or to jump further away depending on their preferences and the structure of the city. We first provide an analytical treatment of the conditions and characteristics under which a first leapfrog occurs and show how the optimal choice is affected by the size of the city, income, commuting costs, as well as the size of the area where green amenities are considered. We then study how further leapfrogging and multiple urban rings may appear and be maintained in the long-run equilibrium, and how infill processes take place through time. [ABSTRACT FROM AUTHOR]

This paper presents a method for determining and mapping suitable locations for development using Multi Criteria Analysis and the Analytical Hierarchy Process and considering uncertainties in the process. The method is applied to the case study of Howth (Dublin), where development suitability is assessed against specific protection and conservation areas as well as ground water vulnerability. Uncertainty is incorporated using a Monte Carlo simulation into the Analytical Hierarchy Process calculations to determine criteria weightings. A map is derived, which includes, for all locations, both site suitability for development and the level of uncertainty attached to this suitability. The map combines a double categorization of suitability and uncertainty. The method allows for increased transparency in decision making regarding site suitability for development, as well as increased confidence in decision making to allow for reduced risk in terms of the potential impact of development. [ABSTRACT FROM AUTHOR]

We present a theoretical model of residential growth that emphasises 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 both to like and to dislike the density of their neighbourhood, and are assumed to 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 ID elementary CA to visualise 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. [ABSTRACT FROM AUTHOR]

This article proposes a methodology for the construction and the calibration of a micro-economic urban land-use model within an extended Cellular Automata (CA) framework. The methodology is applied to processes of residential spread in a pan of the commuting periphery of Brussels. The model hypothesizes that households effect on urban development. Through their valuation of neighbourhood externalities. A coarse sensitivity analysis is undertaken in order to explore the relationship between household neighbourhood preferences and emerging spatial morphologies. These macro-structures are measured with different indices in order to parameterize the model. [ABSTRACT FROM AUTHOR]

Due to the rapidly increasing percentage of the population living in urban centres, there is a need to focus on the energy demand of these cities and the use of renewable energies instead of fossil fuels. In this paper, we develop a spatial model to determine the potential per parcel for using shallow geothermal energy, for space heating and hot water. The method is based on the space heating and hot water energy demand of each building and the specific heat extraction potential of the subsurface per parcel. With this information, along with the available space per parcel for boreholes, the percentage of the energy demand that could be supplied by geothermal energy is calculated. The potential reduction in CO 2 emissions should all possible geothermal energy be utilised, is also calculated. The method is applied to Ludwigsburg, Germany. It was found that CO 2 emissions could potentially be reduced by 29.7% if all space heating and hot water requirements were provided by geothermal energy, which would contribute to the sustainability of a city. The method is simple in execution and could be applied to other cities as the data used should be readily available. Another advantage is the implementation into the web based Smart City Energy platform which allows interactive exploration of solutions across the city. [ABSTRACT FROM AUTHOR]

This paper describes a dataset of 6284 land transactions prices and plot surfaces in 3 medium-sized cities in France (Besançon, Dijon and Brest). The dataset includes road accessibility as obtained from a minimization algorithm, and the amount of green space available to households in the neighborhood of the transactions, as evaluated from a land cover dataset. Further to the data presentation, the paper describes how these variables can be used to estimate the non-observable parameters of a residential choice function explicitly derived from a microeconomic model. The estimates are used by Caruso et al. (2015) to run a calibrated microeconomic urban growth simulation model where households are assumed to trade-off accessibility and local green space amenities.