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.

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

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

Equilibrium and first-best city with endogenous exposure to local air pollution from traffic

Exposure to urban traffic-induced air pollution is a major health concern of cities. This paper analyzes the urban structure when localized pollution exposure arises from commuting traffic and investigates the feedback effect of endogenous pollution on residential choices. The presence of stronger traffic-induced air pollution exposure reduces the geographical extent and the population of cities. Land rents fall with distance from the city center while population densities may be non-monotonic. Cleaner vehicle technologies reduce pollution exposure everywhere, increase population and density everywhere and do not affect the spatial extent of the city. The paper compares the urban equilibrium with the first-best. The first-best structure is a less expanded city with higher densities at the center and lower densities at the fringe

Discrete Path Planing Strategies for Coverage and Multi-Robot Rendezvous

This thesis addresses the problem of motion planning for autonomous robots, given a map and an estimate of the robot pose within it. The motion planning problem for a mobile robot can be defined as computing a trajectory in an environment from one pose to another while avoiding obstacles and optimizing some objective such as path length or travel time, subject to constraints like vehicle dynamics limitations. More complex planning problems such as multi-robot planning or complete coverage of an area can also be defined within a similar optimization structure. The computational complexity of path planning presents a considerable challenge for real-time execution with limited resources and various methods of simplifying the problem formulation by discretizing the solution space are grouped under the class of discrete planning methods. The approach suggests representing the environment as a roadmap graph and formulating shortest path problems to compute optimal robot trajectories on it. This thesis presents two main contributions under the framework of discrete planning. The first contribution addresses complete coverage of an unknown environment by a single omnidirectional ground rover. The 2D occupancy grid map of the environment is first converted into a polygonal representation and decomposed into a set of convex sectors. Second, a coverage path is computed through the sectors using a hierarchical inter-sector and intra-sector optimization structure. It should be noted that both convex decomposition and optimal sector ordering are known NP-hard problems, which are solved using a greedy cut approximation algorithm and Travelling Salesman Problem (TSP) heuristics, respectively. The second contribution presents multi-robot path-planning strategies for recharging autonomous robots performing a persistent task. The work considers the case of surveillance missions performed by a team of Unmanned Aerial Vehicles (UAVs). The goal is to plan minimum cost paths for a separate team of dedicated charging robots such that they rendezvous with and recharge all the UAVs as needed. To this end, planar UAV trajectories are discretized into sets of charging locations and a partitioned directed acyclic graph subject to timing constraints is defined over them. Solutions consist of paths through the graph for each of the charging robots. The rendezvous planning problem for a single recharge cycle is formulated as a Mixed Integer Linear Program (MILP), and an algorithmic approach, using a transformation to the TSP, is presented as a scalable heuristic alternative to the MILP. The solution is then extended to longer planning horizons using both a receding horizon and an optimal fixed horizon strategy. Simulation results are presented for both contributions, which demonstrate solution quality and performance of the presented algorithms

Toxic metal concentrations in cigarettes obtained from U.S. smokers in 2009 : results from the International Tobacco Control (ITC) United States survey cohort

This research was funded by grants from the U.S. National Cancer Institute (R01 CA100362 and P01 CA138389), and the Canadian Institutes of Health Research (115016). Geoffrey T. Fong was supported by a Senior Investigator Award from the Ontario Institute for Cancer Research (OICR) and a Prevention Scientist Award from the Canadian Cancer Society Research Institute.Smoking-related diseases can be attributed to the inhalation of many different toxins, including heavy metals, which have a host of detrimental health effects. The current study reports the levels of arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb) in cigarettes obtained from adult smokers participating in the 2009 wave of the ITC United States Survey (N = 320). The mean As, Cd, Cr, Ni, and Pb levels were 0.17, 0.86, 2.35, 2.21, and 0.44 mu g/g, respectively. There were some differences in metal concentrations of cigarette brands produced by different manufacturers, suggesting differences in the source of tobaccos used by different companies. For Ni, there were significant pairwise differences between Philip Morris U.S. (PMUSA) and R.J. Reynolds (RJR) brands (PMUSA higher; p 0.10). Because of the variety of toxic heavy metals in cigarette tobacco, and their numerous negative health effects, metal content in cigarette tobacco should be reduced.Publisher PDFPeer reviewe