Concepts, reflections and applications of social equity: approaches to accessibility to primary goods and services in the region of Flanders, Belgium

Mobility presents a variety of opportunities as it allows users to access locations and services, and to meet people beyond their immediate surroundings. While the concept of mobility primarily focuses on the ease of moving, accessibility delineates the actual potential to participate in out-of-home activities. As a result, accessibility is a complex concept with a multitude of foci. This complexity is presented in the first section, which explains the general concept of accessibility, how it is defined and how it is related to the notion of transport-related exclusion. This section also gives an overview of the body of literature on the measures to determine area-based as well as personal accessibility levels and points out the important contrast between the simple, easy-to-interpret methods, adopted by policy makers and the complex methods preferred by experts. The second section clarifies how the dichotomous relationship between the urban and rural environment is reflected in transport policy that emphasizes on (especially car-based) mobility rather than on accessibility. Furthermore, the environmental and economic points of view are highlighted and the common policy strategies focused on sustainability are illustrated. Subsequently, the shortcomings in the way in which the contemporary debates concerning mobility, sustainability and the social implications of transport planning are conducted, are criticized. Finally, the last part of this section is dedicated to an extensive discussion on the ability of transport policies to, on the one hand, generate spatially as well as temporally uneven accessibility effects that give preference to certain population groups above others, and on the other hand, their ability to strive for a more equitable distribution of transport services amongst the population. The third section proposes two methodologies for measuring transport-related social exclusion implemented in a literature-based case study in Flanders. These studies comprise the following topics: measuring transport gaps by relating the social to the transport disadvantage and measuring modal disparities by comparing accessibility by private and public transport. The former investigates in which areas the provision of the public transport system is not tailored to specific public transport needs. The latter examines the disparity in access by private and public transport in order to highlight the car dependency. Both case studies incorporate the temporal variability in provision through the private and public transport network, as the time-of-day strongly influences accessibility levels

An integrated urban systems model with GIS

The purpose of the research is to develop an integrated urban systems model, which will assist in formulating a better land use-transportation policy by simulating the relationships between land use patterns and travel behavior, integrated with geographic information systems (GISs). In order to make an integrated land use-transportation model possible with the assistance of GISs technologies, the following four sub-systems have been developed: (1) an effective traffic analysis zone generation system; (2) an iterative land use and transportation modeling system; (3) efficient interfaces between GIS and land use, and GIS and transportation models; and (4) a user-friendly graphic user interface (GUI) system. By integrating these sub-systems, a variety of alternative land use-transportation policies can be evaluated through the modification of input parameters in each simulation. Eventually, the developed model using a GIS will assist in formulating an effective land use policy by obtaining robust simulation results for both land use-transportation planners and decision makers. The model has been applied to the Urbana-Champaign area as well as to the Seoul region in Korea for a demonstration of the workings of the model.

Models of Transportation and Land Use Change: A Guide to the Territory

Modern urban regions are highly complex entities. Despite the difficulty of modeling every relevant aspect of an urban region, researchers have produced a rich variety models dealing with inter-related processes of urban change. The most popular types of models have been those dealing with the relationship between transportation network growth and changes in land use and the location of economic activity, embodied in the concept of accessibility. This paper reviews some of the more common frameworks for modeling transportation and land use change, illustrating each with some examples of operational models that have been applied to real-world settings.Transport, land use, models, review network growth, induced demand, induced supply

"So go downtown": simulating pedestrian movement in town centres

Pedestrian movement models have been developed since the 1970s. A review of the literature shows that such models have been developed to explain and predict macro, meso, and micro movement patterns. However, recent developments in modelling techniques, and especially advances in agent-based simulation, open up the possibility of developing integrative and complex models which use existing models as 'building blocks'. In this paper we describe such integrative, modular approach to simulating pedestrian movement behaviour. The STREETS model, developed by using Swarm and GIS, is an agent-based model that focuses on the simulation of the behavioural aspects of pedestrian movement. The modular structure of the simulation is described in detail. This is followed by a discussion of the lessons learned from the development of STREETS, especially the advantages of adopting a modular approach and other aspects of using the agent-based paradigm for modelling

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Towards Developing a Travel Time Forecasting Model for Location-Based Services: a Review

Travel time forecasting models have been studied intensively as a subject of Intelligent Transportation Systems (ITS), particularly in the topics of advanced traffic management systems (ATMS), advanced traveler information systems (ATIS), and commercial vehicle operations (CVO). While the concept of travel time forecasting is relatively simple, it involves a notably complicated task of implementing even a simple model. Thus, existing forecasting models are diverse in their original formulations, including mathematical optimizations, computer simulations, statistics, and artificial intelligence. A comprehensive literature review, therefore, would assist in formulating a more reliable travel time forecasting model. On the other hand, geographic information systems (GIS) technologies primarily provide the capability of spatial and network database management, as well as technology management. Thus, GIS could support travel time forecasting in various ways by providing useful functions to both the managers in transportation management and information centers (TMICs) and the external users. Thus, in developing a travel time forecasting model, GIS could play important roles in the management of real-time and historical traffic data, the integration of multiple subsystems, and the assistance of information management. The purpose of this paper is to review various models and technologies that have been used for developing a travel time forecasting model with geographic information systems (GIS) technologies. Reviewed forecasting models in this paper include historical profile approaches, time series models, nonparametric regression models, traffic simulations, dynamic traffic assignment models, and neural networks. The potential roles and functions of GIS in travel time forecasting are also discussed.

Information technology and urban green analysis

It is well recognized that green area plays a pivotal role in improving urban environment, such as preserving water and soil, controlling temperature and humidity of air, preventing pollution, flood prevention, functioning as buffers between incompatible land uses, preserving natural habitat, and providing space for recreation and relaxation. However, due to pressures from new development both in urban fringes and urban centres, urban green and open spaces are seen to be rapidly declining in term of allocated spaces and quality. Without careful urban land use planning, many open spaces will be filled with residential and commercial buildings. Therefore, there is a need for proper planning control to ensure that the provisions of green spaces are adequately being conserved for current and future generations. The need for an urban green information system is particularly important for strategic planning at macro level and local planning at the micro level. The advent of information technology has created an opportunity for the development of new approaches in preserving and monitoring the development of urban green and open spaces. This paper will discuss the use of Geographical Information Systems (GIS) incorporated with other data sources such as remote sensing images and aerial photographs in providing innovative and alternative solutions in the management and monitoring of urban green. GIS is widely accepted in urban landscape planning as it can provide better understanding on the spatial pattern and changes of land use in an area. This paper will primarily focus on digital database that are developed to assist in monitoring urban green and open spaces at regional and local context. The application of GIS in the Klang Valley region or better known as AGISwlk developed since mid-1990's is currently being used by various organisations in the region. The focus of AGISwlk is not merely in providing relevant database to its stakeholders but more importantly, assist in making specific and relevant decisions with regard to spatial planning. It is also used to monitor the loss of green areas by using several temporal data sets. The method of classifying green and open spaces in the region is also being discussed. This paper demonstrates that GIS can be an effective tool in preserving and monitoring green and open spaces in an urban area. The contribution of urban green digital database in someway may leads toward landscape sustainability as to satisfy the ever changing society

Multi-agent simulation: new approaches to exploring space-time dynamics in GIS

As part of the long term quest to develop more disaggregate, temporally dynamic models of spatial behaviour, micro-simulation has evolved to the point where the actions of many individuals can be computed. These multi-agent systems/simulation(MAS) models are a consequence of much better micro data, more powerful and user-friendly computer environments often based on parallel processing, and the generally recognised need in spatial science for modelling temporal process. In this paper, we develop a series of multi-agent models which operate in cellular space.These demonstrate the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behaviour. We first summarise the way cellular representation is important in adding new process functionality to GIS, and the way this is effected through ideas from cellular automata (CA) modelling. We then outline the key ideas of multi-agent simulation and this sets the scene for three applications to problems involving the use of agents to explore geographic space. We first illustrate how agents can be programmed to search route networks, finding shortest routes in adhoc as well as structured ways equivalent to the operation of the Bellman-Dijkstra algorithm. We then demonstrate how the agent-based approach can be used to simulate the dynamics of water flow, implying that such models can be used to effectively model the evolution of river systems. Finally we show how agents can detect the geometric properties of space, generating powerful results that are notpossible using conventional geometry, and we illustrate these ideas by computing the visual fields or isovists associated with different viewpoints within the Tate Gallery.Our forays into MAS are all based on developing reactive agent models with minimal interaction and we conclude with suggestions for how these models might incorporate cognition, planning, and stronger positive feedbacks between agents