Planning Support Systems for Sustainable Urban Development

Since its introduction, geographic information science has witnessed a tremendous growth and can build on enormous achievements (e.g. Cheng et al. 2012). Current geographic information systems and the decision support systems and models that have been accompanying these systems have a strong ‘geography’ identity, typical of the era in which geographic information system were introduced. Systems are mostly based on spatial entities (mostly grids or polygons). To the extent that commercial and open source geographic information systems have been enriched with models, a similar strong geographic flavor can be discerned. Most models of spatial choice behavior are related to the aggregate spatial interaction models, models of land use change are often based on cellular automata. The question then becomes whether dominant spatial decision support systems, fundamentally based on aggregate spatial interaction, cellular automata and similar models, are suitable for adequately predicting consumer response. We content that in light of the increasing complexity of the decision making process and increasing personalization of decisions and lifestyles, these systems and their underlying models have increasingly become inadequate and obsolete. The field should shift to the development of more integral microscopic models of choice behavior, allowing more integral policy performance assessments. Moreover, mobile computing should allow and stimulate the development of real-time information and decision support systems that support the management of urban functions and include persuasive computing. Uncertainty analysis should play an integral role in these developments.

Many studies on land use change have been performed in order to provide fundamental information for future land use plans. In the estimation process of transition probabilities of land use, it should be noted that the spatial unit of land use conversions in city area is a lot. The present study proposes a land use model based on the transition probability of lots, which can be built in planning support systems for sustainable urban development. Lot conversions such as changes in land category, division of lots, the demolition/reconstruction of buildings, changes in building types are described in the models, and we investigate what variables are best to describe the structure of lot conversions. Using the model estimated from time-series GIS data, we discuss the effects of land use policy by simulating land use change in the future, and demonstrate that it is necessary to control the potential for development of lots by adopting adequate zoning regulations and widening roads, by taking into account effects on lot conversions.

Creative industries have been widely adopted to promote economy growth, urban regeneration and innovation. It is expected that this strategy can produce a sustainable development model. However, in reality it is not effective enough because the implemented policy based on linear analysis is misleading. This chapter aims to fill this gap by examining the dynamics among creative industries, urban land space and urban government from a complex systems’ view. It presents a general simulation framework and an agent-based model (named “CID-USST”) developed in NetLogo. This is a spatially explicit model where a simplified urban space is used to represent the real urban land space. The agents involved include the creative firms, the creative workers, and the urban government. The resulting urban spatial structure is examined from two aspects: the spatial density distribution and the spatial clustering pattern of both the creative firms and the creative workers.

Land consolidation is considered as the most effective land management planning approach for solving the land fragmentation problem in rural areas and more broadly to assist the implementation of regional and urban planning. This chapter focuses on a planning support system for land consolidation in rural areas called Land CONsolidation Integrated Support System for planning and decision making (LACONISS) that integrates GIS, artificial intelligence techniques and multi-criteria decision methods. The system involves four modules: the Land Fragmentation System (LandFragmentS) module measures existing land fragmentation in an agricultural context; the Land Spatial Consolidation Expert System (LandSpaCES) Design module produces alternative land redistribution plans; the LandSpaCES Evaluation module assesses these plans based on a set of criteria; and the Land Parcelling System (LandParcelS) module produces the final land partitioning plan. The final output is the land reallocation plan. The whole system has been applied to a case study area in Cyprus and this reveals that land fragmentation can be reliably measured, that alternative land reallocation plans can be produced that can successfully emulate planners’ reasoning, that the most beneficial plan for various combinations of criteria and weights can be identified and that the subdivision process can be automated satisfactorily although further improvements are needed. The contribution of LACONISS is relevant to both rural and urban sustainable development since it supports and automates the land reallocation (or land readjustment) process which is the principal component of any land consolidation project whether rural or urban. Eventually, LACONISS may constitute the foundations for developing a generic system that could be applied in any country that implements land consolidation projects.

Land-use microsimulation is becoming an indispensable function in a planning support system for sustainable urban development because it provides the detailed information necessary for decision making on emerging issues at the household or firm level. In land-use microsimulations, there are two approaches for estimating base-year micro-data: cell-based population synthesis, which generally uses the iterative proportional fitting method, and agent-based methods. This chapter compares these two methods qualitatively and quantitatively. The qualitative comparison shows that neither one is superior in every aspect. The cell-based method is preferred when the microsimulation deals with data sufficiently simple, while the agent-based method is preferred when accurate and/or numerous micro-data attributes are demanded. Similarly, the quantitative comparison based on a goodness-of-fit evaluation does not show a single superior method for all applications. These findings suggest a way for selecting a better method based on the conditions of the microsimulation model and the purpose of its application.

This chapter illustrates an application of the Conversion of Land Use and Its Effects at Small regional extent (CLUE-S) model, combined with Geographic Information System (GIS) and Remote Sensing (RS) technology, in simulating future land use and landscape pattern change under different land use scenarios in Xinzhuang town, Jiangsu province, China. It is based on multi-temporal high-resolution remotely sensed images. Three different scenarios are designed to simulate the future patterns of the study area. Kappa coefficients are applied to evaluate the feasibility of CLUE-S model for supporting spatial planning. The results showed that the increase of construction land and decrease of paddy fields would be the dominant trend of future land use change. Plenty of farmlands and ecological land will be encroached by construction land in the next 20 years. The landscape pattern will be more fragmented, disaggregated and disconnected, and the landscape will become more diversified and homogenous. The prediction accuracy of CLUE-S is satisfactory; it means that this model can provide scientific support for land use planning and policy making.

GIS-based Strategic Environmental Assessments (SEA) generally require the processing of a variety of environmental and planning data. Therefore, it is necessary to combine thematic datasets in different spatial resolutions. This chapter presents a method for the generalization of a city-wide biotope-type assessment and an urban structure and inventory of open and green spaces map for the city of Berlin. The method includes the aggregation of an ecological assessment of a biotope-type map to a more generalized block-based inventory of open and green spaces map by areal weighting. The results show that the combination of the two datasets can be very sufficiently utilized to detect areas of high ecological significance in early stages of environmental planning. The application of a 1 ha minimum mapping unit leads to a better integration of biotope-type information into the block structure than the utilization of a 3 ha-size criterion.

Sustainable urban development is a critical issue in the Netherlands. The country is densely populated, which causes conflicts between environmental concerns and spatial development. Environmental policy integration is proposed as a way to improve the integration of environmental values into spatial planning with the help of learning processes. This chapter evaluates the extent to which the combination of a map-based touch table and an area-specific environmental profile are of added value to environmental policy integration. The case study is the application of the map-based touch table, called MapTable® for the development of a sustainable neighborhood in the region of Utrecht, the Netherlands. It was found that MapTable® facilitates learning processes by providing a platform for communication among stakeholders from different backgrounds. Nonetheless, it must be ensured that all stakeholders are equally included, and that the process suits the application of a map-based touch table in combination with an area-specific environmental profile.

Traditional efforts to improve the quality of life in our communities have, at times, had detrimental effects on both the environment and the very issues the investments were designed to address. Sustainable development decisions must take into account–in social, economic and environmental terms–the long-term impacts of planning and investment decisions. In this chapter we argue that advances in computation techniques and network infrastructure enable the next generation of planning support systems to support such an accounting. We describe our experiences and lessons learned from application of the LEAM planning support system and a Web-based GeoPortal in helping to sustain critical green infrastructure resources in the state of Illinois.

This chapter explores a GIS-based performance metric for designing a low energy agriculture system in the City of Atlanta. A framework of a planning support system (PSS) is proposed, which contains dimensions of representation, performance and scenario planning. The specific PSS demonstrated how a performance-oriented urban design decision model reorganizes fragmented information and turns them into useful representational layers, analyses of performance measures, and scenario planning for making design decisions.

This review considers previous researches that dealt with energy modelling in the built environment at different urban spatial scales. Up to now, modelling approaches focus on energy flow simulation in urban area from generation to distribution and finally consumption. Dependent on the energy flow direction and focus of these models in urban energy system, they are categorized in three distinct groups: supply, demand and integrated models. A critical evaluation of each category of these models based on the same criteria is provided. As a result, some of the main aspects that are missing in the existing models are highlighted, including: integrated multilayer models, spatial implications of renewable energy technologies and integration of simulation and optimization methods.

This paper presents a procedure to analyse the quality of the urban space on the vicinity of public transport stations. This procedure evaluates walk and bicycle paths near the stations based on indicators mainly related to the physical characteristics of these paths. To define these indicators, a bibliographical review and a survey research in subway stations in Rio de Janeiro, Brazil were developed. From this survey, the distances travelled by users to the stations were evaluated and the attractive factors of walk and bicycles trips around them were identified; finally, based on these indicators, a spatial analysis of paths around a transit station is presented. For the spatial analysis, a Geographic Information System (GIS) was used. The resulting maps indicate the quality levels of the walk and bicycle paths.

Improved pedestrian safety is integral to walkable, sustainable neighborhoods. This study aggregated 2,944 pedestrian-vehicle collisions in the Seattle-King County area using a 500 m² grid overlay that captured related road and neighborhood characteristics. Collision cells were concentrated in 17.4 % of the extent, and 17.0 % of the collisions took place in high-frequency collision locations clustered in a 3.5 km² area. A negative binomial model estimated that the frequency of collisions in grid cells correlated to higher volumes of vehicles and bus riders (boarding and alighting counts), higher intersection and traffic signal densities, higher densities of residential units and jobs, and several known pedestrian activity generators. These proxy measures of pedestrian activity and exposure to vehicles confirmed a lack of pedestrian safety in the metropolitan areas. The relatively small number of locations with high and very high pedestrian-vehicle collisions should facilitate targeted, effective, and inexpensive pedestrian safety improvement programs.

This manuscript describes a computer-aided approach for the design and evaluation of potential impacts of new cycling routes connecting a university campus with the city’s street network. The routes were based on the analyses of actual trips reported in a survey carried out with over 900 undergraduate students, and field information obtained from Google Earth (GE). Whereas GE helped in the identification of suitable paths, GIS tools were used to assess the potential impacts of the proposed routes on bicycle, car and walking trips. The results show that the proposed methodology is adequate for exploratory studies and transferable to a Planning Support System (PSS). Such a system could be designed for a variety of goals, such as design of paths, management of bicycles flows, etc. Although this study focuses on the particular case of a university campus, the approach can be easily applied to other large trip generators.

This paper demonstrates a new methodology for finding optimal walking routes according to user specified conditions selected from a set of attribute choices. The pedestrian network planning methodology discussed in this paper reflects the influence of environmental factors facilitating or impeding pedestrians’ propensity to walk. The principle tasks involved in applying this method include identifying attributes of walkability, weighting the importance of each attribute, evaluating the composite walking cost of each street segment, and identifying the optimal route by aggregating segments that minimize the total cost. A case study of the city of Atlanta is presented to demonstrate the application of this method and discuss its limitations.

In the absence of a comprehensive population registration system in the United Kingdom (UK), the decadal Census of Population provides a crucially important source of demographic and socio-economic data both for academic research as well as planning and policy making for urban sustainability. Data from recent UK censuses have been used to produce a variety of products in digital form at different spatial scales, ranging from the counts of individuals or households with particular characteristics captured by the census questionnaire and often referred to as aggregate statistics, to samples of the population at individual or household level, known collectively as micro data. Access to these often large and complex data sets for social science research has been facilitated through the development of a set of services funded by the Economic and Social Research Council (ESRC) under the Census Programme. In this chapter, we review the current Census Support Service at a point of transition to a more integrated system allowing users ‘one stop shop’ access to a range of different data sources, including those associated with the census, through the facility known as the UK Data Service.

The chapter introduces the Online What if? (OWI) GIS-based planning support system, which is being made available through the Australian Urban Research Infrastructure Network (AURIN). AURIN has been established to provide an advanced information infrastructure to support discipline-specific and multi-disciplinary research and promote sustainable urban development in Australia. OWI is an open source online version of the widely used desktop What if? planning support system developed by Klosterman (1999). OWI enables a range of end users to create and explore what if? land use change scenarios. This chapter discusses OWI in the context of a demonstrator case study in Hervey Bay, Queensland, and introduces future applications of this collaborative planning tool to support the sustainable planning of cities in Australia.

Cellular automata (CA) as an emerging technology has been adapted increasingly by geographers and planners to simulate the spatial and temporal processes of urban growth. While the literature reports many applications of cellular automata models for urban studies, in practice, the operation of the models and the calibration of the parameters in use were only known to the modellers. This is largely due to the constraint that most CA models were developed based on desktop computer programs, either by incorporating the model within a desktop GIS environment, or developing the model independent of a desktop GIS. Consequently, there is little input from the user to test or visualise the actual operation or evaluate the applicability of the model under different conditions. This chapter presents a methodology to implement a fuzzy constrained urban CA model within a web-based GIS environment using Gold Coast City in Southeast Queensland, Australia as a case study to simulate its spatio-temporal processes of urban growth. With the web-based CA model, users can visualise and test the operation of the model; they can modify or calibrate the model’s parameters and evaluate its simulation accuracies, or even feed the model with ‘what-if’ conditions to generate alternative outcomes. This web-based modelling platform provides a useful channel to foster public participation in urban planning and management.

This chapter presents the framework for and implementation of a flexible, loosely coupled geoportal platform for supporting distributed urban modelling with spatially detailed land use and transportation interactions. The proposed framework is built upon open source applications, such as Apache, PostgreSQL, MapServer, Drupal, Flex, and MediaWiki, with minimal custom code and some integration of proprietary tools such as ArcGIS Server. It provides collaborative tools to support parallel development and interconnection of complex model components in a manner that facilitates the visualization, discussion, and sharing of intermediate results. Large-scale land use, transportation and environment modelling contains many components which are themselves complex, in various stages of development, and distributed among different research groups. Many of the datasets needed for model calibration are incomplete, more aggregated than desired, or yet to be acquired. The geoportal platform is aimed at accelerating the realistic evolution of modelling data and cross-group learning as well as enhancing sense-making during early stages of model exploration and integration. The development and sharing of origin/destination matrices and modelling results from four scenarios are used to illustrate the types of visualization and cross-group interactions that are facilitated.

The main goal of this book chapter is to present a framework for analysis of online participation platforms. Recently, the whole range of various participation platforms emerged and there is a need for a model, which would enable to analyse their specific characteristics. The framework presented in this chapter, the participatory cube, is based on models proposed by Fung (2006) and Ferber et al. (2007). It consists of three axes: interactive communication, access to space of participation, and decision power. These categories play a major role in the analysis of the implemented study cases. The study cases were taken from Germany and Brazil. We concentrated on the selection of a variety of technologies that support civic engagement. The participatory cube served as the model for the comparison of the selected cases. We conclude the article with a discussion about the presented model and further research directions.

This research compares two methodologies to gain an insight into which may best fit the research of Planning Support Systems (PSS) used in planning practice. The approach taken by this research is twofold; firstly using data collected through case studies and the application of Actor-Network Theory (ANT), and secondly, an online questionnaire of staff in government and private practice. The questionnaire data was analysed using the Unified Theory of Acceptance and Use of Technology (UTAUT). Results of applying ANT can provide useful insights into the social and technical interactions that are relied upon to build and implement a PSS. Moreover, the UTAUT results found that in order for Information and Communication Technology (ICT) applications to be widely accepted by planners, the organizations in which they work need to address performance expectancy and facilitating conditions as priorities. Although the methods used in this research are vastly different, results have been found to be somewhat complimentary.

In recent decades, governance approaches have been widely advocated in the context of immigrant communities. The interplay between state, market, and civil society results in several modes of governance in these approaches. This chapter shows that each mode of governance has its positive and negative consequences for the regeneration of immigrant communities. Planning support systems (PSS) can assist in dealing with the negative consequences. This chapter suggests that three types of PSS—namely “informing PSS,” “communicating PSS,” and “analyzing PSS”—can play a distinctive role in dealing with the specific deficiencies of each mode of governance in the context of immigrant communities.

Large scale and long term decision making processes encounter a huge amount of difficulties. On the one hand, the uncertainty about the future represents a fundamental problem which is innate in long-term planning. On the other hand, the different interests and opinions regarding goals and strategies among the various actors are complex issues to be tackled. In order to build common knowledge and facilitate reasoning among the different actors, the following research proposes a method for sharing information through the use of dynamic maps. By means of the visual localisation of costs and benefits, the participants in the spatial decision processes are led to evaluate methods and objectives for a number of alternative development options. The system has been used in different case studies and has shown its effectiveness in creating awareness of spatial problems and enhancing discussions.

This chapter contributes to the literature on the dyad creative design versus analytical assessment. It describes the challenges of creating a planning support system acceptable by designers, and reports the success of combining two planning support tools: Phoenix, an easy-to-use natural user-interface (using multitouch and physical objects input) for spatial design and Urban Strategy, a framework for integrating advanced environmental and socio-economic models for urban sustainability analysis. The systems were developed in different circumstances, contexts, by and for different groups, but their combination unlocked the key to user acceptance and adoption. Their extremely low learning curve attracts even the most technophobic stakeholders and makes use of recent advances in cloud computing for storage and processing to deliver immediate feedback. It allows anyone (especially designers) to sketch their solutions with natural movements and immediately receive feedback on key indicators of the sustainability performance, enabling iterative improvements of designs.