Edited by Stan Geertman and John Stillwell
Stan Geertman and John Stillwell
This introductory chapter has two main objectives. First, it acknowledges the rapidly changing world that we live in and summarises some of the mega trends, challenges and risks at different scales that provide the context for the development of the sub-discipline that we now refer to as planning support science and the planning support systems (PSS) that have been created. Second, the rationale for the sequence of the remaining chapters in this handbook that have been grouped into key themes is explained and a short resumé of each chapter is presented that outlines the objectives and key contributions in each case. Several of the chapters report on particular PSS applications.
Mark Birkin, William James, Nik Lomax and Andrew Smith
This chapter addresses the linkage of data sets, incorporating the characteristics of individuals using the technique of spatial microsimulation (SMSM). We present two case studies to exemplify how SMSM can be used in planning support systems (PSS), both of which are combining data from different sources. The first details ongoing work to produce household and population projections which are being used for resource planning for a range of utilities. The second describes a project estimating consumer demand for pork and other meat products in the UK. We offer some conclusions on the current challenges faced when linking data sets for the purposes of planning support and conclude that SMSM offers the potential to provide smarter, more flexible PSS because models are produced of individuals who require services and make decisions.
Elisabete A. Silva, Lun Liu, Heeseo Rain Kwon, Haifeng Niu and Yiqiao Chen
As human society evolves, it’s spatial and aspatial imprint becomes more complex owing to increasingly sophisticated interactions. The twenty-first century presents a set of opportunities and challenges that result from a key development: the use of digital means. This chapter reviews key cutting-edge approaches that are informing this new digital world. A mixed-methods approach can capture both hard-physical (quantitative) and soft-aspatial (qualitative) analysis as a hybrid approach depending on the task at hand. Using case studies from the UK, China, Germany and South Korea, this chapter first introduces current data availability, its opportunities and challenges, and the required need to integrate with more classical methods and existent data sets. The chapter discusses crowdsourcing, one of the fast-growing data collection methods that bridges the quantitative/hard and qualitative/soft data analysis; uses these methods and sentiment analysis for public policy analysis; presents an application of hard data collection associated with local/remote sensing linked with soft data collection of field surveys; pinpoints the key role of a new generation of learning algorithms towards data harvesting, mining and calibration; and explores the role of behavioural theories in support of these new learning algorithms.
Christopher Pettit, Bob Stimson, Jack Barton, Xavier Goldie, Philip Greenwood, Robin Lovelace and Serryn Eagleson
Open access data, open source software and cloud computing are three parallel and mutually reinforcing drivers of change in the field of applied geographical information systems (GIS). While these developments create many new opportunities for GIS users and companies, they are also associated with under-explored risks. This chapter investigates cloud GIS, focusing on the Australian Urban Research Infrastructure Network (AURIN), an online, cloud-based data portal and GIS designed explicitly for Australian urban research and public-sector planning applications. AURIN provides direct access to more than 4000 data sets, over 100 spatial analysis tools and powerful computational resources that are typically available in desktop GIS. The experience of developing, communicating and using AURIN has provided insights into the opportunities unleashed by new models of GIS research. This chapter explores those opportunities, such as greater accessibility, transparency and consistency in decision support for public policy, and risks of cloud GIS and its potential uses for social benefit.
Geodesign is a new buzzword currently used to refer to a novel but growingly popular approach to spatial planning and design. It entails the integrated use of methods and enabling technologies to address the complexity of current urban and territorial development challenges by integrated processes, including project conceptualization, knowledge building and evaluation, alternative design creation, impact evaluation, collaboration and participation. This chapter presents the geodesign approach, contributing three main complementary section. The first section sets the context for geodesign diffusion, from its origin to its most recent developments. It includes a brief overview of the history of geodesign, a review of the relevant growing literature, the diffusion of geodesign education, and the community involved in its application. The second section, in the light of the Steinitz framework for geodesign, reviews the main technologies for geodesign support, and their coupling in planning support systems (PSS) which may enable planners to handle complex workflows within the planning and design process, before focusing on the novel Geodesignhub PSS. The final section discusses the opportunities that geodesign and enabling technologies can contribute to bring innovation into current spatial planning practice and to address some of the most critical parts of the weakest and less understood issues of the design process, such as the effective link between knowledge building, design creation and decision making.
Tianyu Su, Shihui Li, Jing Li, Hungyu Chou and Ying Long
With the rise of city science and data science, big data such as records of bike-sharing, mobile phone signalling, public transportation records and open data from various sources, jointly promote the formation of a new data environment, which provides a stable underpinning for the emergence of innovative planning and design methodologies. Also, historical areas in the existing built environment require renewal and redevelopment to adjust to the spatial requirements of the twenty-first century. Given this situation, this chapter delivers a new quantitative methodology for urban planning and design, termed data augmented design (DAD), and tests its application in an urban redevelopment design project. The main steps and two primary methods of DAD for urban redevelopment design – existing condition analysis and spatial parameter extraction – are introduced. The chapter applies these methods in the urban redevelopment design for the Panyu-Xinhua Area in Shanghai, China. Their effectiveness is evaluated from the perspective of planners, officers and citizens. I addition to the academic and practical contributions, potential applications, potential bias and future research using DAD methods are also discussed.
Yexuan Gu and Brian Deal
To improve the widespread applications of planning support systems (PSS), this chapter proposes a procedural framework that provides a systematic and comprehensive process for PSS implementation. The procedural framework is created by integrating PSS technologies and a geodesign process within a resilience framing. By integrating these technologies, processes and theories, we develop a framework that can help broaden the realm of PSS implementation from a purely planning-orientated activity into other fields. The new framework invites a variety of organizations, scientists, stakeholders and community residents to engage in the process and collaborate. The framework also helps to reveal the value of PSS technologies in achieving more resilient outcomes. The proposed procedural method can reshape organizational characteristics towards PSS use. We first briefly describe the notions of geodesign, resilience, and introduce a PSS technology platform in shaping a new PSS implementation framework. We then test the robustness of the framework in a case-study application in Sangamon County, Illinois. In our application we find that the proposed integration both enhanced the usefulness of the PSS and improved the overall credibility of the geodesign-based and resilient design process. We conclude the chapter with a discussion on advantages, potential challenges and transferability of the framework across different contexts.
Subhrajit Guhathakurta, Ge Zhang and Bon Woo Koo
Spatially explicit data about the physical and natural environment are becoming ubiquitous with the growing number of air/space-borne and terrestrial sensors. While this growing volume of data has transformed the operations of various sectors in both private and public domains, such as agriculture, natural resource management, transportation and retail services, the impact on urban spatial planning has been minimal. This chapter discusses the evolving approaches to spatial modelling and forecasting as they apply to planning urban communities. The objective is to focus on the key developments in the recent past in spatial modelling and show how big data and machine learning based techniques can be incorporated into future planning models.