Handbook of Planning Support Science
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Handbook of Planning Support Science

Edited by Stan Geertman and John Stillwell

Encompassing a broad range of innovative studies on planning support science, this timely Handbook examines how the consequences of pressing societal challenges can be addressed using computer-based systems. Chapters explore the use of new streams of big and open data as well as data from traditional sources, offering significant critical insights into the field.
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Chapter 3: Hard and soft data integration in geocomputation: mixed methods for data collection and processing in urban planning

Elisabete A. Silva, Lun Liu, Heeseo Rain Kwon, Haifeng Niu and Yiqiao Chen

Abstract

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.

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