Edited by Stan Geertman and John Stillwell
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.
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