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Spatial Uncertainty Challenges in Location Modeling with Dispersion Requirements

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Spatial Analysis and Location Modeling in Urban and Regional Systems

Part of the book series: Advances in Geographic Information Science ((AGIS))

Abstract

Geographic information systems provide the capacity to digitally create, store, manipulate, analyze and display various types of spatial information. While these functionalities enable handling of spatial data in a much more rapid and precise way than traditional paper-based approaches, uncertainties nevertheless remain in digital information and are not likely to ever be completely eliminated. Location modeling, as an important spatial analytical approach, must therefore confront the various uncertainties and errors in spatial data. In this chapter we detail multi-objective models structured to account for data uncertainty in support of location siting when spatial dispersion is a prerequisite. These models explicitly incorporate facets of data uncertainty and can be applied in a manner that enables evaluation of uncertainty impacts with statistical confidence. Solution approaches are discussed, along with the case study setting, to demonstrate how these models address spatial uncertainty in a context supporting facility location planning.

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Acknowledgements

The first author would like to acknowledge support through the 2012-13 Benjamin H. Stevens Graduate Fellowship in Regional Science as well as an Arizona State University Graduate College Completion Fellowship. This material is also based upon work supported by the National Science Foundation under grants 0924001 and 0922737. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Author information

Authors and Affiliations

  1. School of Public Policy, University of California at Riverside, Riverside, CA , 32521, USA

    Ran Wei

  2. Department of Geography, University of California at Santa Barbara, Santa Barbara, CA , 93106, USA

    Alan T. Murray

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  1. Ran Wei
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  2. Alan T. Murray
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Correspondence to Ran Wei .

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Editors and Affiliations

  1. Geography & Earth Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina, USA

    Jean-Claude Thill

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Wei, R., Murray, A.T. (2018). Spatial Uncertainty Challenges in Location Modeling with Dispersion Requirements. In: Thill, JC. (eds) Spatial Analysis and Location Modeling in Urban and Regional Systems. Advances in Geographic Information Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37896-6_12

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