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Advances in location modeling: GIS linkages and contributions

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Abstract

Geographic information systems (GIS) have matured and proven to be an enabling technology, one that is important to many disciplines. Location analysis is also a field that has matured and continues to evolve. In fact, the combination of GIS and location science is at the forefront of advances in spatial analysis capabilities, offering substantial potential for continued and sustained theoretical and empirical evolution. This paper provides an overview of location analysis and discusses GIS. The paper highlights how GIS has contributed to location science in terms of data input, visualization, problem solution and theoretical advances. The significance of GIS in this context is that it is far more than a mere spatial data input mechanism, which is a commonly held misconception within geography, operations research and other allied disciplines. In contrast to other reviews, the focus in this paper is to highlight the theoretical foundations of location analysis and modeling and how GIS is contributing to important advancements in this field. An overall contribution of the paper is providing a perspective on spatial analysis and how associated specialty areas are evolving and thriving, particularly as a component of GIScience.

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Notes

  1. Church (1999) identifies four general classes of location models, median, covering, capacitated and competitive, not unlike the distinction made in Daskin (1995). Here, the allocation term is preferred, as it is more encompassing than median. Further, given that allocation (and median) and covering models can have capacities, the capacitated distinction is avoided. Some conceive of covering and center problems as distinct (see ReVelle and Eiselt 2005), though both address equity concerns. Thus, they have been combined here under the heading of an equity class. Owen and Daskin (1998), among others, distinguish stochastic location models, so this is included as a fourth class in the presented classification.

  2. Assumed conditions are that demand is uniformly distributed, the facility provides circular coverage from a point and the diameter of the circular coverage is less than or equal to that of the minimum enclosing circle.

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  1. GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, 85287-5302, USA

    Alan T. Murray

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Murray, A.T. Advances in location modeling: GIS linkages and contributions. J Geogr Syst 12, 335–354 (2010). https://doi.org/10.1007/s10109-009-0105-9

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