Geographical information systems and location science

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Abstract

Since the 1970s the field of Geographical Information Systems (GIS) has evolved into a mature research and application area involving a number of academic fields including Geography, Civil Engineering, Computer Science, Land Use Planning, and Environmental Science. GIS can support a wide range of spatial queries that can be used to support location studies. GIS will play a significant role in future location model development and application. We review existing work that forms the interface between GIS and Location Science and discuss some of the potential research areas involving both GIS and Location Science.

Scope and purpose

During the past 30 years there have been many developments in spatial data analysis, spatial data storage and retrieval, and mapping. Many of these developments have occurred in the field of Geographical Information Science. Geographical Information Systems software now supports many elementary and advanced spatial analytic approaches including the production of high quality maps. GIS will have a major impact on the field of Location Science in terms of model application and model development. The purpose of this paper is to explore the interface between the field of Location Science and GIS.

Introduction

Geographical information systems (GIS) are designed to store, retrieve, manipulate, analyze, and map geographical data. The central element of a GIS is the use of a location referencing system so that data about a specific location can be analyzed in its relationship to other locations. Both plane and global coordinate systems are commonly used. A system may be capable of easily transforming one referencing system (e.g. Universal Tranverse Mercator (UTM)) to some other referencing system (e.g. State Plane Coordinates). This makes it possible to take data that has been stored in one form and combine it with data that has been entered and stored in some other form. The use of GIS has come of age as a result of several interrelated factors. First, there are many GIS software products that are available from commercial vendors and universities. Second, computer workstations are now capable of handling many of the computational, retrieval, and storage problems within a reasonable amount of time and at reasonable cost. Third, graphical displays and plotters are now sophisticated and fast, producing high-quality and high-resolution output. Fourth, geographic data vendors as well as governmental agencies such as the Bureau of the Census of the US Government have made large amounts of geographic data available at reasonable cost. Fifth, the use of remote sensing has expanded, especially in environmental monitoring, and this has led to the need for systems that are capable of handling large amounts of data as well as serve as a major source of land coverage information. Sixth, the emergence of the satellite based Global Positioning System (GPS) has made it easy to collect attribute data along with its location at relatively low cost and with relatively high accuracy. Each of these factors has contributed to the growth of the GIS industry.

It is now common to see GIS software in use in municipalities, states, utilities, and governmental agencies like the US Forest Service, transportation companies, and consulting firms. Such systems range from simple, limited systems to large, complex software systems. Many utilize commercial off-the-shelf systems, but some agencies and companies have developed their own proprietary systems. There are now many trade magazines and journals that are devoted to aspects of GIS, and many universities maintain special GIS laboratories and offer specialized classes in GIS. The mere fact that GISs are used to store, retrieve, and map geographic data should be of interest to practitioners of Location Science. But, just what makes GIS so important to the field of Location Science? Are there aspects of Location Science that are inextricablly linked with GIS? Just what are the emerging problems related to GIS and Location Science? The objective of this paper is to provide a review of GIS and Location modeling with the purpose of addressing these questions.

Section snippets

Background

There are two fundamentally different types of GIS software. They differ in terms of the data model, i.e., the means for storing geographical data. Since the real world is so complex, it would take an infinitely large database to capture the real world precisely. Data therefore must be generalized or abstracted to reduce it to some manageable quantity. Data are represented as a finite set of objects. The two principal data models are raster and vector. The raster model divides the study area

Brief history of GIS and facility location

The siting (i.e., location) and placement (i.e., orientation) of a major facility such as a roadway, factory, or housing project has long been a subject of interest in the field of landscape architecture. Such problems can be quite “wicked” [1]. For example, the routing of a freeway segment in an urban area must meet a number of competing objectives. To accomplish a task such as road location, McHarg [2] proposed an approach which deals with the preparation of a number of maps, each with a

Bridging between traditional location models and GIS

When Revelle and Swain [21] first published an integer linear programming formulation of the p-median problem, they gave results based upon a 55 node data set. Subsequent testing and analysis has reused this data set numerous times. In 1970, few data sets of spatial demand existed, and what existed were small (i.e., less than 75 nodes). One major element controlling problem size was the fact that most problems that were larger than 75 nodes could not be solved optimally. A further complication

Research areas in integrating location models with GIS

Inevitably, GIS and Location models will be linked for model applications. Linking GIS and models requires that a number of technical and basic research issues be addressed [34]. Although we cannot list and discuss all of the pertinent issues in this review paper, we can highlight six major categories of integration and linking factors.

(1) Problem scale and representation: at what level of scale should a problem be represented? In a GIS, problem data may be stored by individual customer or

Current developments in GIS and location models

ReVelle et al. [57] were the first to classify location models into two broad classes of problems: continuous space and discrete network-based models. Location model development has concentrated on the latter of these two areas. Some of this modeling bias is because a network can capture a number of nuances of spatial variability that are often assumed away in a unbounded, continuous, planar representation. A network model may accurately represent travel distances in an urban area, whereas an

Conclusions

Geographical Information Systems involve software that provides storage, retrieval, analysis, visualization, and mapping capabilities for spatial data such as road networks, land use information, census track data, etc. Some GISs include embedded location models and most provide the opportunity to integrate location models within a map-based graphical user interface. Because GIS can be used to assemble data from various sources involving different map scales and transformations, it can be a

Richard Church is a Professor of Geography at the University of California, Santa Barbara. He has extensive experience in the modeling of complex logistics and spatial optimization problems. He received a Ph.D. from the Johns Hopkins University in Environmental Systems Engineering in 1974. He specializes in applied Operations Research as well as Location and Transportation research and Decision Support Systems. He has published over 100 papers and monographs in related journals and research

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    Richard Church is a Professor of Geography at the University of California, Santa Barbara. He has extensive experience in the modeling of complex logistics and spatial optimization problems. He received a Ph.D. from the Johns Hopkins University in Environmental Systems Engineering in 1974. He specializes in applied Operations Research as well as Location and Transportation research and Decision Support Systems. He has published over 100 papers and monographs in related journals and research publication series. Dr. Church has served as a consultant to numerous federal agencies and private companies. He has recently published in the area of conservation reserve design, intelligent transportation systems, forest management, and manpower deployment planning. Current research funding includes the U.S. Forest Service, the Bureau of Land Management, the U.S. Geological Survey, U.S. Department of Transportation, Caltrans, and the National Science Foundation.

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