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Integration Of Geographical Information Systems Based Spatial Analysis In Recreation Demand Analysis

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  • Bhat, Gajanan
  • Bergstrom, John C.

Abstract

This study has examined the use of an Object-Oriented GIS framework to generate and analyze spatial data in recreation demand analysis. Several forms of GIS analysis are introduced and explained as how they can be utilized in recreational demand analysis. An application of GIS to calculate journey distance and duration has been illustrated with a case study of camping activities in Cherokee National Forest, North Carolina. The recreation demand models using these travel distance and duration are then compared with the models using respondent's stated values and models using distance data obtained from ZIPFIP software. Based on the criteria such as 2 statistic, individual coefficient significance, it is found out that travel cost functions based on GIS calculated distance and time performed better than the other two functions. The coefficients of travel cost and travel time in the GIS-distance based models are highly significant. Thus, a measurement approach that combines the accuracy of GIS approach with route itinerary information elicited from respondents would provide a significantly superior basis for travel cost studies.

Suggested Citation

  • Bhat, Gajanan & Bergstrom, John C., 1996. "Integration Of Geographical Information Systems Based Spatial Analysis In Recreation Demand Analysis," Faculty Series 16649, University of Georgia, Department of Agricultural and Applied Economics.
  • Handle: RePEc:ags:ugeofs:16649
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    References listed on IDEAS

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    1. Anselin, Luc, 1990. "Some robust approaches to testing and estimation in spatial econometrics," Regional Science and Urban Economics, Elsevier, vol. 20(2), pages 141-163, September.
    2. Michael D. Creel & John B. Loomis, 1990. "Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(2), pages 434-441.
    3. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-238, July-Sept.
    4. Wiktor L. Adamowicz & Jerald J. Fletcher & Theodore Graham-Tomasi, 1989. "Functional Form and the Statistical Properties of Welfare Measures," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 414-421.
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