Paper
16 October 2009 Dynamic modeling of tourism by stochastic method: a case of the Beijing-Tianjin-Hebei region
Juan Dai, Shihui Zhang, Chongsheng Xue
Author Affiliations +
Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74925D (2009) https://doi.org/10.1117/12.838634
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
As an efficient way to stimulate the growth of economy, tourism is promoted by most counties allover the world, and has become one of the world's largest and fastest-growing industries. Essentially, tourism is a spatiotemporal system, with tourist attractions located in different geographic areas and tourist flows exchanging between different geographic regions. In this paper, we present a dynamic model for the simulation of tourism and tourist's activities in the context of GIS and stochastic method, using a case of the Beijing-Tianjin-Hebei region. The model is developed on stochastic method and multiple geospatial data sources. In the model, the spatiotemporal behavior of tourist on the Earth's Surface is governed by the evolution rules, which are extracted from the researches on tourist's activities and executed via stochastic method and multiple geospatial data. By means of the model, we simulate the tourism in the Beijing-Tianjin- Hebei region, and find that there is good correspondence between the tourist arrivals calculated with the model and those obtained from the tourism statistics. This shows that the animated dynamic modeling of tourism based on geospatial data can be used as an indicator of the tourism in the realistic world, and is also can be embedded in the GIS applications.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan Dai, Shihui Zhang, and Chongsheng Xue "Dynamic modeling of tourism by stochastic method: a case of the Beijing-Tianjin-Hebei region", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74925D (16 October 2009); https://doi.org/10.1117/12.838634
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