Title :
Spatial structure of tourist attractions in Nanjing, China — Based on statistical analysis of 317 tourist attractions
Author :
Ding, Lei ; Wang, Yu ; Zhang, Fangyi ; Wu, Xiaogen ; Tang, Shu
Author_Institution :
Sch. of Geographic & Oceaographic Sci., Nanjing Univ., Nanjing, China
Abstract :
Based on the researches carried out by Nanjing University Subject Group in Nanjing Tourist Resources Census (2002-2003), this paper selected 317 samples of tourist attractions that have relatively high quality resources, high development potential and high representativeness in reflecting the direction of tourism development in Nanjing, China, measured the Euclidean distance between 317 tourist attractions and their nearest scenic spots using ArcGIS 9.3, analyzed the density of 317 tourist attractions, and meanwhile conducted quantitative analysis with mathematical methods for geography, and thus analyze the factors that influence the spatial structure distribution of Nanjing tourist attractions. The paper has found that the spatial distribution of Nanjing tourist attractions is cohesive, with low regional distribution equilibrium, large district (county) difference; the areas with high-density tourist attractions include Xuanwu District, Drum Tower District, Qinhuai District and Baixia District, while Jiangning District, Luhe District and Pukou District does not have high-density tourist attractions.
Keywords :
geographic information systems; statistical analysis; travel industry; ArcGIS 9.3; Baixia District; Drum Tower District; Euclidean distance; Jiangning District; Luhe District; Pukou District; Qinhuai District; Xuanwu District; geography; regional distribution equilibrium; spatial structure distribution; statistical analysis; tourism development; tourist attraction; Cities and towns; Cultural differences; Economics; Indexes; Poles and towers; Rivers; ArcGIS; Nanjing; mathematical methods for geography; tourism spatial structure;
Conference_Titel :
Geoinformatics, 2011 19th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-849-5
DOI :
10.1109/GeoInformatics.2011.5980771