JOURNAL OF NATURAL RESOURCES ›› 2012, Vol. 27 ›› Issue (1): 122-131.doi: 10.11849/zrzyxb.2012.01.013

• Resources Evaluation • Previous Articles     Next Articles

Grade Classification of Tourism Affected Zone and Analysis of Relevant Indicators

GUO Xiu-ling, SHANGGUAN Tie-liang   

  1. College of Environment and Resources, Shanxi University, Taiyuan 030006, China
  • Received:2011-03-15 Revised:2011-06-25 Online:2012-01-20 Published:2012-01-20

Abstract: The Luya Mountain Nature Reserve, a well-known tourism spots, is in the northern part of Luliang Mountains in Shanxi Province. It was designated as the national AAAA level scenic area in 2010. The mountain has abundant species, various vegetation types and highly diversified habitats. This thesis selected one of the typical tourist attractions in Luya Mountain Nature Reserve, namely Bingkouwa to study the impacts of tourism on forest vegetations through the quantitative ecological methods including plant classification, principal component analysis and correlation analysis. The major studying results are as follows: 1) The TWINSPAN classification divided the area into six impact zones by the extent of tourism influences, reflecting the alternations in spatial pattern by tourism activities, where the trails were used as the axis. 2) The correlation analysis revealed significant relationships among 3 out of 12 pairs of tourism indicators, namely remove stumps influence coefficient vs. trail distance, waste impact coefficient vs. remove stumps influence coefficient, and waste impact coefficient vs. trail distance. Meanwhile the H' and slope were found well correlated. 3) The PCA analysis of 12 impact indicators showed five principal components which were closely related with seven impact indicators, accounting for 81.88% of the comprehensive information. The results of tourism affected zone level division by seven tourism impact indicators and 12 tourism impact indicators were the same. This simplifies the selection for tourism impact indicators for application purpose.

Key words: tourism geography, tourism impact indicators, principal component analysis, tourism impact level zone, TWINSPAN classification

CLC Number: 

  • X36