Resource assessment and landscape assessment have always been the focus of tourism evaluation studies. These studies indicate that quantitative method is an effective way to evaluate tourism object, while they only consider the linear relationship between the properties. In fact, as a lack of structural analysis, quantitative methods could hardly make a reliable assessment of the object. In this paper, quantitative methods are used to evaluate the structure of tourism landscape image by making use of structural analysis. This paper uses a questionnaire survey of 291 random tourists in Zhouzhuang (Guzhen) and Wuzhen (Dongzha). The covered topics include tourism landscape image and other demographic characteristics. Then, by using SPSS16.0 as factor analysis and LISREL8.70 to carry out a SEM analysis, the paper proposes a bottom-up method of the tourism landscape image evaluation. It is necessary to evaluate the tourism landscape image on the basis of linear relations and in particular, the coupling between various properties. If there is only linear relationship between properties, the quality of Zhouzhuang (Guzhen) and Wuzhen (Dongzha) tourism landscape images is similar. However, in terms of structural relations, the images of Zhouzhuang (Guzhen) and Wuzhen (Dongzha) tourism landscape are actually at different quality levels, as Zhouzhuang (Guzhen) tourism landscape imagery is superior to that of Wuzhen (Dongzha). In this paper, a tourism landscape image evaluation method based on structural relationship has been proposed. With the tourism landscape image analyzed on the basis of 291 questionnaires, this paper concludes that tourism landscape image evaluation should not only attach importance to a linear relationship between the various properties, but also pay attention to their coupling relations. Quantitative evaluation of properties and their relationship is the appropriate way to comprehensive evaluation of tourism landscape image. To enhance the quality of tourism landscape image, it is necessary to further optimize its structure.
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