Hakka traditional villages are an important segment of traditional Chinese villages. Analysis of the process of selection of a Hakka site can deepen our knowledge of Hakka culture. In this study, we selected Hakka traditional villages in Fujian, Guangdong, and Jiangxi provinces as research sites. We extracted basic data for these traditional villages using geographic information system coordinates, identified several potential influencing factors, and analyzed correlations among the factors using the R language. Finally, the degree of influence of each factor on the site selection of Hakka traditional villages in the study area was determined using a geographic probe to confirm the dominant factors. The results showed that Hakka traditional villages in Fujian, Guangdong, and Jiangxi had an overall significant clustered distribution. Distance to water, elevation, and vegetation richness were the dominant factors influencing the location of Hakka villages, while the interaction of multiple factors had a facilitating effect on the location of Hakka village foundations. This study utilized the observed distribution of Hakka villages in different regions and the differences between them resulting from the interaction of influencing factors, combined with data analysis, to provide a theoretical basis for the development and protection of Hakka traditional villages.
Ancient villages are a unique landscape of cultural heritage with both tangible and intangible culture, which provide rich ecosystem services for human beings. Assessment of society’s perceptions on cultural heritage landscapes can improve the integration of cultural heritage values into decision-making processes that affect landscapes, thereby contributing to maximizing the benefits people receive from cultural ecosystem services. Based on this premise, a new sense-based hierarchical assessment framework for a cultural landscape of ancient villages in China from the perspectives of experts and the public was developed in this study. Field research was conducted by the experts to preliminarily extract the evaluation indicators by identifying and refining the characteristics of the landscape perception units based on the classification of village’s landscape resources. The public indicators as supplements were determined by the semantic and social networks generated with ROSTCM tool post-processing, which followed crawling public comments on the tourism platforms with Python. The findings indicated that visual stimulation (57.36%) is the strongest, while touch perception is the weakest (3.56%). The proportion of hearing, smell, and taste was 21.52%, 12.05%, and 5.53%, respectively. Furthermore, people consider variety, historicity, culture, and localism as the core themes of perception in their landscape experiences. The value and usefulness of the sensory experiences for cultural landscape assessment and for decision-making in the context of cultural ecosystem services are discussed.
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