• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1047-1056
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• 2016

This study aims to provide managerial implications for provincial parks through an analysis on visitors' characteristics and motivational factors. The information was collected by surveying 290 visitors. The survey questionnaire consisted of questions regarding visitors' socioeconomic characteristics, characteristics of their travel behavior, visitors' motivation to visit the park, and the degree of satisfaction derived from visiting the park. Results show that most respondents appeared not to collect any information on the park prior to their visit. It was also seen that most visitors do not visit other tourist sites nearby, and are not aware of the Gochang UNESCO biosphere, which indicates that Gochang-gun, which is responsible for park management, needs to make more efforts to promote the park. A factor analysis on the visitors' motivation to visit the park extracted three factors to visit the Seonunsan Provincial Park: 'to hike,' 'to experience and observe nature,' i.e., nature learning field trip and camping, and 'to build and nurture bonding with family and friends.' To examine the effect of these various motivational factors had on the visitors' satisfaction level upon visiting the park, we conducted a multiple regression analysis with the three extracted factors to visit the park and the respondents' socioeconomic characteristics as independent variables, and the degree of recommendation of visiting the park as a dependent variable. The result shows found that, of the three travel factors, only the 'hiking' factor statistically significantly affected the degree of recommendation of visiting the park. This result suggests that the Seonunsan Provincial Park only satisfied hikers and failed to meet the demands for nature experience and observation. It is therefore suggested that the park managers develop new experience-based tourism programs, such as guided tours conducted by professional eco-interpreters.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.61-73
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• 2021

This study aimed to identify the landscape perception and landscape characteristics of users by utilizing SNS data generated by their experiences. Therefore, how to recognize the main places and scenery appearing on the island, and what are the characteristics of the main scenery were analyzed using online text data and photo data. Text data are text mining and network structural analysis, while photographic data are landscape identification models and color analysis. As a result of the study, First, as a result of frequency analysis of Bakji·Banwol-do topics, we were able to derive keywords for local landscapes such as 'Purple Bridge', 'Doori Village', and location, behavior, and landscape images by analyzing them simultaneously. Second, the network structure analysis showed that the connection between key and undrawn keywords could be more specifically analyzed, indicating that creating landscapes using colors is affecting regional activation. Third, after analyzing the landscape identification model, it was found that artificial elements would be excluded to create preferred landscapes using the main targets of "Purple Bridge" and "Doori Village", and that it would be effective to set a view point of the sea and sky. Fourth, Bakji·Banwol-do were the first islands to be created under the theme of color, and the colors used in artificial facilities were similar to the surrounding environment, and were harmonized with contrasting lighting and saturation values. This study used online data uploaded directly by visitors in the landscape field to identify users' perceptions and objects of the landscape. Furthermore, the use of both text and photographic data to identify landscape recognition and characteristics is significant in that they can specifically identify which landscape and resources they prefer and perceive. In addition, the use of quantitative big data analysis and qualitative landscape identification models in identifying visitors' perceptions of local landscapes will help them understand the landscape more specifically through discussions based on results.