Python과 QGIS를 활용한 제주 올레길 이용객 행태분석 : 코로나19 전·후를 중심으로

Abstract

The purpose of this study is to identify the course usage behavior of Jeju Olle Trail users before and after COVID-19. To achieve the purpose, data was collected using Python and analyzed on the basis of QGIS. 24,093 course-related text data and 9,409 location data, such as destination restaurants, were collected for the analysis. As a result, the most visited course was course 1 in text-mining, and course 7-1 in location data. In detail, the visitors showed a preference for outdoor activities, including visiting scenic spots and street markets, rather than indoor activities. Course 1, which was derived the most frequently in the text, was found to be a behavior for the purpose of enjoying nature such as tourist attractions or landscape photos. Next, the 7-1 course, which had the highest frequency on the location information map, is a course where people can enjoy the natural scenery while walking lightly, and where accommodations (hotels, guesthouses, motels, etc.) and restaurants or exotic cafes are located. Comparing the usage behavior results between pre-and post-COVID-19, the restaurant name and guest house, which are indoor spaces, showed high frequency in the pre-COVID-19 situation. On the other hand, the frequency of 'Jeju Olle Market', which allows people to eat outdoors and take away, has soared in the post-COVID-19 situation. Also, there was a noticeable change in the behavior of accommodation for 'Resort', where only a few people, such as family or friends, can stay.