중국 하북성 만리장성(萬⾥⾧城) 유적 관광지의 공간활력 평가 - 당산시(唐⼭市) 3개 관광지구를 중심으로 - = Spatial Vitality Evaluation of the Great Wall Relics and Tourist Attractions in Hebei Province, China - Focusing on 3 Tourist Zones in Tangshan City -

국문 초록 (Abstract)

본 연구는 중국 상산시 청산관 백양욕 희봉구 관광지구 등 총 15개 지구를 대상으로 만리장성 유적지의 공간활력에 영향을 미치는 요인을 분석하고 공간활력 평가방법을 수립하여 관광지구 개선에 기초자료를 제공하는 것에 목적이 있다 연구방법으로는 첫째 여가활동 관찰기법(SOPARC)을 활용해 탐방객의 활동특성을 관찰·분석하였다. 동시에 인간·시간·공간의 3차원적 접근방식을 통해 ArcGIS 핵밀도 추정 알고리즘(KDE)을 이용하여 만리장성 유적 관광지의 활력특성을 분석하였다. 둘째, 탐방객을 대상으로 공간 편의시설 동선 건축 및 자연경관, 역사 문화, 문화 활동 등 15개 항목에 대해 5점 리커트척도로 설문조사를 수행하였다. 셋째, 전문가 대상 델파이법과 계층분석법(AHP)을 통해 공간지표를 선정하고 지표의 가중치를 설정하여 대상지의 공간활력을 평가하고 활력도 제고를 위한 지침을 마련하였다. 연구결과는 첫째, 만리장성 유적 관광지의 공간 이용자 중 젊은 층이 절대적인 비율을 차지하였다. 또한 접근성이 좋고 시설이 잘 갖추어져 공간의 규모가 적절하고 자연경관과 문화경관이 우수하며, 문화활동이 다양하고 활발한 관광지일수록 이용자 간의 혼합도가 높았다. 공간기능이 다양한 관광지는 공간활동의 다양성도 더 높았다. 둘째, 관광지의 활동 피크 시간대는 주로 오전 10시에서 12시, 오후 3시에서 5시 사이로 나타났으며, 미기후가 쾌적한 관광지에서는 피크 시간대의 활동빈도가 더 높았다. 시설이 잘 갖추어지고 관리가 잘된 공간일수록 활동변동이 적었으며, 경관이 아름답고 문화환경이 우수한 공간에서는 활력이 오래 지속되었다. 셋째, 주변 인구밀도가 높고 역사요소가 잘 보존되며, 유지관리가 우수한 관광지일수록 공간 활동빈도가 높았다. 또한 특색 있는 지역산업이 발전하고 상업활동이 활발하며, 공간의 기능이 다양한 경우 공간집적도가 더 높아진다는 결과를 확인하였다. 넷째, 사례연구 결과와 만리장성 유적 관광지의 특성을 결합하여 자연환경 산업공간 기능 시설 서비스 문화 및 경관 등 4가지 주요 영향요인을 도출하였다. 델파이법을 통해 1개의 목표층, 4개의 1차 지표, 9개의 2차지표 및 29개의 3차 지표로 구성된 만리장성 유적 관광지의 공간활력 평가모델을 수립하였다. 이를 토대로 계층 분석법을 통해 공간활력 평가지표 시스템의 가중치를 결정하였으며, 가중치는 문화 및 경관 활력(45.12%), 자연환경 활력(26.09%), 산업공간 기능 활력(16.89%), 시설 서비스 활력(11.9%) 순으로 나타났다. 이는 관광지의 공간활력을 조성하는 데 있어 문화와 자연경관이 가장 중요하다는 것을 의미한다. 다섯째, 연구를 통해 도출된 평가지표와 대상지의 현황을 종합하여 만리장성 유적 관광지의 공간 활력 5단계 평가등급을 정의하였다. 각 요인 항목에 점수를 부여해 최종 활력값을 도출할 수 있었으며, 이 값은 공간의 활력정도를 정량적으로 설명할 수 있는 기반을 마련해 주었다. 실제 검증을 통해 구축된 평가 시스템과 5단계 평가등급은 신뢰성이 높았으며, 만리장성 유적지의 공간활력 평가를 위한 새로운 패러다임을 제공했음을 확인하였다.

다국어 초록 (Multilingual Abstract)

This study aims to analyze the factors influencing the spatial vitality of the Great Wall heritage sites, focusing on 15 tourist areas including Qing Shanguan, Baiyangyue, and Xihong District in Shangshan City, China. It seeks to establish a method for assessing spatial vitality and provide foundational data for improving these tourist areas. The research methodology includes three main approaches. First, the SOPARC (System for Observing Play and Recreation in Communities) observation technique was utilized to analyze visitor activity characteristics. Concurrently, the ArcGIS kernel density estimation algorithm was applied to examine the vitality characteristics of the Great Wall heritage tourism sites through a three-dimensional approach involving human, time, and space. Second, a survey was conducted with visitors using a 5-point Likert scale, encompassing 15questions related to space, amenities, movement patterns, architecture and natural scenery, historical culture, and cultural activities. Third, experts were engaged through the Delphi hierarchical analysis method to select spatial indicators, and the AHP (Analytic Hierarchy Process)was employed to set the weights of these indicators, assessing the spatial vitality of the sites and establishing guidelines for enhancing their vitality. The results indicate that, first, a significant proportion of users at the Great Wall heritage tourism sites are young individuals. Furthermore, sites with good accessibility, well-equipped facilities, pleasant spatial scales, excellent natural scenery, and rich cultural atmospheres tend to have higher user diversity. Tourist areas with diverse spatial functions exhibited greater variability in spatial activities. Second, the peak activity times at tourist sites were primarily between 10AM to 12PM and 3PM to 5PM, with pleasant microclimates correlating with higher activity frequencies during peak hours. Spaces that are well-equipped and well-managed showed the least variability in activities, while areas with beautiful scenery and rich cultural atmospheres maintained sustained vitality. Third, tourist sites with high surrounding population density, a favorable historical atmosphere, and excellent maintenance exhibited higher frequencies of spatial activities. Additionally, it was confirmed that areas with distinctive local industry development, abundant commercial activities, and diverse spatial functions had higher spatial aggregation. Fourth, by integrating case study results with the characteristics of the heritage tourism sites, four influential factors were identified: natural environment, industrial spatial functions, facility services, and culture and scenery. Through three rounds of expert Delphi method, a spatial vitality assessment model for the Great Wall heritage tourism sites was established, consisting of one objective layer, four primary indicators, nine secondary indicators, and 29tertiary indicators. Based on this, the weights of the assessment index system for the spatial vitality of the Great Wall heritage sites were determined using hierarchical analysis. The weights were as follows: cultural and scenic vitality (45.12%) > natural environmental vitality (26.09%) > industrial spatial function vitality (16.89%) > facility service vitality (11.9%), indicating the paramount importance of culture and natural scenery in fostering spatial vitality in tourist areas. Fifth, by synthesizing the derived assessment indicators with the current status of the sites, a five-level spatial vitality evaluation system for the Great Wall heritage tourism sites was defined. By assigning scores to each factor in the evaluation system, a final vitality value was obtained, quantitatively describing the degree of spatial vitality. The evaluation system established through practical validation and the five-level scoring criteria w...

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