首页|基于多源大数据的城市旅游目的地吸引力评价研究——以武汉市为例

基于多源大数据的城市旅游目的地吸引力评价研究——以武汉市为例

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  • NETL
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目的地吸引力是旅游者选择前往某地旅游的重要因素,对目的地旅游业的发展至关重要.已有研究虽然在特定领域内取得了丰富的成果,但在数据来源的多样性和全面性、评价方法的科学性和高效性等方面仍存在需改进的空间.本文以武汉市为研究对象,构建城市和景区两个层面的旅游吸引力评价指标体系,融合旅游网站数据、兴趣点数据、街景图像数据等多源数据,采用两步移动搜寻法和图像语义分割法对景区吸引力评价指标进行计算;并采用熵权-TOPSIS方法定量分析武汉市及其各级旅游景区的吸引力.结果表明:尽管武汉市的旅游资源丰富,其总体旅游吸引力水平仍落后于其他热门旅游城市,如西安、成都等;旅游景区吸引力与景区等级正相关,高等级景区具有更高的吸引力;位于中心城区的景区,其旅游吸引力得分明显高于郊区.研究成果可为武汉市及类似城市的旅游资源优化配置和旅游政策制定提供数据支持依据.
Evaluation on urban tourism destination attractiveness based on multi-source big data: A case study of Wuhan
This study aims to develop a comprehensive dual-level tourism attraction evaluation index system, distinguishing between urban areas and scenic sites. This enables the assessment and comparison of Wuhan's appeal relative to other prominent tourist cities. The primary goal is to provide a robust framework for precisely gauging the attractiveness of various tourist destinations within Wuhan and benchmarking them against well-known tourist cities such as Xi'an and Chengdu. To achieve these objectives, the study employs a sophisticated methodology integrating various multi-source datasets, including statistical yearbooks, tourism-specific websites, point of interest (POI) data, population density grids, and street view imagery. This ensure a rich, data-driven foundation for analysis. The evaluation model utilizes the two-step floating catchment area method and advanced deep learning algorithms to calculate precise indices for evaluating scenic attractions. This approach considers crucial factors such as the accessibility of tourism facilities and the quality of the surrounding environment at scenic locations. Additionally, an entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) method is implemented to conduct a detailed quantitative analysis of Wuhan's tourism attractiveness and its various scenic spots. The analysis reveals that despite its extensive tourism resources, Wuhan's overall attractiveness as a tourist destination lags behind other major tourist hubs like Xi'an and Chengdu. The evaluation covered 53 tourist attractions in Wuhan, culminating in an average attractiveness score of 0.441. A significant finding is the positive correlation between the ratings of tourist sites and their attractiveness, indicating that sites with higher ratings inherently possess greater appeal. The variability in attractiveness scores across different levels shows consistent patterns, suggesting a stable yet improvable landscape for Wuhan's tourism. Notably, tourist attractions located in the central urban areas significantly outshine those in suburban areas, mainly due to better public tourism infrastructure and higher environmental quality. The findings underscore the need for strategic enhancements in Wuhan's tourism offerings, particularly in under performing areas. The empirical evidence supports targeted improvements in public tourism facilities and environmental management, especially in suburban scenic spots, to elevate their attractiveness. By providing a data-backed basis for optimizing tourism resources and strategically formulating tourism policies, this research significantly contributes to enhancing Wuhan's stature as a tourist destination. Additionally, the methodologies and findings from this study can serve as a blueprint for similar urban centers aiming to refine their tourist appeal and competitiveness on a global scale.

tourist destinationattraction evaluationtwo-step floating catchment area methoddeep learningmulti-source big dataspatiotemporal data

李婧璇、禹文豪、黄雅雅、吴啸

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中国地质大学(武汉)地理与信息工程学院,武汉 430074

武汉市规划研究院,武汉 430074

旅游目的地 吸引力评价 两步移动搜寻法 深度学习 多源大数据 时空数据

国家自然科学基金面上项目国家自然科学基金面上项目湖北省自然科学基金项目中国地质大学(武汉)中央高校基本科研业务费专项资金项目

42371446420714422024AFD412CUG170640

2024

10.20117/j.jsti.202403009

地理信息世界
中国地理信息产业协会 黑龙江测绘地理信息局

地理信息世界

CSTPCD
影响因子：0.826
ISSN：1672-1586
年,卷(期)：2024.31(3)
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