| 多源数据融合的中国滑雪场空间活力评价研究 |
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| 引用本文： | 方琰,徐海滨,蒋依依.多源数据融合的中国滑雪场空间活力评价研究[J].地理研究,2023,42(2):389-406. |
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| 作者姓名： | 方琰 徐海滨 蒋依依 |
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| 作者单位： | 1.北京体育大学体育休闲与旅游学院，北京 1000842.北京市冬奥文化与冰雪运动发展研究基地，北京 100084 |
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| 基金项目： | 国家自然科学基金项目(42001255);国家社会科学基金重点项目(21ATY001);北京社会科学基金重点项目(22JCB018) |
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| 摘 要： | 随着北京2022年冬奥会及冬残奥会的成功举办，“三亿人参与冰雪运动”成为现实，有效带动了中国滑雪场建设和发展。后冬奥时代，如何推动中国滑雪场从量升到质变成为重要议题。为有效回答从“量”到“质”转变的问题，需针对滑雪场构建科学合理的综合评价体系。基于空间活力概念，从场所、活动和人的交互联系出发，提出滑雪场吸引力、滑雪活动活跃度和滑雪者体验感3项测度指标，采用层次分析法和熵权法构建复合视角下的滑雪场空间活力评价体系和框架；利用统计、位置、客流、用户评分等多源数据，通过时间序列波动率模型、核密度分析、可达性计算模型和信息熵等方法分析中国滑雪场空间活力特征。结果表明：(1)中国滑雪场吸引力、滑雪活动活跃度、滑雪者体验感空间分异特征明显，分别呈现京冀和广东省“双核”引领、北高南低、东高西低的分布特征；(2)中国滑雪场空间活力呈高值集聚，低值分散的空间分异特征，其中高活力滑雪场主要集中在北京-张家口、吉林省、新疆阿勒泰三大区域，而低活力滑雪场呈全国分散性分布；(3)中国滑雪场平均空间活力位列前五的省/直辖市为北京市、河北省、广东省、吉林省和辽宁省，而江苏省、安徽省、江西省、浙江省和湖北省的滑雪场平...
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| 关 键 词： | 滑雪场 空间活力 多源数据 空间分异 |
| 收稿时间： | 2022-09-06 |
Evaluation of spatial vitality of China's ski resorts based on multi-source data |
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| FANG Yan,XU Haibin,JIANG Yiyi.Evaluation of spatial vitality of China's ski resorts based on multi-source data[J].Geographical Research,2023,42(2):389-406. |
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| Authors: | FANG Yan XU Haibin JIANG Yiyi |
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| Institution: | 1. School of Leisure Sports and Tourism, Beijing Sport University, Beijing 100084, China2. Research Base for the Development of Winter Olympic Culture and Ice and Snow Sports of Beijing, Beijing 100084, China |
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| Abstract: | With the success of the Beijing 2022 Winter Olympics and Winter Paralympics, “300 million people participating in ice and snow sports” has become a reality, which effectively drives the construction and development of China's ski resorts. In the post-Beijing Winter Olympics era, how to promote China's ski resorts from quantity to quality has become an important issue. What is “quality”? It is necessary to build a scientific and reasonable comprehensive evaluation system for ski resorts. Based on the concept of spatial vitality and the interaction between the people, activity and place, we develop a comprehensive system including three evaluations based on AHP weight method and entropy weight method: ski resort attractiveness, activity level of ski activity and skiers' perception. Using multi-source data such as statistical data, location data, passenger flow data and user rating data, the spatial vitality characteristics of China's ski resorts are analyzed through time series volatility model, kernel density analysis, accessibility calculation model and information entropy. Results indicate that: (1) There are obvious regional differences in the distribution of the attractiveness of China's ski resorts, the activity level of ski activity, and skiers' perception, showing a dual-core pattern centered on the Beijing-Tianjin-Hebei region and Guangdong Province, high in the north and low in the south, and high in the east and low in the west, respectively; (2) The spatial vitality of China's ski resorts is characterized by high-value agglomeration and low-value dispersion. Specifically, high spatial vitality ski resorts are mainly concentrated in the three major regions (i.e. Beijing-Zhangjiakou, Jilin Province, and Xinjiang's Altay Prefecture), while low spatial vitality ski resorts are distributed nationwide; (3) The top five provinces/municipalities in terms of average spatial vitality of ski resorts in China are Beijing, Hebei, Guangdong, Jilin and Liaoning, while the average spatial vitality of ski resorts in Jiangsu, Anhui, Jiangxi, Guizhou and Qinghai provinces are included in the weakest type. Besides, overall improvement strategies for the spatial vitality of ski resorts in China are proposed as well as the corresponding optimization paths for different regions, which could provide basis and guidance for promoting the high-quality development of the ski industry in the post-Winter Olympics era. |
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| Keywords: | ski resort spatial vitality big data differential features |
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