| 摘要: |
| 大数据为风景园林规划方法的创新提供了技术支持，为城市公园游憩使用和规划应对带来了新的机遇。首先，对城市公园游憩使用研究中有关大数据的应用类型进行梳理和分类；其次，从公园游憩使用、可达性、服务范围和规划应对4个方面分析城市公园游憩使用的研究进展；最后对城市公园游憩使用研究方法进行分类总结。在游憩使用方面，大数据可通过游人分布特征判定公园游憩使用情况；在可达性方面，大数据用于精细化分析不同尺度的城市公园的可达性，促进公园规划的合理性；在服务范围方面，大数据可用于城市公园服务范围的识别、基于流动进行衰退研究，提高公园游憩规划的公平性；在规划应对方面，可通过研究游憩使用的影响因素进一步指导规划。同时对大数据在游憩使用研究方面的未来发展趋势做出判断，以期为大数据在公园游憩规划中得以更好的应用提供合理思路。 |
| 关键词: 大数据 游憩使用 可达性 服务范围 规划应对 |
| DOI：10.14085/j.fjyl.2021.01.0010.07 |
| 分类号:TU984 |
| 基金项目:国家自然科学基金（编号 51908036，31670704）；北京市自然科学基金 ( 编号 8194071）；教育部人文社科基金项目 ( 编号 19YJC760042）；中央高校基本科研业务费专项资金资助（编号 BLX201808）；首都区域空间规划研究北京市重点实验室开放课题资助（编号 CLAB202006） |
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| Research Progress of Urban Park Recreation Use and Planning Strategies Based on Multi-source Big Data |
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LI Fangzheng1, ZONG Pengge2
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1.Beijing Forestry University;2.Chinese Academy of Forestry
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| Abstract: |
| Big data technology provides technical support for the innovation of landscape architecture planning methods, and brings new opportunities for urban park recreation use and planning response. This paper first sorts out and classifies the application types of big data in the study of urban park recreation use, and then analyzes the use of urban park recreation from four aspects: park recreation use, accessibility, service area, and planning response. Finally, the research methods of urban park recreation are classified and summarized. For example, in the use of recreation, big data can be used to determine the use of parks based on the distribution characteristics of visitors; in terms of accessibility, big data can be used to analyze the accessibility of urban parks at different scales to promote the rationality of park planning; in terms of area, big data can be used for research on the determination, flow and decline of urban park services to improve the fairness of park recreation planning; furthermore, it can be used to guide planning and response through research on factors affecting recreation use. On this basis, this paper also speculates on the development trend of big future data in the use of recreation, in order to provide reasonable ideas for the better application of big data in park recreation planning. |
| Key words: big data recreational use accessibility service area planning response |
