摘要
全面梳理绿地研究中大数据的应用情况,为深入开展绿地系统的科学研究提供经验与技术支持。借助CiteSpace知识图谱软件,对Web of Science数据库近20年应用大数据中绿地研究的文献进行文献计量和图谱分析,梳理绿地研究中大数据类型及研究热点,总结其分析方法和研究特点,探讨未来研究方向。结果显示,绿地研究中大数据分为3大类9小类,数据有效反映了绿地游人行为、游人体验以及城市空间信息。基于这些数据信息重点开展绿地使用及管理、绿地布局、绿地健康作用、绿地生态系统文化服务以及绿地景观偏好等研究,结果表明大数据的引入有效推动了绿地多维量化研究,促进了多学科交叉融合研究,为城市绿地规划建设提供了更为广泛的实践指导。
Comprehensively clarifying green space research based on big data will provide experience and technical support for a more systematic and in-depth study.This paper carried out bibliometrics and graph analysis of WOS(Web of Science)literature in the recent 20 years by using CiteSpace and traditional literature analysis methods to sort out signifi cant data types and research hotspots in green space research,summarize data analysis methods and research characteristics in green space research and ex-plore future research directions.The results showed that:(1)Big data commonly applied in green space research can be divided into three categories and nine sub-categories.These data effectively quantify visitors’behavior,experience,and urban space attri-butes.Based on the information,researchers have done green space use and management research,green space layout research,the health effects of green space research,the cultural ecosystem service of green space research,and the green space landscape preference research;(2)The application of big data effectively promotes quantitative analysis on green space,promotes interdis-ciplinary research,and provides more extensive practical guidance for urban green space planning and construction.
作者
黄宇飞
曾昱璇
孙迪
章莉
陈艳
HUANG Yufei;ZENG Yuxuan;SUN Di;ZHANG Li;CHEN Yan(College of Horticulture and Forestry Sciences,Huazhong Agricultural University,Wuhan,Hubei,China,430070;China UrbanConstruction Desig n&Research Institute CO.,LTD.,Beijing,C hina,100120)
出处
《园林》
2023年第4期76-85,共10页
Landscape Architecture Academic Journal
基金
国家重点研发计划“乡村生态景观营造关键技术研究”专项“乡村生态景观资源特征指标体系研究”(编号:2019YFD1100401)。
关键词
大数据
绿地
可视化软件
游人行为
游人体验
研究进展
big data
green space
CiteSpace
visitor behavior
visitor experience
research progress
