Big data has garnered substantial attention from urban researchers and policymakers, offering new perspectives for assessing the urban environment and supplementing traditional datasets. The increasing number of studies analyzing urban green space (UGS) topics using multiple sources of big data necessitates an in-depth review to guide future research. Existing reviews often narrow their focus to a single type of big data and offer limited coverage of UGS topics. In contrast, this review comprehensively synthesizes 445 UGS articles using three widely used types of big data, aiming to identify ongoing research trends and current gaps to inform future studies in this field. Based on bibliometric and thematic analyses, we identified five key topics: UGS assessment, human psycho-social responses to UGS, ecosystem services of UGS, UGS benefits, and UGS management tools. Research observations are summarized from a procedural perspective. Issues include the impacts of inherent big data limitations, challenges in using different data sources, and difficulties in explaining conclusions. Opportunities span from exploring new topics, developing methods to reduce biases, and applying advanced computational approaches. This review contributes to the current knowledge of UGS research using big data by synthesizing various types of big data, analyzing methodologies from new perspectives, and summarizing observations, issues and opportunities across multiple dimensions. It provides a reference for future UGS studies that apply big data.

中文翻译：

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大数据在城市绿地研究中的应用综述


大数据引起了城市研究人员和政策制定者的极大关注，为评估城市环境和补充传统数据集提供了新的视角。使用多个大数据来源分析城市绿地 （UGS） 主题的研究越来越多，因此有必要进行深入审查以指导未来的研究。现有的评论通常会将关注点缩小到单一类型的大数据，并且对 UGS 主题的覆盖范围有限。相比之下，本综述使用三种广泛使用的大数据类型全面综合了 445 篇 UGS 文章，旨在确定正在进行的研究趋势和当前差距，为该领域的未来研究提供信息。基于文献计量学和主题分析，我们确定了五个关键主题：UGS 评估、人类对 UGS 的心理社会反应、UGS 的生态系统服务、UGS 的好处和 UGS 管理工具。研究观察结果从程序角度进行总结。问题包括固有的大数据限制的影响、使用不同数据源的挑战以及解释结论的困难。机会包括探索新主题、开发减少偏见的方法以及应用高级计算方法。本文通过综合各种类型的大数据，从新的角度分析方法，以及从多个维度总结观察结果、问题和机会，为当前使用大数据的 UGS 研究知识做出了贡献。它为未来应用大数据的 UGS 研究提供了参考。