Review on data-informed planning for underground space

Abstract

Urban underground space (UUS) development, guided by prudent planning, has emerged as a vital solution to the increasingly complex issues of urban built environments globally. Driven by the growing needs for human-centric urban design, low-carbon development, enhanced urban resilience, and alignment with sustainable development goals, UUS planning is rapidly shifting from experience-based approaches to evidence-based and data-driven methodologies. Yet, the broader landscape of this research field remains ambiguous, with the characteristics and future trajectories of such emerging planning technologies still to be clearly delineated. To this end, this systematic review delves into the burgeoning field of data-informed planning technologies for underground space (DIPTUS), examining how data-driven methods are revolutionizing the planning, design, and management of underground environments. Through a comprehensive bibliometric analysis of 134 articles published from 2014 to 2024, we identified key trends and mapped research themes within DIPTUS. Our narrative synthesis evaluated DIPTUS advancements across three dimensions: sensing and measurement, pattern and model, and planning and governance. The results indicate that DIPTUS exploits diverse data streams to quantitatively analyze UUS development. Utilizing advanced analytical tools such as spatial statistics, machine learning, and causal inference, these technologies uncover utilization patterns and planning optimization strategies. The review also underscores the increasing integration of planning and governance within DIPTUS, merging resource evaluation and demand forecasting, layout planning optimization, development benefits and spatial performance evaluation into a cohesive framework. Enhancements in 3D cadastral systems, innovative management models, and digital twin technologies further bolster this integrated approach. Despite significant strides, challenges in data integration, model complexity, and practical application persist. Lastly, we proposed a visionary framework to address these issues through interdisciplinary research and robust model development, aiming to fully harness DIPTUS’s transformative potential for sustainable, resilient, and human-centered urban environments.

Keywords

Underground space / Spatial planning / Multisource big data / Bibliometric analysis

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Fang-Le Peng: Writing - original draft, Project administration, Funding acquisition, Conceptualization. Wei-Xi Wang: Writing - original draft, Visualization, Resources, Data curation. Yong-Kang Qiao: Validation, Resources, Investigation, Data curation. Chen-Xiao Ma: Visualization, Resources, Formal analysis. Yun-Hao Dong: Writing - review & editing, Visualization, Validation, Software, Resources, Methodology, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

Dr. Fang-Le Peng is an editorial board member for Underground Space and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant Nos. 42071251 and 42301289).

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