Multimodal Spatio-Temporal Data Visualization Technologies for Contemporary Urban Landscape Architecture: A Review and Prospect in the Context of Smart Cities

Xiao Han, Zhe Li (), Hao Cao and Bingyu Hou
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Xiao Han: School of Architecture, Southeast University, Nanjing 210096, China
Zhe Li: School of Architecture, Southeast University, Nanjing 210096, China
Hao Cao: School of Architecture, Southeast University, Nanjing 210096, China
Bingyu Hou: School of Architecture, Southeast University, Nanjing 210096, China

Land, 2025, vol. 14, issue 5, 1-35

Abstract: The development of smart cities provides a vital foundation for the intelligent advancement of landscape architecture and engineering technologies, where multimodal spatio-temporal data visualization plays a key role. This study conducts a scoping review to explore the advancements in multimodal spatio-temporal data visualization within landscape architecture and to assess their potential to drive urban intelligence and sustainable development. This review analyzes publication trends, data types, application scenarios, and identifies research challenges and future directions. The results indicate that the complementary integration of basic data and sensing data has established relatively mature technical pathways for clustering, correlation analysis, process simulation, and trend forecasting. Future research should prioritize real-time data presentation, efficient platform integration, intelligent processing and scientific mapping of massive information, and interdisciplinary research and practical applications. This study lays a foundation for the development of intelligent landscape architecture, highlighting promising prospects for technological advancement.

Keywords: multimodal spatio-temporal data; visualization technology; landscape architecture; scoping review; smart city (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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