On the development of surveying and mapping in the era of artificial intelligence

doi:10.11947/j.AGCS.2025.20250438

Abstract

Abstract:

Against the backdrop of rapid advances in artificial intelligence and the surging demand for spatio-temporal information applications, spatio-temporal intelligence, a new discipline integrating surveying, navigation, remote sensing, and artificial intelligence (AI) has emerged. Leveraging intelligent sensors for communication, navigation, and remote sensing, cloud computing, and AI technologies, it enables intelligent perception, cognition, and decision support for natural and human activities, with a focus on promoting sustainable development. Surveying and mapping plays a core supporting role, requiring the construction of a four-dimensional spatio-temporal reference frame to ensure the accuracy of spatio-temporal information, the development of “fast, accurate, and agile” intelligent processing technologies to address massive data challenges, and the enhancement of spatio-temporal information comprehension efficiency through multi-dimensional dynamic visualization. The “National One Map” project serves as a typical paradigm for the practical implementation of spatio-temporal intelligence theory. Relying on the Oriental Smart Eye constellation and Tianditu (national geospatial information public service platform), it promotes the unified application of spatio-temporal information in government affairs, public services, and commercial sectors, achieving dynamic updates and intelligent analysis. In the future, spatio-temporal intelligence will deepen its theoretical system, improve the theories of spatio-temporal reference frame construction and data processing, integrate cutting-edge AI technologies, facilitate global spatio-temporal information sharing, provide more precise decision support for urban governance, environmental protection, and other fields, and contribute to the construction of a community with a shared future for mankind.

Key words: spatio-temporal intelligence, surveying and mapping, spatio-temporal reference frame, spatio-temporal data processing, spatio-temporal information visualization, “National One Map”

CLC Number:

Deren LI, Mi WANG, Wenbin SHEN, Qingyun DU, Shuo WANG. On the development of surveying and mapping in the era of artificial intelligence[J]. Acta Geodaetica et Cartographica Sinica, 2025, 54(12): 2107-2115.

Figures/Tables 4

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评价维度	考量因子	Mesh模型	单体化模型	LOD1.3级模型	属性设色三维模型
美观性	可视化效果	★★★★	★★★★☆	★★	★★★
易用性	数据量大小、属性挂接、平台支持	★★	★★★★	★★★★	★★★★
应用性	支撑应用场景是否广泛	★★★★	★★★★	★★★	★★★☆
经济性	自动化程度、成本高低	★★★	☆	★★★★	★★★★★
易维护性	数据更新难易程度	☆	★★★☆	★★★★★	★★★★★
生产成本/（元/km²）		8000~10 000	30 000~40 000	3000	1500