测绘学报 ›› 2026, Vol. 55 ›› Issue (3): 381-389.doi: 10.11947/j.AGCS.2026.20250500

• 数智时代地图学新理论与新方法 •    下一篇

人工智能赋能地图科学数智化

王家耀1,2,3(), 陈琳4, 程士源1,2,3(), 王利军1,2,3, 熊思奇1,2,3   

  1. 1.河南大学遥感与空间信息工程学院,地理科学与工程学部,河南 郑州 450046
    2.空间基准全国重点实验室(河南大学),河南 郑州 450046
    3.河南大学河南省时空大数据产业技术研究院,河南 郑州 450046
    4.黄河水利职业技术大学,河南 开封 475004
  • 收稿日期:2025-11-25 修回日期:2026-03-04 出版日期:2026-04-16 发布日期:2026-04-16
  • 通讯作者: 程士源 E-mail:wjy@henu.edu.cn;shiyuan.cheng@henu.edu.cn
  • 作者简介:王家耀(1936—),男,中国工程院院士,主要从事地图学理论、地理信息系统、网格地理信息服务及时空大数据理论、技术与应用研究。E-mail:wjy@henu.edu.cn
  • 基金资助:
    国家自然科学基金(U21A2014)

Artificial intelligence empowering the digital-intelligent transformation of cartographic science

Jiayao WANG1,2,3(), Lin CHEN4, Shiyuan CHENG1,2,3(), Lijun WANG1,2,3, Siqi XIONG1,2,3   

  1. 1.College of Remote Sensing and Geoinformatics Engineering, Faculty of Geographical Science and Engineering, Henan University, Zhengzhou 450046, China
    2.State Key Laboratory of Spatial Datum, Henan University, Zhengzhou 450046, China
    3.Henan Industrial Technology Academy of Spatiotemporal Big Data, Henan University, Zhengzhou 450046, China
    4.Yellow River Conservancy Technical University, Kaifeng 475004, China
  • Received:2025-11-25 Revised:2026-03-04 Online:2026-04-16 Published:2026-04-16
  • Contact: Shiyuan CHENG E-mail:wjy@henu.edu.cn;shiyuan.cheng@henu.edu.cn
  • About author:WANG Jiayao (1936—), male, academician of the Chinese Academy of Engineering, majors in cartographic theory, geographic information systems, gridded geographic information services, and the theories, technologies, and applications of spatio-temporal big data. E-mail: wjy@henu.edu.cn
  • Supported by:
    The National Natural Science Foundation of China(U21A2014)

摘要:

人工智能是国家科技攻关和广泛应用的重要领域,对于抢占科技制高点和提升我国战略竞争优势具有重要意义。本文在系统梳理相关文献的基础上,从人工智能的总体发展态势、技术创新、赋能应用、安全治理及未来前景等方面进行了综合分析。研究认为,人工智能将推动地图科学的数智化转型进入新的发展阶段。具体而言,人工智能与脑科学或神经科学的融合,将加速地图科学数智化基础理论研究的深化;人工智能领域在类脑智能与类脑计算方面的最新进展,为破解地图科学数智化进程中“知识工程”瓶颈问题提供了有力的技术支撑;深度学习与生成式人工智能的发展,为数智化地图制图开辟了更为广阔的应用空间。与此同时,在人工智能技术快速演进与广泛渗透的背景下,地图科学的数智化仍需坚持“以人为本”的理念,强化人与人工智能的深度融合与协同发展。这是一项具有战略性、长期性和可持续性的系统工程,已取得阶段性成果,蕴含了巨大的发展潜力。最后,本文作了简要总结,认为站在新起点上的地图科学必将迎来一个新的里程碑式的大好局面。

关键词: 地图科学, 生成式人工智能, 脑科学, 神经科学, 类脑智能, 深度学习, 数智化

Abstract:

Artificial intelligence (AI) represents a key frontier in national scientific and technological innovation, playing a crucial role in seizing the strategic high ground and strengthening China's competitive advantage in science and technology. Based on a systematic review of relevant literature, this paper conducts a comprehensive analysis of AI from multiple perspectives, including its developmental trends, technological innovation, empowering applications, security governance, and future prospects. The study argues that AI will propel the digital-intelligent transformation of cartographic science into a new stage of development. Specifically, the integration of AI with brain science or neuroscience will accelerate the deepening of fundamental theoretical research in the digital-intelligent transformation of cartographic science; recent advances in brain-inspired intelligence and neuromorphic computing provide strong technical support for addressing the “knowledge engineering” bottleneck in this transformation process; and the rapid progress of deep learning and generative AI opens up broader application spaces for intelligent cartographic production. Meanwhile, under the background of the rapid evolution and extensive penetration of AI technologies, the digital-intelligent development of cartographic science must continue to adhere to a “human-centered” philosophy, strengthening the deep integration and coordinated evolution between humans and AI. This is a strategic, long-term, and sustainable systematic endeavor that has already achieved phased results while containing tremendous developmental potential. In conclusion, the paper posits that cartographic science, standing at a new historical starting point, is poised to embrace a milestone stage of prosperity.

Key words: cartographic science, generative artificial intelligence, brain science, neuroscience, brain-inspired intelligence, deep learning, digital-intelligent transformation

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