测绘通报 ›› 2026, Vol. 0 ›› Issue (4): 11-19.doi: 10.13474/j.cnki.11-2246.2026.0402

• 测绘地理信息赋能低空经济 • 上一篇    下一篇

时空智能驱动低空技术的测绘新质发展

刘春1, 艾克然木·艾克拜尔2, 沈雨清1, 吴杭彬1   

  1. 1. 同济大学测绘与地理信息学院, 上海 200092;
    2. 同济大学电子与信息工程学院, 上海 200092
  • 收稿日期:2025-11-17 发布日期:2026-05-12
  • 作者简介:刘春(1973—),男,博士,教授,主要研究方向为激光雷达遥感与低空技术与工程。E-mail:liuchun@tongji.edu.cn
  • 基金资助:
    国家自然科学基金重点项目(42130106)

Spatio-temporal intelligence-driven new-quality development of low-altitude surveying and mapping

LIU Chun1, Akram Akbar2, SHEN Yuqing1, WU Hangbin1   

  1. 1. College of Surveying and Geomatics, Tongji University, Shanghai 200092, China;
    2. College of Electronic and Information Engineering, Tongji University, Shanghai 200092, China
  • Received:2025-11-17 Published:2026-05-12

摘要: 低空经济是我国战略性新兴产业集群与新兴领域国家安全能力建设的交汇点,其高质量发展亟需测绘地理信息提供精准、动态的时空智能底座支撑。本文围绕“空域—航路网—起降点—无人系统”4要素协同架构,深入剖析测绘地理信息在低空人地系统构建、数字孪生方法论及多模态智能感知体系中的技术演进;系统梳理时空智能的技术演进路径及其在空域规划、运行管控等关键环节的赋能机制,结合低空物流、应急救援等典型场景,分析阐释时空智能技术的支撑效能与面临的挑战;提出“通信—感知—计算—智能”一体化闭环、数字基底规范体系及测绘即服务生态平台等未来发展路径,驱动测绘新质发展,构建低空经济高质量智能支撑体系。

关键词: 时空智能, 低空经济, 多模态感知, 低空数字孪生, 测绘即服务(MaaS)

Abstract: The low-altitude economy constitutes a pivotal intersection between China's strategic emerging industrial clusters and the advancement of national security capabilities in novel domains.Its high-quality development critically depends on precise,dynamic spatio-temporal intelligence underpinned by surveying,mapping,and geospatial information technologies.This paper focuses on a four-element collaborative architecture—encompassing airspace,aerial route networks,takeoff and landing facilities,and unmanned systems—and systematically examines the technological evolution of geospatial information in constructing human-environment systems for low-altitude operations,advancing digital twin methodologies,and enabling multimodal intelligent sensing frameworks.It delineates the developmental trajectory of spatio-temporal intelligence and its empowering mechanisms in key operational functions such as airspace planning and real-time traffic management.Through case studies in representative applications—including low-altitude logistics and emergency response—the study evaluates the enabling efficacy of these technologies alongside persistent challenges such as data latency and interoperability gaps.Building on this analysis,the paper proposes forward-looking pathways:an integrated “communication-sensing-computing-intelligence” closed-loop system,standardized frameworks for dynamic digital foundations,and a mapping-as-a-service (MaaS)ecosystem.These strategies aim to transition geospatial information from static data provisioning toward intelligent,decision-ready services,thereby providing core impetus for the new-quality development of geospatial information and building a high-quality intelligent support system for the low-altitude economy.

Key words: spatio-temporal intelligence, low-altitude economy, multi-modal sensing, low-altitude digital twin, mapping-as-a-service

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