智能化测绘的混合计算范式与方法研究

doi:10.11947/j.AGCS.2024.20240131

测绘学报 ›› 2024, Vol. 53 ›› Issue (6): 985-998.doi: 10.11947/j.AGCS.2024.20240131

• 智能化测绘 • 下一篇

智能化测绘的混合计算范式与方法研究

陈军¹^,²^,³^,⁴(), 艾廷华⁵, 闫利⁶(), 刘万增¹^,³, 李志林⁷, 朱强⁸, 高井祥², 谢洪⁶, 武昊¹, 张俊¹

^1.国家基础地理信息中心，北京　100830
^2.中国矿业大学环境与测绘学院，江苏　徐州　221116
^3.自然资源部时空信息与智能服务重点实验室，北京　100830
^4.莫干山地信实验室，浙江　湖州　313299
^5.武汉大学资源与环境科学学院，湖北　武汉　430079
^6.武汉大学测绘学院，湖北　武汉　430079
^7.西南交通大学地球科学与环境工程学院，四川　成都　611756
^8.浙江大学，浙江　杭州　310058

收稿日期:2024-04-06 发布日期:2024-07-22
通讯作者: 闫利 E-mail:chenjun@ngcc.cn;lyan@sgg.whu.edu.cn
作者简介:陈军（1956—），男，教授，中国工程院院士，研究方向为时空信息理论及赋能应用。　E-mail：chenjun@ngcc.cn
基金资助:
国家自然科学基金(42394060)

Hybrid computational paradigm and methods for intelligentized surveying and mapping

Jun CHEN¹^,²^,³^,⁴(), Tinghua AI⁵, Li YAN⁶(), Wanzeng LIU¹^,³, Zhilin LI⁷, Qiang ZHU⁸, Jingxiang GAO², Hong XIE⁶, Hao WU¹, Jun ZHANG¹

^1.National Geomatics Center of China, Beijing 100830, China
^2.School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
^3.Key Laboratory of Spatio-temporal Information and Intelligent Services (LSIIS), MNR, Beijing 100830, China
^4.Moganshan Geospatial Information Laboratory, Huzhou 313299, China
^5.School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
^6.School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
^7.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
^8.Zhejiang University, Hangzhou 310058, China

Received:2024-04-06 Published:2024-07-22
Contact: Li YAN E-mail:chenjun@ngcc.cn;lyan@sgg.whu.edu.cn
About author:CHEN Jun (1956—), male, professor, academician of Chinese Academy of Engineering, majors in the theory of geospatial information modeling and its applications.　E-mail: chenjun@ngcc.cn
Supported by:
The National Natural Science Foundation of China(42394060)

摘要/Abstract

摘要：

传统数字化测绘产品在数字经济、数字治理与数字生活等方面发挥着越来越重要的时空基底和关键生产要素作用，但其精细程度、更新周期、服务方式难以满足数智新时代下的高质量发展需求。因此，迫切需要实现数字化测绘到智能化测绘的转型升级，通过构建新型时空新型基础设施以全方位提升高品质的时空信息供给能力、高层次的时空数据分析能力，以及高水平的时空知识服务能力。本文从测绘自然智能与人工智能结合的必要性分析出发，首先讨论了测绘智能计算的基本概论及内涵，然后提出了智能化测绘知识为引导、数据为驱动、算法为基础、服务为支撑（KDAS）的混合智能计算范式并梳理了其构建基本任务，最后从感知、认知、表达与服务4个维度研究并系统阐述了智能化测绘的混合计算关键技术和相应途径，试图为混合计算赋能智能化测绘知识体系构建以及产业发展升级搭建基础研究框架。

关键词: 智能化测绘, 时空型混合智能, KDAS混合智能计算范式, 混合智能计算方法

Abstract:

The products from traditional digital surveying and mapping play an increasingly important role as the spatiotemporal foundation and key production element in the field of digital economy, digital governance, and digital life. However, their level of detail, update cycle, and service mode struggle to meet the high-quality development demands of the new digital intelligence era. Thus, there is an urgent need to transition from digital to intelligentized surveying and mapping, constructing new spatiotemporal infrastructures to comprehensively enhance the supply of high-quality spatiotemporal information resources, high-level spatiotemporal analysis capabilities, and high-standard spatiotemporal knowledge services. Starting from the analysis of the necessity of combining natural intelligence and artificial intelligence in surveying and mapping, this paper firstly discusses the basic overview and connotation of intelligent computing for surveying and mapping. Then we propose a new paradigm of KDAS hybrid intelligent computation for intelligent mapping, and sort out the basic tasks of its construction. Finally, this paper systematically elaborates the research method of hybrid computation for the key tasks of intelligentized surveying and mapping including perception, cognition, expression and service, as well as pointing out the basic research directions for the construction of the intelligent knowledge system and the industrial upgradation empowered by hybrid computing.

Key words: intelligentized surveying and mapping, spatiotemporal hybrid intelligence, KDAS computing paradigm of hybrid intelligence, methodology of hybrid computation

中图分类号:

陈军, 艾廷华, 闫利, 刘万增, 李志林, 朱强, 高井祥, 谢洪, 武昊, 张俊. 智能化测绘的混合计算范式与方法研究[J]. 测绘学报, 2024, 53(6): 985-998.

Jun CHEN, Tinghua AI, Li YAN, Wanzeng LIU, Zhilin LI, Qiang ZHU, Jingxiang GAO, Hong XIE, Hao WU, Jun ZHANG. Hybrid computational paradigm and methods for intelligentized surveying and mapping[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(6): 985-998.

图/表 3

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智能化测绘的混合计算范式与方法研究

Hybrid computational paradigm and methods for intelligentized surveying and mapping

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