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