测绘学报 ›› 2021, Vol. 50 ›› Issue (9): 1137-1146.doi: 10.11947/j.AGCS.2021.20200420
• 智能化测绘 • 下一篇
张永生, 张振超, 童晓冲, 纪松, 于英, 赖广陵
收稿日期:
2020-08-31
修回日期:
2021-06-08
发布日期:
2021-10-09
通讯作者:
张振超
E-mail:zhzhc_1@163.com
作者简介:
张永生(1963-),男,博士,教授,研究方向为摄影测量与遥感、地理空间智能等。E-mail:yszhang2001@vip.163.com
基金资助:
ZHANG Yongsheng, ZHANG Zhenchao, TONG Xiaochong, JI Song, YU Ying, LAI Guangling
Received:
2020-08-31
Revised:
2021-06-08
Published:
2021-10-09
Supported by:
摘要: 随着地理空间科学、人工智能、高性能计算技术的迅速发展,地理空间智能已成为处理和分析地理空间大数据的主要手段,并将在地球科学、空间认知、智慧城市、智慧社会等科学研究、工程建设和社会发展中发挥越来越重要的作用。地理空间智能作为地理空间科学和人工智能深度融合的交叉领域,其发展受到多学科的驱动,目前已在算力增强软硬件研制、系统开发、数据与模型共享、服务与应用方面不断取得进展,显示出巨大的活力和潜能,同时难题和挑战也相生相伴。本文首先阐述地理空间智能的概念演进、若干技术系统构建思路和国内外科学研究现状,然后梳理地理空间智能的典型应用,分析地理空间智能面临的问题和挑战,最后对其重要的发展方向及趋势予以展望。
中图分类号:
张永生, 张振超, 童晓冲, 纪松, 于英, 赖广陵. 地理空间智能研究进展和面临的若干挑战[J]. 测绘学报, 2021, 50(9): 1137-1146.
ZHANG Yongsheng, ZHANG Zhenchao, TONG Xiaochong, JI Song, YU Ying, LAI Guangling. Progress and challenges of geospatial artificial intelligence[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(9): 1137-1146.
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