地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (1): 76-87.doi: 10.12082/dqxxkx.2020.190701
宋关福1,2,3,*(), 卢浩1,2, 王晨亮3, 胡辰璞1,2, 黄科佳1,2
收稿日期:
2019-11-20
修回日期:
2020-01-03
出版日期:
2020-01-25
发布日期:
2020-04-08
通讯作者:
宋关福
E-mail:songguanfu@supermap.com
作者简介:
宋关福(1969— ),男,博士,重庆人,教授级高工,主要从事地理信息软件技术研究。
基金资助:
SONG Guanfu1,2,3,*(), LU Hao1,2, WANG Chenliang3, HU Chenpu1,2, HUANG Kejia1,2
Received:
2019-11-20
Revised:
2020-01-03
Online:
2020-01-25
Published:
2020-04-08
Contact:
SONG Guanfu
E-mail:songguanfu@supermap.com
Supported by:
摘要:
作为人工智能的代表性技术,深度学习已经成为大数据等各个领域中最具有突破性发展的新技术。深度学习的成功主要得益于其新颖的数据驱动的特征表示学习能力,这种能力成功地替代了传统建模中基于领域知识人为设计特征的方式。在这些技术推动下,人工智能技术在新一代GIS基础软件技术的研究与应用中发挥着极为重要的作用,而现有人工智能GIS(AI GIS)技术研究整体仍处于初步探索阶段,距离成熟阶段尚有较大距离。作为新一代GIS基础软件的方法和技术,AI GIS已经广泛应用在遥感数据分析、水资源研究、空间流行病学和环境健康等地学领域,与传统GIS模型相比大大提高了对非结构化的遥感或街景影像和文本的地理信息提取和特征理解能力,显示出巨大的价值和发展潜力,但现有研究对AI GIS软件技术体系的梳理和总结尚不够全面。大部分研究只关注地理空间人工智能算法的研究及其特定场景下的应用研究,而对相关的AI GIS软件技术体系关注较少。本文分析了地理智慧的几个层次,并讨论了其与AI GIS的关系,总体介绍了国内外现有人工智能技术与GIS软件相结合的发展现状,进而提出了AI GIS软件技术体系。根据AI与GIS的结合关系提出了AI GIS由地理空间智能算法、AI赋能GIS和GIS赋能AI三部分组成。此外,为深入介绍AI GIS各部分组成,本文以SuperMap为例,探讨了AI GIS软件的设计与实现。最后,探讨了AI GIS的未来发展中亟需解决的问题。本文基于AI GIS软件技术的初步探索,尝试为地理智能的基础GIS软件技术体系的构建提供理论基础,以促进人工智能技术与GIS技术的进一步融合和发展,为实现地理智能提供一个可行的研究方向。
宋关福, 卢浩, 王晨亮, 胡辰璞, 黄科佳. 人工智能GIS软件技术体系初探[J]. 地球信息科学学报, 2020, 22(1): 76-87.DOI:10.12082/dqxxkx.2020.190701
SONG Guanfu, LU Hao, WANG Chenliang, HU Chenpu, HUANG Kejia. A Tentative Study on System of Software Technology for Artificial Intelligence GIS[J]. Journal of Geo-information Science, 2020, 22(1): 76-87.DOI:10.12082/dqxxkx.2020.190701
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