遥感知识图谱创建及其典型场景应用技术  

Remote sensing knowledge graph construction and its application in typical scenarios

作　　者：张永军[1] 王飞 李彦胜 欧阳松 魏东 刘晓建 孔德宇 陈瑞贤 张斌 ZHANG Yongjun;WANG Fei;LI Yansheng;OUYANG Song;WEI Dong;LIU Xiaojian;KONG Deyu;CHEN Ruixian;ZHANG Bin(School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)

机构地区：[1]武汉大学遥感信息工程学院,武汉430079

出　　处：《遥感学报》2023年第2期249-266,共18页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金重点项目(编号:42030102);国家重点研发计划(编号:2018YFB0505003)。

摘　　要：相对于当前指数级增长的强大遥感数据获取能力,遥感大数据的智能处理和知识服务能力相对滞后,海量多源化遥感数据堆积与有限信息孤岛并存的矛盾日益突出,亟需有效的遥感领域知识建模技术来辅助挖掘遥感大数据的有用信息并形成知识服务能力。知识图谱技术以符号形式描述物理世界中的概念及其相互关系,具有强大的知识建模与推理应用能力,在搜索引擎、电子商务、社交网络分析等领域已经得到成功应用。在通用知识图谱技术启发下,本文首次提出建立遥感领域知识图谱研究构想,可以为遥感领域知识建模与知识服务提供支撑。本文首先回顾通用知识图谱的发展历程,然后探讨遥感知识图谱的构建技术、遥感知识图谱驱动的典型地学应用案例,最后对遥感知识图谱的应用现状与未来研究方向进行分析论述。总体来说,遥感知识图谱的研究有利于更好的归纳遥感领域学科概念化知识、管理遥感大数据所蕴含的新增信息与知识,可以向多领域众多用户提供灵活便捷的遥感知识查询与知识服务能力,有助于全面提升海量多源遥感观测成果的应用能力,在全球遥感地表覆盖分类、气候变化、国际人道主义援助等方面都将发挥重要作用。Compared with the current powerful acquisition capabilities of remote sensing data,its intelligent processing and knowledge service capabilities are relatively lagging.The contradiction between the accumulation of massive multisource remote sensing data and the limited information island is becoming increasingly prominent.Therefore,there is an urgent need for effective remote sensing domain knowledge modeling technology to assist in mining the useful information of remote sensing big data and form knowledge service capabilities.A Knowledge Graph(KG)describes the concepts and their relationships in the physical world in symbolic form.It has strong knowledge modeling and reasoning capabilities and has been successfully applied in search engines,e-commerce,social network analysis and other fields.Inspired by the general KGs,this paper conceives of establishing a remote sensing domain KG for the first time,which can provide support for knowledge modeling and knowledge services in the remote sensing field.First,this paper reviews the development history of general KGs.Second,it discusses the technologies of constructing remote sensing KGs.Compared with general KGs,remote sensing KGs are oriented to the field of remote sensing geosciences.They have significant disciplinary characteristics and spatiotemporal graph characteristics in terms of graph nodes,graph relationships and graph reasoning.Specific performances are as follows:(1)Images are an important part of remote sensing,which play an irreplaceable role and are ignored by general KGs.(2)Remote sensing knowledge is oriented to spatial entities.In addition to semantic relationships,the description of entity relationships also requires spatial and temporal relationships.(3)Traditional logical reasoning and natural language processing learning reasoning cannot effectively deal with image entities and spatial relationships.To solve the above problems,this paper draws on the construction scheme of the general KG and related domain KG and proposes the basic construction

关 键 词：遥感知识图谱 典型场景应用 人工智能 知识服务 知识图谱表示学习 领域知识建模 

分 类 号：P2[天文地球—测绘科学与技术]