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New Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method Based on Remote Sensing Images

文献类型：期刊论文

作者Wang, Shu2; Yan, Xinrong2,3; Zhu, Yunqiang2,4; Song, Jia2; Sun, Kai2; Li, Weirong2,3; Hu, Lei2,3; Qi, Yanmin1,2; Xu, Huiyao2,3
刊名REMOTE SENSING
出版日期2022-10-01
卷号14期号:19页码:20
关键词toponym correction TC-RSI geo-parsing remote sensing image text mining location correction toponym resolution
DOI10.3390/rs14194725
通讯作者Zhu, Yunqiang(zhuyq@lreis.ac.cn)
英文摘要Geo-parsing, one of the key components of geographical information retrieval, is a process to recognize and geo-locate toponyms mentioned in texts. Such a process can obtain locations contained in toponyms successfully with consistent updating of neural network models and multiple contextual features. The significant offset distance between the geo-parsed locations and the actual occurrence locations still remains. This is because the geo-parsed locations sourced from toponyms in texts always point to the centers of cities, counties, or towns, and cannot directly represent the actual occurrence locations such as factories, farms, and activity areas. Consequently, The significant offset distances between the geo-parsed locations and the actual occurrence locations limit text mining applications in micro-scale geographic discoveries. This research aims at decreasing offset distances of geo-parsed locations by proposing a novel Toponym Correction Method based on satellite Remote Sensing Images (TC-RSI). The TC-RSI method uses satellite remote sensing images to provide extra detailed spatial information that can be associated with the sentence toponym by corresponding attributes. The TC-RSI method was validated in a case study of the forest ecological pattern dataset of An'hui province from visual, statistical, and robustness assessments. The correction results show that the TC-RSI method dramatically decreases the offset distances from about 50 km to about 1 km and promotes geographical discoveries on smaller scales. A series of analyses indicated that the TC-RSI is a valid, effective, and promising method to improve the accuracy of geo-parsed locations, which allows text mining to find more accurate geographical discoveries with lower offset distances. Moreover, toponym correction promotes the use of more diverse spatial data sources, such as Lidar, domain gazetteers, Wikimedia, and streetscapes, which are expected to usher in a new era of geo-parsing with toponym corrections.
WOS关键词INFORMATION ; CHALLENGES ; SYSTEM
资助项目National Natural Science Foundation of China[42101467] ; National Natural Science Foundation of China[42050101] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100101] ; Informatization Plan of Chinese Academy of Sciences[CAS-WX2021SF-0106]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者MDPI
WOS记录号WOS:000867896900001
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Informatization Plan of Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/185498]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, Yunqiang
作者单位1.Univ Nottingham Ningbo China, Fac Sci & Engn, Ningbo 315199, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100101, Peoples R China
4.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Shu,Yan, Xinrong,Zhu, Yunqiang,et al. New Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method Based on Remote Sensing Images[J]. REMOTE SENSING,2022,14(19):20.
APA Wang, Shu.,Yan, Xinrong.,Zhu, Yunqiang.,Song, Jia.,Sun, Kai.,...&Xu, Huiyao.(2022).New Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method Based on Remote Sensing Images.REMOTE SENSING,14(19),20.
MLA Wang, Shu,et al."New Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method Based on Remote Sensing Images".REMOTE SENSING 14.19(2022):20.

入库方式： OAI收割

来源：地理科学与资源研究所

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