{"title":"基于图神经网络的多尺度地理空间数据沟渠匹配模式识别","authors":"Zhekun Huang, Haizhong Qian, Xiao Wang, Defu Lin, Junwei Wang, Limin Xie","doi":"10.1080/10106049.2023.2294900","DOIUrl":null,"url":null,"abstract":"Ditches are vital to water system data. To ease the task of matching multi-scale ditch data and enhance accuracy (Acc), it is essential to discern ditch data matching patterns. Despite its importan...","PeriodicalId":12532,"journal":{"name":"Geocarto International","volume":"313 5 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Graph neural network-based identification of ditch matching patterns across multi-scale geospatial data\",\"authors\":\"Zhekun Huang, Haizhong Qian, Xiao Wang, Defu Lin, Junwei Wang, Limin Xie\",\"doi\":\"10.1080/10106049.2023.2294900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ditches are vital to water system data. To ease the task of matching multi-scale ditch data and enhance accuracy (Acc), it is essential to discern ditch data matching patterns. Despite its importan...\",\"PeriodicalId\":12532,\"journal\":{\"name\":\"Geocarto International\",\"volume\":\"313 5 1\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geocarto International\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/10106049.2023.2294900\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geocarto International","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/10106049.2023.2294900","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Graph neural network-based identification of ditch matching patterns across multi-scale geospatial data
Ditches are vital to water system data. To ease the task of matching multi-scale ditch data and enhance accuracy (Acc), it is essential to discern ditch data matching patterns. Despite its importan...
期刊介绍：
Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community.
The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines;
Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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