Graph neural network-based identification of ditch matching patterns across multi-scale geospatial data

IF 3.3 4区 地球科学 Q2 ENVIRONMENTAL SCIENCES Geocarto International Pub Date : 2023-12-26 DOI:10.1080/10106049.2023.2294900
Zhekun Huang, Haizhong Qian, Xiao Wang, Defu Lin, Junwei Wang, Limin Xie
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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...
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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
沟渠对水系数据至关重要。为了简化多尺度沟渠数据的匹配任务并提高准确性(Acc),必须找出沟渠数据的匹配模式。尽管沟渠数据非常重要...
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来源期刊
Geocarto International
Geocarto International ENVIRONMENTAL SCIENCES-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
6.30
自引率
13.20%
发文量
407
审稿时长
>12 weeks
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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