基于结构变分法的机载电磁数据平差

IF 1.8 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Instrumentation Methods and Data Systems Pub Date : 2024-03-26 DOI:10.5194/egusphere-2024-306
Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, Yunqing Liu
{"title":"基于结构变分法的机载电磁数据平差","authors":"Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, Yunqing Liu","doi":"10.5194/egusphere-2024-306","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> The leveling errors are defined as the data difference among flight lines in airborne geophysical data. The differences of the signal leveling always show as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided leveling error model by an anisotropic Gabor filter. Then we embed the leveling error model in total variational framework to flexibly calculate leveling errors. The guided leveling error model constrain the noise term of total variation rather than just blind removal. Moreover, the structured variational method can be extended to remove other type of noises which have general noise priors. We have applied the method to the airborne electromagnetic, magnetic data, and apparent conductivity data collected by Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level airborne geophysical data based on the space properties of leveling error.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Airborne electromagnetic data leveling based on structured variational method\",\"authors\":\"Qiong Zhang, Xin Chen, Zhonghang Ji, Fei Yan, Zhengkun Jin, Yunqing Liu\",\"doi\":\"10.5194/egusphere-2024-306\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> The leveling errors are defined as the data difference among flight lines in airborne geophysical data. The differences of the signal leveling always show as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided leveling error model by an anisotropic Gabor filter. Then we embed the leveling error model in total variational framework to flexibly calculate leveling errors. The guided leveling error model constrain the noise term of total variation rather than just blind removal. Moreover, the structured variational method can be extended to remove other type of noises which have general noise priors. We have applied the method to the airborne electromagnetic, magnetic data, and apparent conductivity data collected by Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level airborne geophysical data based on the space properties of leveling error.\",\"PeriodicalId\":48742,\"journal\":{\"name\":\"Geoscientific Instrumentation Methods and Data Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscientific Instrumentation Methods and Data Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/egusphere-2024-306\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscientific Instrumentation Methods and Data Systems","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/egusphere-2024-306","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

摘要平差是指机载地球物理数据中飞行线路之间的数据差异。信号平差总是在成像图上显示为与飞行线平行的条纹状图案。这种固定的结构模式启发我们用各向异性的 Gabor 滤波器来构建一个有引导的平差误差模型。然后,我们将配平误差模型嵌入总变分法框架,以灵活计算配平误差。引导式平差误差模型限制了总变分的噪声项,而不仅仅是盲目去除。此外,结构变分法还可扩展用于去除具有一般噪声前值的其他类型噪声。我们将该方法应用于安大略省地质调查局收集的机载电磁、磁数据和视导率数据,通过与已公布数据的比较,证实了该方法的有效性和稳健性。根据平差误差的空间特性,结构变分法可以更好地平整机载地球物理数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Airborne electromagnetic data leveling based on structured variational method
Abstract. The leveling errors are defined as the data difference among flight lines in airborne geophysical data. The differences of the signal leveling always show as a striping pattern parallel to the flight lines on the imaged maps. The fixed structured pattern inspires us to structure a guided leveling error model by an anisotropic Gabor filter. Then we embed the leveling error model in total variational framework to flexibly calculate leveling errors. The guided leveling error model constrain the noise term of total variation rather than just blind removal. Moreover, the structured variational method can be extended to remove other type of noises which have general noise priors. We have applied the method to the airborne electromagnetic, magnetic data, and apparent conductivity data collected by Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data. The structured variational method can better level airborne geophysical data based on the space properties of leveling error.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Geoscientific Instrumentation Methods and Data Systems
Geoscientific Instrumentation Methods and Data Systems GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
3.70
自引率
0.00%
发文量
23
审稿时长
37 weeks
期刊介绍: Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following: concepts, design, and description of instrumentation and data systems; retrieval techniques of scientific products from measurements; calibration and data quality assessment; uncertainty in measurements; newly developed and planned research platforms and community instrumentation capabilities; major national and international field campaigns and observational research programs; new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters; networking of instruments for enhancing high temporal and spatial resolution of observations. GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following: foster scientific discussion; maximize the effectiveness and transparency of scientific quality assurance; enable rapid publication; make scientific publications freely accessible.
期刊最新文献
Comparing triple and single Doppler lidar wind measurements with sonic anemometer data based on a new filter strategy for virtual tower measurements Managing Data of Sensor-Equipped Transportation Networks using Graph Databases Airborne electromagnetic data levelling based on the structured variational method A multiplexing system for quantifying oxygen fractionation factors in closed chambers Development of an integrated analytical platform of clay minerals separation, characterization and 40K/40Ar dating
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1