链接线段:使用 Hough 变换聚类线段和中尺度特征提取

Allison Kubo Hutchison, L. Karlstrom, Tushar Mittal
{"title":"链接线段:使用 Hough 变换聚类线段和中尺度特征提取","authors":"Allison Kubo Hutchison, L. Karlstrom, Tushar Mittal","doi":"10.21105/joss.06147","DOIUrl":null,"url":null,"abstract":"Linear feature analysis plays a fundamental role in geospatial applications, from detecting infrastructure networks to characterizing geological formations. In this paper, we introduce linkinglines , an open-source Python package tailored for the clustering and feature extraction of linear structures in geospatial data. Our package leverages the Hough Transform, commonly used in image processing, performs clustering of line segments in the Hough Space, and then provides unique feature extraction methods and visualization. linkinglines em-powers researchers, data scientists, and analysts across diverse domains to efficiently process, understand, and extract valuable insights from linear features, contributing to more informed decision-making and enhanced data-driven exploration. We have used linkinglines to map dike swarms with thousands of segments associated with Large Igneous Provinces in Kubo Hutchison et al. (2023).","PeriodicalId":94101,"journal":{"name":"Journal of open source software","volume":" 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"LinkingLines: Using the Hough Transform to Cluster Line\\nSegments and Mesoscale Feature Extraction\",\"authors\":\"Allison Kubo Hutchison, L. Karlstrom, Tushar Mittal\",\"doi\":\"10.21105/joss.06147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Linear feature analysis plays a fundamental role in geospatial applications, from detecting infrastructure networks to characterizing geological formations. In this paper, we introduce linkinglines , an open-source Python package tailored for the clustering and feature extraction of linear structures in geospatial data. Our package leverages the Hough Transform, commonly used in image processing, performs clustering of line segments in the Hough Space, and then provides unique feature extraction methods and visualization. linkinglines em-powers researchers, data scientists, and analysts across diverse domains to efficiently process, understand, and extract valuable insights from linear features, contributing to more informed decision-making and enhanced data-driven exploration. We have used linkinglines to map dike swarms with thousands of segments associated with Large Igneous Provinces in Kubo Hutchison et al. (2023).\",\"PeriodicalId\":94101,\"journal\":{\"name\":\"Journal of open source software\",\"volume\":\" 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of open source software\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.21105/joss.06147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of open source software","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.21105/joss.06147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

线性特征分析在地理空间应用中发挥着基础性作用,从检测基础设施网络到描述地质构造,不一而足。本文介绍的 linkinglines 是一个开源 Python 软件包,专门用于地理空间数据中线性结构的聚类和特征提取。我们的软件包利用图像处理中常用的 Hough 变换,在 Hough 空间中对线段进行聚类,然后提供独特的特征提取方法和可视化。linkinglines 可帮助不同领域的研究人员、数据科学家和分析师高效地处理、理解线性特征并从中提取有价值的见解,从而有助于做出更明智的决策和加强数据驱动的探索。我们利用 linkinglines 绘制了与 Kubo Hutchison 等人(2023 年)的大型火成岩矿带相关的堤群地图,其中包含数千个线段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LinkingLines: Using the Hough Transform to Cluster Line Segments and Mesoscale Feature Extraction
Linear feature analysis plays a fundamental role in geospatial applications, from detecting infrastructure networks to characterizing geological formations. In this paper, we introduce linkinglines , an open-source Python package tailored for the clustering and feature extraction of linear structures in geospatial data. Our package leverages the Hough Transform, commonly used in image processing, performs clustering of line segments in the Hough Space, and then provides unique feature extraction methods and visualization. linkinglines em-powers researchers, data scientists, and analysts across diverse domains to efficiently process, understand, and extract valuable insights from linear features, contributing to more informed decision-making and enhanced data-driven exploration. We have used linkinglines to map dike swarms with thousands of segments associated with Large Igneous Provinces in Kubo Hutchison et al. (2023).
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
自引率
0.00%
发文量
0
审稿时长
3 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信