使用新开发的全自动工具进行滑坡频率-面积分布分析的性能

IF 2.3 Q2 REMOTE SENSING Applied Geomatics Pub Date : 2024-07-12 DOI:10.1007/s12518-024-00581-8
Ali Bounab, Younes El Kharim, Mohamed El Kharrim, Abderrahman El Kharrim, Reda Sahrane
{"title":"使用新开发的全自动工具进行滑坡频率-面积分布分析的性能","authors":"Ali Bounab,&nbsp;Younes El Kharim,&nbsp;Mohamed El Kharrim,&nbsp;Abderrahman El Kharrim,&nbsp;Reda Sahrane","doi":"10.1007/s12518-024-00581-8","DOIUrl":null,"url":null,"abstract":"<div><p>Frequency-Area Distribution (FAD) analyses were introduced to landslides research since the early 2000’s. This technique is a powerful tool that allows assessing the completeness of landslide inventory maps (LIM), used to build both landslides susceptibility and landslides hazard assessment models. However, FAD analyses are not commonly used in such studies despite the significant potential of the technique. The long processing steps needed to generate FAD curves, which involve logarithmic binning and iterative model fitting using various statistical tools, constitutes an energy and time-consuming task that pushes many researchers away from using the technique. In fact, no fully automatic tool capable of generating FAD curves and models exists as of July 2023. Therefore, we attempt to provide a fully automatic computer program capable of binning, fitting FAD curves and assessing their goodness of fit to theoretical models in a fully automatic, one step process. An example is provided using real data from Taounate province, Northern Morocco, so as to demonstrate the ability of the tool to deal with exhaustive datasets. In addition, the Kolmogorov-Smirnov, goodness of fit test is added to provide an objective assessment of the data fitting, which constitutes a better alternative to the subjective visual assessment that most landslides researchers rely on. To sum up, we believe that this tool will help popularize the FAD technique, which will consequently improve the accuracy and objectivity of landslides risk and hazard assessment disciplines.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"16 3","pages":"789 - 796"},"PeriodicalIF":2.3000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The performance of landslides frequency-area distribution analyses using a newly developed fully automatic tool\",\"authors\":\"Ali Bounab,&nbsp;Younes El Kharim,&nbsp;Mohamed El Kharrim,&nbsp;Abderrahman El Kharrim,&nbsp;Reda Sahrane\",\"doi\":\"10.1007/s12518-024-00581-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Frequency-Area Distribution (FAD) analyses were introduced to landslides research since the early 2000’s. This technique is a powerful tool that allows assessing the completeness of landslide inventory maps (LIM), used to build both landslides susceptibility and landslides hazard assessment models. However, FAD analyses are not commonly used in such studies despite the significant potential of the technique. The long processing steps needed to generate FAD curves, which involve logarithmic binning and iterative model fitting using various statistical tools, constitutes an energy and time-consuming task that pushes many researchers away from using the technique. In fact, no fully automatic tool capable of generating FAD curves and models exists as of July 2023. Therefore, we attempt to provide a fully automatic computer program capable of binning, fitting FAD curves and assessing their goodness of fit to theoretical models in a fully automatic, one step process. An example is provided using real data from Taounate province, Northern Morocco, so as to demonstrate the ability of the tool to deal with exhaustive datasets. In addition, the Kolmogorov-Smirnov, goodness of fit test is added to provide an objective assessment of the data fitting, which constitutes a better alternative to the subjective visual assessment that most landslides researchers rely on. To sum up, we believe that this tool will help popularize the FAD technique, which will consequently improve the accuracy and objectivity of landslides risk and hazard assessment disciplines.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":\"16 3\",\"pages\":\"789 - 796\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-024-00581-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-024-00581-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0

摘要

自 2000 年代初以来,山体滑坡研究引入了频率-面积分布(FAD)分析。该技术是一种强大的工具,可用于评估滑坡清单图(LIM)的完整性,从而建立滑坡易发性和滑坡危害评估模型。然而,尽管 FAD 分析技术潜力巨大,但在此类研究中却并不常用。生成 FAD 曲线所需的处理步骤较长,其中包括对数分档和使用各种统计工具进行迭代模型拟合,这构成了一项耗费精力和时间的任务,促使许多研究人员放弃使用该技术。事实上,截至 2023 年 7 月,还没有一款能够生成 FAD 曲线和模型的全自动工具。因此,我们试图提供一种全自动计算机程序,能够以全自动、一步到位的方式分选、拟合 FAD 曲线并评估其与理论模型的拟合度。我们以摩洛哥北部陶纳特省的真实数据为例,展示了该工具处理详尽数据集的能力。此外,该工具还添加了 Kolmogorov-Smirnov 拟合度测试,以提供数据拟合的客观评估,从而更好地替代大多数滑坡研究人员所依赖的主观视觉评估。总之,我们相信该工具将有助于普及 FAD 技术,从而提高滑坡风险和灾害评估学科的准确性和客观性。
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
The performance of landslides frequency-area distribution analyses using a newly developed fully automatic tool

Frequency-Area Distribution (FAD) analyses were introduced to landslides research since the early 2000’s. This technique is a powerful tool that allows assessing the completeness of landslide inventory maps (LIM), used to build both landslides susceptibility and landslides hazard assessment models. However, FAD analyses are not commonly used in such studies despite the significant potential of the technique. The long processing steps needed to generate FAD curves, which involve logarithmic binning and iterative model fitting using various statistical tools, constitutes an energy and time-consuming task that pushes many researchers away from using the technique. In fact, no fully automatic tool capable of generating FAD curves and models exists as of July 2023. Therefore, we attempt to provide a fully automatic computer program capable of binning, fitting FAD curves and assessing their goodness of fit to theoretical models in a fully automatic, one step process. An example is provided using real data from Taounate province, Northern Morocco, so as to demonstrate the ability of the tool to deal with exhaustive datasets. In addition, the Kolmogorov-Smirnov, goodness of fit test is added to provide an objective assessment of the data fitting, which constitutes a better alternative to the subjective visual assessment that most landslides researchers rely on. To sum up, we believe that this tool will help popularize the FAD technique, which will consequently improve the accuracy and objectivity of landslides risk and hazard assessment disciplines.

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
Applied Geomatics
Applied Geomatics REMOTE SENSING-
CiteScore
5.40
自引率
3.70%
发文量
61
期刊介绍: Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences. The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology. Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements
期刊最新文献
Interphase modeling of sedimentation rate using the GIS-based modified universal soil loss equation Circle-circle intersection. A universal method for solving typical surveying problems Drainage analysis of the Karanja River basin, Karnataka, India using Geo-informatics Predicting the spatiotemporal changes of an agriculturally vulnerable region of Bangladesh A new fuzzy location-based approach for fire station site selection in Tehran
×
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