The Improvement of Change Detection from Multi-Date Satellite Images using the Source Separation

Amira Echtioui, O. B. Sassi, Lamia Sellami, A. Hamida
{"title":"The Improvement of Change Detection from Multi-Date Satellite Images using the Source Separation","authors":"Amira Echtioui, O. B. Sassi, Lamia Sellami, A. Hamida","doi":"10.1109/MMS48040.2019.9157311","DOIUrl":null,"url":null,"abstract":"The development of satellites with the strong temporal repetitiveness and development of remote sensing techniques resulted in the advancement of change detection techniques from geospatial imagery. The natural events cause many modifications in the control process of the ecosystems. There is a necessity of using a method capable to map, categorize and monitor areas affected by natural events along time. In this article, a novel methodology of change detection is proposed in order to improve the change detection from multi-date satellite image using the source separation. The results obtained by our methodology are efficient and effective.","PeriodicalId":373813,"journal":{"name":"2019 IEEE 19th Mediterranean Microwave Symposium (MMS)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 19th Mediterranean Microwave Symposium (MMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMS48040.2019.9157311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The development of satellites with the strong temporal repetitiveness and development of remote sensing techniques resulted in the advancement of change detection techniques from geospatial imagery. The natural events cause many modifications in the control process of the ecosystems. There is a necessity of using a method capable to map, categorize and monitor areas affected by natural events along time. In this article, a novel methodology of change detection is proposed in order to improve the change detection from multi-date satellite image using the source separation. The results obtained by our methodology are efficient and effective.
基于源分离的多日期卫星图像变化检测改进
具有较强时间重复性的卫星的发展和遥感技术的发展导致了地理空间图像变化检测技术的进步。自然事件在生态系统的控制过程中引起许多变化。有必要使用一种能够长期绘制、分类和监测受自然事件影响地区的方法。本文提出了一种新的变化检测方法,利用源分离技术对多日期卫星图像进行变化检测。我们的方法得到的结果是高效和有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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