Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis

L. Mossucca, I. Zinno, S. Elefante, C. Luca, V. Casola, O. Terzo, F. Casu, R. Lanari
{"title":"Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis","authors":"L. Mossucca, I. Zinno, S. Elefante, C. Luca, V. Casola, O. Terzo, F. Casu, R. Lanari","doi":"10.1109/CLOUDCOM.2014.96","DOIUrl":null,"url":null,"abstract":"The advanced Differential SAR Interferometers (DInSAR) methodologies are widely used for the investigation of Earth's surface deformation phenomena. In particular, the advanced DInSAR approach referred to as Small Baseline Subset (SBAS) technique is able to produce deformation velocity maps and the corresponding displacement time-series from a temporal sequence of space borne SAR acquisitions. Considering the already huge SAR data archives as well the upcoming massive data flow coming from the SENTINEL satellite constellation, cloud computing can be a valid solution to carry out DInSAR analyses thanks to its scalability and flexibility features. In this paper, the focus is given on the migration of the whole parallel version of the SBAS technique, namely P-SBAS, to a cloud environment by taking into account different parameters that influence processing time. Experimental tests that have been performed using both private and public cloud are also presented.","PeriodicalId":249306,"journal":{"name":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 6th International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLOUDCOM.2014.96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The advanced Differential SAR Interferometers (DInSAR) methodologies are widely used for the investigation of Earth's surface deformation phenomena. In particular, the advanced DInSAR approach referred to as Small Baseline Subset (SBAS) technique is able to produce deformation velocity maps and the corresponding displacement time-series from a temporal sequence of space borne SAR acquisitions. Considering the already huge SAR data archives as well the upcoming massive data flow coming from the SENTINEL satellite constellation, cloud computing can be a valid solution to carry out DInSAR analyses thanks to its scalability and flexibility features. In this paper, the focus is given on the migration of the whole parallel version of the SBAS technique, namely P-SBAS, to a cloud environment by taking into account different parameters that influence processing time. Experimental tests that have been performed using both private and public cloud are also presented.
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
地表干涉SAR图像分析科学进展的云平台
先进的差分SAR干涉仪(DInSAR)方法被广泛用于地球表面变形现象的研究。特别是,被称为小基线子集(SBAS)技术的先进DInSAR方法能够从星载SAR获取的时间序列中生成变形速度图和相应的位移时间序列。考虑到已经庞大的SAR数据档案以及即将到来的来自SENTINEL卫星星座的海量数据流,云计算由于其可扩展性和灵活性的特点,可以成为进行DInSAR分析的有效解决方案。在本文中,重点是考虑到影响处理时间的不同参数,将SBAS技术的整个并行版本(即P-SBAS)迁移到云环境。还介绍了使用私有云和公共云进行的实验测试。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Exploring the Performance Impact of Virtualization on an HPC Cloud Performance Study of Spindle, A Web Analytics Query Engine Implemented in Spark Role of System Modeling for Audit of QoS Provisioning in Cloud Services Dependability Analysis on Open Stack IaaS Cloud: Bug Anaysis and Fault Injection Delegated Access for Hadoop Clusters in the Cloud
×
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