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首页> 外文期刊>Remote Sensing >An On-Demand Web Tool for the Unsupervised Retrieval of Earth’s Surface Deformation from SAR Data: The P-SBAS Service within the ESA G-POD Environment
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An On-Demand Web Tool for the Unsupervised Retrieval of Earth’s Surface Deformation from SAR Data: The P-SBAS Service within the ESA G-POD Environment

机译：一种用于从SAR数据中无监督地检索地球表面变形的按需Web工具：ESA G-POD环境中的P-SBAS服务

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This paper presents a web tool for the unsupervised retrieval of Earth’s surface deformation from Synthetic Aperture Radar (SAR) satellite data. The system is based on the implementation of the Differential SAR Interferometry (DInSAR) algorithm referred to as Parallel Small BAseline Subset (P-SBAS) approach, within the Grid Processing on Demand (G-POD) environment that is a part of the ESA’s Geohazards Exploitation Platform (GEP). The developed on-demand web tool, which is specifically addressed to scientists that are non-expert in DInSAR data processing, permits to set up an efficient on-line P-SBAS processing service to produce surface deformation mean velocity maps and time series in an unsupervised manner. Such results are obtained by exploiting the available huge ERS and ENVISAT SAR data archives; moreover, the implementation of the Sentinel-1 P-SBAS processing chain is in a rather advanced status and first results are already available. Thanks to the adopted strategy to co-locate both DInSAR algorithms and computational resources close to the SAR data archives, as well as the provided capability to easily generate the DInSAR results, the presented web tool may contribute to drastically expand the user community exploiting the DInSAR products and methodologies.
机译：本文介绍了一种网络工具，可从合成孔径雷达（SAR）卫星数据中无监督地检索地球表面变形。该系统基于ESA地质灾害的一部分的按需网格处理（G-POD）环境中差分SAR干涉测量（DInSAR）算法（称为并行小BAseline子集（P-SBAS）方法）的实现。开发平台（GEP）。专门针对DInSAR数据处理领域非专业科学家的按需开发的网络工具允许建立高效的在线P-SBAS处理服务，以生成表面变形平均速度图和时间序列。无人监督的方式。这些结果是通过利用可用的巨大ERS和ENVISAT SAR数据档案获得的;此外，Sentinel-1 P-SBAS处理链的实施处于相当先进的状态，并且已经有了初步结果。由于采用了将DInSAR算法和计算资源同时放置在SAR数据档案附近的策略，以及所提供的轻松生成DInSAR结果的功能，因此所提供的Web工具可能有助于利用DInSAR大大扩展用户社区产品和方法论。

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