首页> 外文会议>2017 IEEE International Geoscience and Remote Sensing Symposium >An innovative distributed scatterer based time-series InSAR method over underground mining region
【24h】

An innovative distributed scatterer based time-series InSAR method over underground mining region

机译:一种基于分布式分布式散射的时间序列InSAR井下采矿方法

获取原文
获取原文并翻译 | 示例

摘要

Advanced Time series InSAR (ATS-InSAR) is generally refer to those TS-InSAR methods with an external Distributed Scatterer (DS) selection module, e.g. SqueeSAR and GEOS-ATSA. It is being known as a very efficient tool for monitoring the ground deformation over suburban or even non-urban regions with great success. However, within Appin Colliery, which is located in the southeastern corner of the Southern Coalfield, New South Wales (NSW), Australia. C-band ASAR based ATS-InSAR failed to produce reasonable outcome due to the underground mining effect. This paper presents a modified ATS-InSAR method for mapping the ground deformation over underground mining region. Firstly, traditional reliable DS pixels and Persistent Scatterer (PS) pixels are selected to form the initial triangular irregular network (TIN) reference network. Then the ground deformation and DEM error with respect to these Measurement Scatterer (MS) pixels are solved through a robust regression estimator. Due to the losses of coherence, the general underground mining pattern cannot be formed when using C-band image stacks. Therefore, in order to achieve the best detail, modified MS pixel selection method is conducted by including less reliable MS pixels based on a weighted least square method. Moreover, final result proved to be efficient to offer sufficient information to associated councils and department for risk management purpose.
机译:高级时间序列InSAR(ATS-InSAR)通常是指那些带有外部分布式散射体(DS)选择模块的TS-InSAR方法,例如SqueeSAR和GEOS-ATSA。它是一种非常有效的工具,用于监视郊区甚至非城市地区的地面变形,并取得了巨大的成功。但是,在位于澳大利亚新南威尔士州(NSW)南部煤田东南角的Appin煤矿内。由于地下开采的影响,基于C波段ASAR的ATS-InSAR无法产生合理的结果。本文提出了一种改进的ATS-InSAR方法,用于绘制地下采矿区域的地面变形图。首先,选择传统的可靠DS像素和持久散射(PS)像素来形成初始三角形不规则网络(TIN)参考网络。然后,通过鲁棒的回归估计器来解决与这些测量散射体(MS)像素有关的地面变形和DEM误差。由于失去连贯性,使用C波段图像堆栈时无法形成一般的地下采矿模式。因此,为了获得最好的细节,基于加权最小二乘法通过包括较不可靠的MS像素来进行改进的MS像素选择方法。此外,最终结果证明是有效的,可以为相关理事会和部门提供足够的信息以进行风险管理。

著录项

  • 来源
  • 会议地点 Fort Worth(US)
  • 作者单位

    Geoscience and Earth Observing System Group (GEOS), School of Civil and Environmental Engineering, the University of New South Wales (UNSW), Sydney, Australia;

    Geoscience and Earth Observing System Group (GEOS), School of Civil and Environmental Engineering, the University of New South Wales (UNSW), Sydney, Australia;

    Department of Surveying Engineering, School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, China;

    Geoscience and Earth Observing System Group (GEOS), School of Civil and Environmental Engineering, the University of New South Wales (UNSW), Sydney, Australia;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Remote sensing; Geoscience; Indexes; Manganese; Radar interferometry;

    机译:遥感;地球科学;索引;锰;雷达干涉法;;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号