Please wait a minute...
国土资源遥感  2019, Vol. 31 Issue (2): 210-217    DOI: 10.6046/gtzyyg.2019.02.29
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
Sentinel-1A数据矿区地表形变监测适用性分析
白泽朝1,汪宝存2(),靳国旺1,徐青1,张红敏1,刘辉3
1.信息工程大学地理空间信息学院,郑州 450001
2.河南省地质矿产勘查开发局测绘地理信息院,郑州 450006
3.华北水利水电大学测绘与地理信息学院,郑州 450046
Applicability analysis of ground deformation monitoring in mining area by Sentinel - 1A data
Zechao BAI1,Baocun WANG2(),Guowang JIN1,Qing XU1,Hongmin ZHANG1,Hui LIU3
1.Geospatial Information Institute, Information Engineering University, Zhengzhou 450001, China
2.Institute of Surveying, Mapping and Geoinformation, Henan Provincial Bureau of Geo-Exploration and Mineral Development, Zhengzhou 450006, China
3.School of Surverying and Geoinformatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
全文: PDF(17595 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

针对合成孔径雷达干涉测量(interferometric synthetic aperture Radar,InSAR)技术监测矿区地表形变中形变位置确定、形变梯度估计和相干性之间的关系,利用Sentinel-1A数据开展InSAR技术矿区地表形变监测适用性研究,分析干涉图相干性、形变位置识别和形变梯度之间的响应关系。以河南省焦作市某矿区为研究区,实验结果表明,在暖温带半湿润季风气候条件下,裸地和村落地表类型全年保持较高相干性,目视识别可以有效确定矿区的形变位置,受村落周边农田的影响,部分形变范围无法准确确定,通过形变梯度函数模型验证形变梯度也在可检测的范围; 农田覆盖类型夏季在卫星最短重访周期内,目视识别可以有效确定矿区的形变区域和范围,但受噪声影响条纹模糊,通过形变梯度函数模型验证形变梯度位于可检测最小形变梯度上; 采用真实水准数据验证了村落地物类别模型的适用性。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
白泽朝
汪宝存
靳国旺
徐青
张红敏
刘辉
关键词 合成孔径雷达干涉测量Sentinel-1A矿区形变形变梯度相干性    
Abstract

According to the relationship between the deformation position determination, the deformation gradient estimation and the coherence of the InSAR monitoring surface deformation in the mining area, the Sentinel-1A data were used to study the applicability of the InSAR technique in the monitoring of the mining area. The experimental results show that the surface type of bare land and village is maintained at high coherence throughout the year under the condition of semi - humid monsoon climate in the warm and temperate zone in Henan Province. Visual identification can effectively determine the deformation position of the mining area. The deformation range can not be accurately determined by the deformation gradient function model. The deformation gradient is also within the range of the detectable range. The field coverage type can effectively determine the deformation of the mine in summer. In addition, the deformation gradient is located on the detectable minimum deformation gradient by using the deformation gradient function model. Furthermore, the applicability of the model is proved by the leveling data.

Key wordsInSAR    Sentinel-1A    mine deformation    deformation gradient    coherence
收稿日期: 2018-01-05      出版日期: 2019-05-23
ZTFLH:  TP79  
基金资助:河南省国土资源厅地质科研项目“基于HNGICS系统在采矿区三维形变监测技术研究”(201413);国家自然科学基金项目“基于区域网平差的InSAR干涉参数定标新方法研究”(41071296);“InSAR连接点自动稳健提取理论与方法研究”共同资助(41474010)
通讯作者: 汪宝存     E-mail: 309307201@qq.com
作者简介: 白泽朝(1991-),男,硕士,主要从事InSAR地表形变监测。Email: baizechao1991@163.com。
引用本文:   
白泽朝,汪宝存,靳国旺,徐青,张红敏,刘辉. Sentinel-1A数据矿区地表形变监测适用性分析[J]. 国土资源遥感, 2019, 31(2): 210-217.
Zechao BAI,Baocun WANG,Guowang JIN,Qing XU,Hongmin ZHANG,Hui LIU. Applicability analysis of ground deformation monitoring in mining area by Sentinel - 1A data. Remote Sensing for Land & Resources, 2019, 31(2): 210-217.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.02.29      或      http://www.gtzyyg.com/CN/Y2019/V31/I2/210
Fig.1  相邻影像干涉对分布
Fig.2  实际沉降量随时间变化情况
Fig.3  研究区覆盖范围
Fig.4  区域A裸地时间序列差分干涉图
Fig.5  区域B农田覆盖区时间序列差分干涉图
Fig.6  区域C村落时间序列差分干涉图
Fig.7  相干性变化折线图
Fig.8  验证区的形变条纹
Fig.9  模型验证结果
Fig.10  模型一致性验证结果
[1] 靳国旺, 徐青, 张红敏 . 合成孔径雷达干涉测量[M]. 北京: 国防工业出版社, 2014.
Jin G W, Xu Q, Zhang H M. Synthetic Aperture Radar Interferometry[M]. Beijing: National Defense Industry Press, 2014.
[2] 靳国旺, 张红敏, 徐青 . 雷达摄影测量[M]. 北京: 测绘出版社, 2015.
Jin G W, Zhang H M, Xu Q. Radargrammetry[M]. Beijing: Surveying and Mapping Press, 2015.
[3] 吴立新, 高均海, 葛大庆 , 等. 工矿区地表沉陷D-InSAR监测试验研究[J]. 东北大学学报(自然科学版), 2005,26(8):778-782.
Wu L X, Gao J H, Ge D Q , et al. Experiental study on surface subsidence monitoring with D-InSAR in mining area[J]. Journal of Northeastern University (Natural Science), 2005,26(8):778-782.
[4] 董玉森 , Ge L L, Chang H C, 等. 基于差分雷达干涉测量的矿区地面沉降监测研究[J]. 武汉大学学报(信息科学版), 2007,32(10):888-891.
Dong Y S, Ge L L, Chang H C , et al. Mine subsidence monitoring by differential InSAR[J]. Geomatics and Information Science of Wuhan University, 2007,32(10):888-891.
[5] 朱建军, 邢学敏, 胡俊 , 等. 利用InSAR技术监测矿区地表形变[J]. 中国有色金属学报, 2011,21(10):2564-2576.
Zhu J J, Xing X M, Hu J , et al. Monitoring of ground surface deformation in mining area with InSAR technique[J]. The Chinese Journal of Nonferrous Metals, 2011,21(10):2564-2576.
[6] 汪宝存, 郭凌飞, 王军见 , 等. 矿区地表形变InSAR监测——以永城市为例[J]. 测绘与空间地理信息, 2016,39(6):24-27.
Wang B C, Guo L F, Wang J J , et al. Mining area surface deformation monitoring by InSAR:Taking Yongcheng City as an example[J]. Geomatics and Spatial Information Technology, 2016,39(6):24-27.
[7] 刘广, 郭华东 , Ramon H, 等. InSAR技术在矿区沉降监测中的应用研究[J]. 国土资源遥感, 2008,20(2):51-55.doi: 10.6046/gtzyyg.2008.02.13.
doi: 10.6046/gtzyyg.2008.02.13
Liu G, Guo H D, Ramon H , et al. The application of InSAR technology to mining area subsidence monitoring[J]. Remote Sensing for Land and Resources, 2008,20(2):51-55.doi: 10.6046/gtzyyg.2008.02.13.
doi: 10.6046/gtzyyg.2008.02.13
[8] 廖明生, 王腾 . 时间序列InSAR技术与应用[M]. 北京: 科学出版社, 2014.
Liao M S, Wang T. Time Series InSAR Technology and Application[M]. Beijing: Science Press, 2014.
[9] 田馨 . InSAR技术形变监测中的干涉条件研究[D]. 武汉:武汉大学, 2013.
Tian X . The Study on Interference Conditions Analysis for InSAR in Deformation Monitoring[D]. Wuhan:Wuhan University, 2013.
[10] 葛大庆, 王艳, 范景辉 , 等. 地表形变D-InSAR监测方法及关键问题分析[J]. 国土资源遥感, 2007,19(4):14-22.doi: 10.6046/gtzyyg.2007.04.04.
doi: 10.6046/gtzyyg.2007.04.04
Ge D Q, Wang Y, Fan J H , et al. A study of surface deformation monitoring using differential SAR interferometry technique and an analysis of its key problems[J]. Remote Sensing for Land and Resources, 2007,19(4):14-22.doi: 10.6046/gtzyyg.2007.04.04.
doi: 10.6046/gtzyyg.2007.04.04
[11] 蒋弥, 李志伟, 丁晓利 , 等. InSAR可检测的最大最小变形梯度的函数模型研究[J]. 地球物理学报, 2009,52(7):1715-1724.
doi: 10.3969/j.issn.0001-5733.2009.07.006
Jiang M, Li Z W, Ding X L , et al. A study on the maximum and minimum detectable deformation gradients resolved by InSAR[J]. Chinese Journal of Geophysics, 2009,52(7):1715-1724.
doi: 10.3969/j.issn.0001-5733.2009.07.006
[12] Jiang M, Li Z W, Ding X L , et al. Modeling minimum and maximum detectable deformation gradients of interferometric SAR measurements[J]. International Journal of Applied Earth Observation and Geoinformation, 2011,13(5):766-777.
doi: 10.1016/j.jag.2011.05.007
[13] Baran I, Stewart M, Claessens S . A new functional model for determining minimum and maximum detectable deformation gradient resolved by satellite Radar interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005,43(4):675-682.
doi: 10.1109/TGRS.2004.843187
[1] 陈继伟, 曾琪明, 焦健, 赵斌臣. Sentinel-1A卫星TOPS模式数据的SBAS时序分析方法——以黄河三角洲地区为例[J]. 国土资源遥感, 2017, 29(4): 82-87.
[2] 章钊颖, 鲁奕岑, 吴国周, 王永利. 基于多时相Sentinel-1A SAR数据草原地区降水量反演[J]. 国土资源遥感, 2017, 29(4): 156-160.
[3] 刘斌, 葛大庆, 李曼, 张玲, 王艳, 郭小方, 张晓博. 地基合成孔径雷达干涉测量技术及其应用[J]. 国土资源遥感, 2017, 29(1): 1-6.
[4] 黄燕平, 陈劲松. 基于SAR数据的森林生物量估测研究进展[J]. 国土资源遥感, 2013, 25(3): 7-13.
[5] 陈曦, 张红, 王超. 极化干涉SAR反演植被垂直结构剖面研究[J]. 国土资源遥感, 2009, 21(4): 49-52.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《国土资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 Email:gtzyyg@agrs.cn; gtzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发