时序累积DInSAR与GIS结合的矿区沉降监测与分析
Monitoring and Analysis of Mining Subsidence Based on Timing Accumulation DInSAR and GIS
-
摘要: 为获取长时间序列上矿区地表时空沉降过程并验证其精度,提出一种时序累积DInSAR和GIS分析相结合的矿区地表沉降监测及分析方法。该方法首先选取具有较短时空基线的SAR影像进行二轨DInSAR处理;然后将每组形变图中具有高相干性的点位的地表沉降进行累加;最后,将累计沉降量与GIS空间分析工具相结合,获取矿区地表形变和铁路形变动态发展过程。采用6景高分辨率的RADARSAT-2影像进行了实验,与水准测量数据对比验证的结果表明,该方法监测结果精度可靠,平均绝对误差为0.018 m,最大下沉误差为0.042 m。Abstract: To obtain the space-time settlement process of mining area in long time series and verify its accuracy, we propose a kind of surface subsidence monitoring and analysis method combined timing accumulation DInSAR and GIS analysis. The method firstly selects SAR images with shorter temporal baseline to process two-pass DInSAR, and then accumulates the surface subsidence with a high coherence point in each group of deformation diagram; finally, the method combines the cumulative settlement with GIS spatial analysis tools to obtain the dynamic development of surface subsidence and rail deformation. The test used six-scene high resolution RADARSAT-2 images, and the results comparing with the leveling data shows that the method has reliable detection accuracy, and the mean absolute error is 0.018 m, the maximum subsidence error is 0.042 m.
-
Keywords:
- DInSAR /
- surface subsidence /
- GIS /
- deformation monitoring /
- spatial analysis
-
-
[1] 黄宝伟.基于D-InSAR和GIS技术的煤矿区地面沉降监测研究[D].青岛:中国石油大学(华东),2011. [2] 范洪冬,邓喀中,祝传广,等.基于时序SAR技术的采空区上方高速公路变形监测及预测方法[J].煤炭学报,2012, 37(11):1841-1846. [3] 范洪冬.InSAR若干关键算法及其在地表沉降监测中的应用研究[D].徐州:中国矿业大学, 2010. [4] 师红云.基于时序雷达干涉测量的高速铁路区域沉降变形监测研究[D].北京:北京交通大学,2013. [5] 王志勇,张继贤,黄国满.基于InSAR的济宁矿区沉降精细化监测与分析[J].中国矿业大学学报,2014,43(1):169-174. [6] 刘晓菲,邓喀中,薛继群,等.基于D-InSAR技术的公路采空区变形监测[J].煤矿安全, 2012, 43(8):207-209. [7] Fan H D, Wei G U, Qin Y, et al. A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method[J].Transactions of Nonferrous Metals Society of China, 2014, 24(4):1242-1247. [8] 廖明生,林晖.雷达干涉测量-原理与信号处理基础[M].北京:测绘出版社,2003. [9] 王刘宇,邓喀中,汤志鹏,等.D-InSAR与GIS结合的高速公路变形监测[J].煤炭工程,2015,47(1):121. [10] 陈炳乾,邓喀中,范洪冬.基于D-InSAR技术和SVR算法的开采沉陷监测与预计[J].中国矿业大学学报,2014, 43(5):880-886. [11] 杨俊凯,陈炳乾,邓喀中,等.基于D-InSAR与概率积分法的开采沉陷监测与预计[J].金属矿山, 2015,44(4):195-200.
计量
- 文章访问数: 305
- HTML全文浏览量: 0
- PDF下载量: 0