| 融合D-InSAR与GIS技术的矿区开采沉陷形变监测及预测方法 |
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| 引用本文： | 陈银翠,徐良骥,余礼仁.融合D-InSAR与GIS技术的矿区开采沉陷形变监测及预测方法[J].测绘通报,2019,0(7):54-58,63. |
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| 作者姓名： | 陈银翠 徐良骥 余礼仁 |
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| 作者单位： | 安徽矿业职业技术学院,安徽淮北235000;安徽理工大学,安徽淮南232001;安徽理工大学,安徽淮南,232001 |
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| 基金项目： | 安徽省对外科技合作计划项目（150306020） |
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| 摘 要： | 针对合成孔径雷达差分干涉测量（D-InSAR）技术能监测大范围地表形变信息，但单一的D-InSAR技术不能精确分析沉降分布的范围和位置的问题，本文以淮北袁店二矿为例，首先选择2015年4—5月2景C波段Radarsat-2和7—12月6景Sentinel-1卫星影像数据作为干涉影像数据构成6个干涉影像对，通过二轨法对其进行差分干涉处理和相位解缠提取干涉形变图；然后将D-InSAR差分干涉图与开采平面、开采计划图导入ArcGIS进行叠加，分析矿区开采沉陷区域的空间动态分布位置并进行定量分析；最后采用灰色理论模型进行预测。结果表明：D-InSAR叠加分析图能反映出在煤炭开采过程中沉降区域位置和分布范围；D-InSAR预测值与实测值最大相对误差和方差比分别为11.5%和0.097。
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| 关 键 词： | D-InSAR 干涉影像对 GIS 叠加分析 灰色理论模型 |
| 收稿时间： | 2018-12-27 |
The method of mining subsidence deformation monitoring and prediction based on D-InSAR with GIS technology |
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| CHEN Yincui,XU Liangji,YU Liren.The method of mining subsidence deformation monitoring and prediction based on D-InSAR with GIS technology[J].Bulletin of Surveying and Mapping,2019,0(7):54-58,63. |
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| Authors: | CHEN Yincui XU Liangji YU Liren |
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| Institution: | 1. Anhui College of Mining Technology, Huaibei 235000, China;2. Anhui University of Science and Technology, Huainan 232001, China |
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| Abstract: | Synthetic aperture radar differential interferometry (D-InSAR) technology can monitor large-scale surface deformation information, but a single D-InSAR technique cannot accurately analyze the range and location of the settlement distribution.Firstly, we selected two images of the C-band Radarsat-2 from July to December and the six-monthly Sentinel-1 images from April to May 2015 as the number of interference images. According to the composition of the six interferometric pairs, they were differentially interpolated by the second-track method. Processing and phase unwrapping to extract interferograms. The D-InSAR differential interferograms were imported into ArcGIS with mining planes and mining plan maps to analyze the spatial dynamic distribution of mining subsidence areas in the mining area and quantitative analysis. And finally using a grey theoretical model prediction.The results show that the D-InSAR overlay analysis can reflect the location and distribution of the settlement area during coal mining. The maximum relative error and variance ratio between the predicted and measured D-InSAR values are 11.5% and 0.097 respectively. |
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| Keywords: | D-InSAR interference image pair GIS overlay analysis GM |
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