浏览全部资源
扫码关注微信
Received：18 October 2019，
Published：07 October 2021
移动端阅览
永久散射体识别是用PS-InSAR方法获取地面沉降数据的关键环节之一，其最佳阈值的设定直接影响PS点的精度和密度。本文基于大数据统计的分析方法——ROC曲线法定量分析和确定PS点识别的最佳阈值。选择3种典型的PS识别方法，绘制每种方法在不同阈值条件下的ROC曲线图，当ROC曲线下面积越大，方法越优。依据最佳阈值位于ROC曲线左上部位的特征，采用敏感度与特异度之和（
Se
+
Sp
）最大的方法可定量判定出最佳阈值的取值。在最佳阈值条件下，识别的PS点具有正选率足够高、误选率足够小，PS点的密度足够大的特性。为进一步验证该方法的可行性，本文以北京龙潭公园地区为PS识别的实验区，用振幅离差指数法、相关系数法，以及两种阈值相结合的双阈值法3种方法进行实验识别PS点，并根据ROC曲线判得3种方法的最佳阈值。研究结果发现：（1）振幅离差
T
D
识别PS点的最佳阈值为0.45；相干系数
Tγ
识别PS点的最佳阈值为0.45；振幅离差
T
D
、相干系数
Tγ
双重阈值识别PS点的最佳阈值（
T
D
，
Tγ
）为（0.50，0.50）。（2）用振幅离差
T
D
和相干系数
Tγ
双阈值法识别PS点，得到的ROC曲线下面积AUC=0.762，高于单阈值法，表明双重阈值法识别PS点优于单一阈值的PS点识别方法。研究表明ROC曲线可定量化确定PS点的最佳阈值，而且该方法可进一步推广于GIS空间分析、遥感解译过程中阈值的定量化筛选。
Permanent Scatterer (PS) identification is a key step in the PS-InSAR technology
which is mainly used for obtaining ground subsidence data. The density and accuracy of the PS points are determined by setting the optimal threshold of PS identification. Receiver Operating Characteristic (ROC) curve is used to quantitatively analyze and determine the optimal threshold for PS identification.
The ROC curve is drawn with some thresholds of every PS identification algorithm. According to the ROC curve
the larger area under the ROC curve indicates that the PS recognition method is more reliable. When the area under the ROC curve is sufficiently large
the optimal threshold of PS identification
which is the closest to the upper left of the ROC curve
is determined quantitatively according to the maximum sum of the sensitivity and specificity of the ROC curve. The positive ratio of PS points is sufficiently high
the false positive ratio of PS points is sufficiently low
and the density of the PS point is sufficient
using the optimal threshold.
The PS points are identified with 60 X-band TerraSAR-X images (2010—2017) by three algorithms as amplitude dispersion (
T
D
)
correlation coefficient (
T
γ
)
and dual-threshold (
T
D
T
γ
) with amplitude dispersion index (ADI) and correlation coefficient index (CCI). The experimental area is approximately Beijing Longtan Park. First
three ROC curves are drawn separately with the algorithms ADI
CCI
and dual-threshold. Second
the optimal thresholds of every algorithm have been calculated according to the maximum sum of the sensitivity and specificity of ROC curve. Research found that: (1) the optimal threshold of ADI is
T
D
=0.45; the optimal threshold of CCI is
T
γ
=0.45; the optimal threshold of dual-threshold of ADI and CCI is (
T
D
T
γ
) = (0.50
0.50). (2) The area under the ROC curve of dual threshold is AUC=0.762
which is higher than the AUC of the single threshold algorithm
such as ADI and CCI. Evidently the dual-threshold algorithm is much better than the single threshold of ADI or CCI to identify the PS points.
Result of this research shows that the ROC curve can not only quantitatively determine the optimal threshold of PS identification
but can also be further applied for the quantitative selection of the thresholds during GIS spatial analysis and remote sensing image interpretation.
Baker A M , Hsu F C and Gayzik F S . 2018 . A method to measure predictive ability of an injury risk curve using an observation-adjusted area under the receiver operating characteristic curve . Journal of Biomechanics , 72 : 23 - 28 [ DOI: 10.1016/j.jbiomech.2018.02.018 http://dx.doi.org/10.1016/j.jbiomech.2018.02.018 ]
Bianchini S , Del Soldato M , Solari L , Nolesini T , Pratesi F and Moretti S . 2016 . Badland susceptibility assessment in volterra municipality (Tuscany, Italy) by means of GIS and statistical analysis . Environmental Earth Sciences , 75 ( 10 ): 889 [ DOI: 10.1007/s12665-016-5586-5 http://dx.doi.org/10.1007/s12665-016-5586-5 ]
Bianchini S , Solar L , Del Soldato M , Raspini F , Montalti R , Ciampalini A and Casagli N . 2019 . Ground subsidence susceptibility (GSS) mapping in Grosseto plain (Tuscany, Italy) based on satellite Insar data using frequency ratio and fuzzy logic . Remote Sensing , 11 ( 17 ): 2015 [ DOI: 10.3390/rs11172015 http://dx.doi.org/10.3390/rs11172015 ]
Chen Q , Liu G X , Li Y S and Ding X L . 2006 . Automated detection of permanent scatterers in radar interferometry: algorithm and testing results . Acta Geodaetica et Cartographica Sinica , 35 ( 2 ): 112 - 117
陈强 , 刘国祥 , 李永树 , 丁晓利 . 2006 . 干涉雷达永久散射体自动探测——算法与实验结果 . 测绘学报 , 35 ( 2 ): 112- 117 [ DOI: 10.3321/j.issn:1001-1595.2006.02.004 http://dx.doi.org/10.3321/j.issn:1001-1595.2006.02.004 ]
Crosetto M , Monserrat O , Cuevas-González M , Devanthéry M and Crippa M . 2016 . Persistent scatterer interferometry: a review . ISPRS Journal of Photogrammetry and Remote Sensing , 115 : 78 - 89 [ DOI: 10.1016/j.isprsjprs.2015.10.011 http://dx.doi.org/10.1016/j.isprsjprs.2015.10.011 ]
Fawcett T . 2006 . An introduction to ROC analysis . Pattern Recognition Letters , 27 ( 8 ): 861 - 874 [ DOI: 10.1016/j.patrec.2005.10.010 http://dx.doi.org/10.1016/j.patrec.2005.10.010 ]
Ferretti A , Fumagalli A , Novali F , Prati C , Rocca F and Rucci A . 2011 . A new algorithm for processing interferometric data-stacks: squeeSAR . IEEE Transactions on Geoscience and Remote Sensing , 49 ( 9 ): 3460 - 3470 [ DOI: 10.1109/TGRS.2011.2124465 http://dx.doi.org/10.1109/TGRS.2011.2124465 ]
Ferretti A , Prati C and Rocca F . 2000 . Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry . IEEE Transactions on Geoscience and Remote Sensing , 38 ( 5 ): 2202 - 2212 [ DOI: 10.1109/36.868878 http://dx.doi.org/10.1109/36.868878 ]
Ferretti A , Prati C and Rocca F . 2001 . Permanent scatterers in SAR interferometry . IEEE Transactions on Geoscience and Remote Sensing , 39 ( 1 ): 8 - 20 [ DOI: 10.1109/36.898661 http://dx.doi.org/10.1109/36.898661 ]
Giannecchini R , Galanti , Y , D’Amato Avanzi G and Barsanti M . 2016 . Probabilistic rainfall thresholds for triggering debris flows in a human-modified landscape . Geomorphology , 257 : 94 - 107 [ DOI: 10.1016/j.geomorph.2015.12.012 http://dx.doi.org/10.1016/j.geomorph.2015.12.012 ]
Han J , Lai T , Zhao Y J and Huang J . 2015 . Method on PS detection of small dataset PS-DInSAR . Journal of Signal Processing , 31 ( 6 ): 679 - 685
韩洁 , 赖涛 , 赵拥军 , 黄洁 . 2015 . 小数据集PS-DInSAR的PS点探测方法 . 信号处理 , 31 ( 6 ): 679- 685 [ DOI: 10.3969/j.issn.1003-0530.2015.06.007 http://dx.doi.org/10.3969/j.issn.1003-0530.2015.06.007 ]
Hanley J A and McNeil B J . 1982 . The meaning and use of the area under a receiver operating characteristic (ROC) curve . Radiology , 143 ( 1 ): 29 - 36 [ DOI: 10.1148/radiology.143.1.7063747 http://dx.doi.org/10.1148/radiology.143.1.7063747 ]
Heleno S I N , Oliveira L G S , Henriques M J , Falcão A P , Lima J N P , Cooksley G , Ferretti A , Fonseca A M , Lobo-Ferreira J P and Fonseca J F B D . 2011 . Persistent Scatterers Interferometry detects and measures ground subsidence in Lisbon . Remote Sensing of Environment , 115 ( 8 ): 2152 - 2167 [ DOI: 10.1016/j.rse.2011.04.021 http://dx.doi.org/10.1016/j.rse.2011.04.021 ]
Hooper A , Zebker H , Segall P and Kampes B . 2004 . A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers . Geophysical Research Letters , 31 ( 23 ): L 23611 [ DOI: 10.1029/2004GL021737 http://dx.doi.org/10.1029/2004GL021737 ]
Li G Y , Zhang R , Liu G X , Yu B , Zhang B , Dai K R , Bao J W and Wei B W . 2018 . Land subsidence detection and analysis over Beijing-Tianjin-Hebei area based on Sentinel-1A TS-DInSAR . Journal of Remote Sensing , 22 ( 4 ): 633 - 646
李广宇 , 张瑞 , 刘国祥 , 于冰 , 张波 , 戴可人 , 包佳文 , 韦博文 . 2018 . Sentinel-1A TS-DInSAR京津冀地区沉降监测与分析 . 遥感学报 , 22 ( 4 ): 633- 646 [ DOI: 10.11834/jrs.20187196 http://dx.doi.org/10.11834/jrs.20187196 ]
Liu G X , Jia H G , Nie Y J , Li T , Zhang R , Yu B and Li Z L . 2014 . Detecting subsidence in coastal areas by ultrashort-baseline TCPInSAR on the time series of high-resolution TerraSAR-X images . IEEE Transactions on Geoscience and Remote Sensing , 52 ( 4 ): 1911 - 1923 [ DOI: 10.1109/TGRS.2013.2256428 http://dx.doi.org/10.1109/TGRS.2013.2256428 ]
Lobo J M , Jiménez-Valverde A and Real R . 2008 . AUC: a misleading measure of the performance of predictive distribution models . Global Ecology and Biogeography , 17 ( 2 ): 145 - 151 [ DOI: 10.1111/j.1466-8238.2007.00358.x http://dx.doi.org/10.1111/j.1466-8238.2007.00358.x ]
Long S C , Li T and Feng T . 2011 . Study on selection of PS point targets . Journal of Geodesy and Geodynamics , 31 ( 4 ): 144 - 148
龙四春 , 李陶 , 冯涛 . 2011 . 永久散射体点目标提取方法研究 . 大地测量与地球动力学 , 31 ( 4 ): 144- 148 [ DOI: 10.3969/j.issn.1671-5942.2011.04.033 http://dx.doi.org/10.3969/j.issn.1671-5942.2011.04.033 ]
Luo X J , Huang D F and Liu G X . 2007 . Automated detection of permanent scatterers in time serial differential radar interferometry . Journal of Southwest Jiaotong University , 42 ( 4 ): 414 - 418
罗小军 , 黄丁发 , 刘国祥 . 2007 . 时序差分雷达干涉中永久散射体的自动探测 . 西南交通大学学报 , 42 ( 4 ): 414- 418 [ DOI: 10.3969/j.issn.0258-2724.2007.04.006 http://dx.doi.org/10.3969/j.issn.0258-2724.2007.04.006 ]
Narayan A B , Tiwari A , Dwivedi R and Dikshit O . 2018 . A novel measure for categorization and optimal phase history retrieval of distributed scatterers for InSAR applications . IEEE Transactions on Geoscience and Remote Sensing , 56 ( 10 ): 5843 - 5849 [ DOI: 10.1109/TGRS.2018.2826842 http://dx.doi.org/10.1109/TGRS.2018.2826842 ]
Nie Y J , Liu G X , Shi J F , Yu B and Cheng P G . 2013 . Application of PSI technique in deformation monitoring . Science of Surveying and Mapping , 38 ( 2 ): 80 - 83, 97
聂运菊 , 刘国祥 , 石金峰 , 于冰 , 程朋根 . 2013 . PSI技术在地表形变监测中的应用研究 . 测绘科学 , 38 ( 2 ): 80 - 83 , 97 [ DOI: 10.16251/j.cnki.1009-2307.2013.02.041 http://dx.doi.org/10.16251/j.cnki.1009-2307.2013.02.041 ]
Nykänen V , Lahti I , Niiranen T and Korhonen K . 2015 . Receiver operating characteristics (ROC) as validation tool for prospectivity models—A magmatic Ni-Cu case study from the Central Lapland Greenstone Belt, northern Finland . Ore Geology Reviews , 71 : 853 - 860 [ DOI: 10.1016/j.oregeorev.2014.09.007 http://dx.doi.org/10.1016/j.oregeorev.2014.09.007 ]
Sun W W , Li F , Yang G and Zhang D F . 2018 . Hyperspectral anomaly detection using column-wise robust principal component analysis . Journal of Remote Sensing , 22 ( 3 ): 458 - 465
孙伟伟 , 李飞 , 杨刚 , 张殿发 . 2018 . 列式鲁棒主成分分析的高光谱遥感异常探测 . 遥感学报 , 22 ( 3 ): 458- 465 [ DOI: 10.11834/jrs.20187284 http://dx.doi.org/10.11834/jrs.20187284 ]
Wang X . 2013 . Big Data Analysis: Methods and Applications . Beijing : Tsinghua University Press : 28 - 29
王星 . 2013 . 大数据分析: 方法与应用 . 北京 : 清华大学出版社 : 28 - 29
Wu S B , Zhang L , Ding X L and Perissin D . 2019 . Pixel-wise MTInSAR estimator for integration of coherent point selection and unwrapped phase vector recovery . IEEE Transactions on Geoscience and Remote Sensing , 57 ( 5 ): 2659 - 2668 [ DOI: 10.1109/TGRS.2018.2876115 http://dx.doi.org/10.1109/TGRS.2018.2876115 ]
Wu W , Li A D , He X H , Ma R , Liu H B and Lv J K . 2018 . A comparison of support vector machines, artificial neural network and classification tree for identifying soil texture classes in southwest China . Computers and Electronics in Agriculture , 144 : 86 - 93 [ DOI: 10.1016/j.compag.2017.11.037 http://dx.doi.org/10.1016/j.compag.2017.11.037 ]
Xia L K , Fu W Z , Huang Q H and Xia C X . 2016 . Research on PS selection method of GB-SAR images based on dual-thresholding algorithm . Site Investigation Science and Technology , ( 5 ): 17 - 21, 40
夏磊凯 , 付五洲 , 黄其欢 , 夏晨翔 . 2016 . 基于双阈值法的地基合成孔径雷达影像永久散射体选取方法研究. 勘察科学技术, (5): 17 - 21 , 40 [ DOI: 10.3969/j.issn.1001-3946.2016.05.005 http://dx.doi.org/10.3969/j.issn.1001-3946.2016.05.005 ]
Xu L F , Wang S Z and Wang B S . 2011 . The method of solving the optimal tangent point by ROC curve . Chinese Journal of Health Statistics , 28 ( 6 ): 701 - 702, 705
徐林发 , 汪素珍 , 王柏省 . 2011 . 应用ROC曲线求解最佳切点的方法介绍 . 中国卫生统计 , 28 ( 6 ): 701 - 702 , 705 [ DOI: 10.3969/j.issn.1002-3674.2011.06.030 http://dx.doi.org/10.3969/j.issn.1002-3674.2011.06.030 ]
Zebker H A and Villasenor J . 1992 . Decorrelation in interferometric radar echoes . IEEE Transactions on Geoscience and Remote Sensing , 30 ( 5 ): 950 - 959 [ DOI: 10.1109/36.175330 http://dx.doi.org/10.1109/36.175330 ]
相关文章
相关作者
相关机构
京公网安备11010802024621