用L波段和C波段SAR数据研究汶川地震的同震形变
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摘要
结合ALOS PALSAR和EnvisatASAR监测汶川震区同震形变场的示例验证L波段和C波段SAR数据集的优缺点。实验结果表明L波段数据集更适于地形起伏较大、高植被覆盖地区的地表形变监测,尤其在形变梯度较大的区域,PALSAR影像不易引起干涉图中的条纹混叠现象,便于相位解缠,从而提高观测精度。
It describes the results of the ground motion monitoring over Wenchuan earthquake sites in the southwest of China with the ALOS PALSAR and ENVISAT ASAR sensors based on the differential interferometric synthetic aperture radar(DInSAR) technique.In recent the C-band data were mainly used to detect the ground deformation,but the results of interferometry are limited by high vegetated areas and rugged terrains.The study purpose is to demonstrate that these constraints decrease significantly at L-band data due to its spatial resolution and the longer wavelength.The real and simulated data also show L-band data sets are more appropriate for detecting the deformation over the rugged terrain and high vegetation area.Especially,for the large deformation gradient area,PALSAR images are not likely to generate interferometric phase aliasing which goes against the phase unwrap.
It describes the results of the ground motion monitoring over Wenchuan earthquake sites in the southwest of China with the ALOS PALSAR and ENVISAT ASAR sensors based on the differential interferometric synthetic aperture radar(DInSAR) technique.In recent the C-band data were mainly used to detect the ground deformation,but the results of interferometry are limited by high vegetated areas and rugged terrains.The study purpose is to demonstrate that these constraints decrease significantly at L-band data due to its spatial resolution and the longer wavelength.The real and simulated data also show L-band data sets are more appropriate for detecting the deformation over the rugged terrain and high vegetation area.Especially,for the large deformation gradient area,PALSAR images are not likely to generate interferometric phase aliasing which goes against the phase unwrap.
引文
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5 JPL.SRTM home page.http://www.jpl.nasa.gov/srtm/
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7 Massonnet D,Feigl KL.Radar interferometry and its appli-cation to changes in the Earth’s surface[J].American Geo-phys.Union,1998,36(4):441-500.
8 Chen C W and Zebker H A.Phase unwrapping for largeSAR interferograms:statistical segmentation and generalizednetwork models[J].IEEE Transactions on Geoscience andRemote Sensing 2002,40(8):1 709-1 719.
9 Liao M S,et al.Reconstruction of DEMs From ERS-1/2Tandem Data in Mountainous Area Facilitated by SRTMDa-ta[J].IEEE Transactions on Geoscience and Remote Sens-ing,2007,45(7):2325-2335.
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11 Hanssen R H.Radar interferometry-data interpretation anderror analysis[M].Netherlands:Kluwer Academic Publish-ers,2001.
12孙健宝,等.汶川Ms8.0地震InSAR形变观测及初步分析[J].地质地震,2008,30(3):789-795.
13 GE L,et al.Preliminary results of satellite radar interferom-etry for the co-seismic deformation of the 12 May 2008Ms8.0 Wenchuan earthquake[J].Journal of GeographicInformation Science,2008,14(1):12-19.
14 Zebker H A and John V.Decorrelation in interferometricradar echoes[J].IEEE Transactions on Geoscience andRemote Sensing,1992,30(5):950-959.
15 Bamler R and Hartl P.Synthetic aperture radar interferom-etry.Inverse Problems,1998,14(4):1-54.
2 Zebker A,Rosen Hand Hensley P AS.Atmospheric effectsin interferometric synthetic aperture radar surface deforma-tion and topographic maps[J].Geophys.Res.1997,102:7 547-7 563.
3 Satoshi Fujiwara and Rosen P A.Crustal deformation meas-urements using repeat-passs JERS1 synthetic aperture radarinterferometry near the Izu Peninsula[J].Journal of Geo-physical Reseach,1998,103(B2):2 411-2 426.
4 Wegmuller U,et al.Monitoring of mining induced surfacedeformation using L-band SAR interferometry.2005 IEEEInternational Geoscience and Remote Sensing SymposiumIGARSS,2005,3:2 165-2 168.
5 JPL.SRTM home page.http://www.jpl.nasa.gov/srtm/
6 Baran I S,Stewart M and Claessens S.A new functionalmodel for determining minimum and maximum detectable de-formation gradient resolved by satellite radar interferometry[J].IEEE Transactions on Geoscience and Remote Sens-ing,2005,43(4):675~682.
7 Massonnet D,Feigl KL.Radar interferometry and its appli-cation to changes in the Earth’s surface[J].American Geo-phys.Union,1998,36(4):441-500.
8 Chen C W and Zebker H A.Phase unwrapping for largeSAR interferograms:statistical segmentation and generalizednetwork models[J].IEEE Transactions on Geoscience andRemote Sensing 2002,40(8):1 709-1 719.
9 Liao M S,et al.Reconstruction of DEMs From ERS-1/2Tandem Data in Mountainous Area Facilitated by SRTMDa-ta[J].IEEE Transactions on Geoscience and Remote Sens-ing,2007,45(7):2325-2335.
10 Wegmuller Uand Werner C.Gamma documentation-user’sguide,differential interferometry and geocoding software-DIFF&GEO[S].Version1.0-November 2007.
11 Hanssen R H.Radar interferometry-data interpretation anderror analysis[M].Netherlands:Kluwer Academic Publish-ers,2001.
12孙健宝,等.汶川Ms8.0地震InSAR形变观测及初步分析[J].地质地震,2008,30(3):789-795.
13 GE L,et al.Preliminary results of satellite radar interferom-etry for the co-seismic deformation of the 12 May 2008Ms8.0 Wenchuan earthquake[J].Journal of GeographicInformation Science,2008,14(1):12-19.
14 Zebker H A and John V.Decorrelation in interferometricradar echoes[J].IEEE Transactions on Geoscience andRemote Sensing,1992,30(5):950-959.
15 Bamler R and Hartl P.Synthetic aperture radar interferom-etry.Inverse Problems,1998,14(4):1-54.
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