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DInSAR technique for three-dimensional coastal spit simulation from Radarsat-1 fine mode data

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Języki publikacji
EN
Abstrakty
EN
This work presents a new approach to 3D spit simulation using differential synthetic aperture interferometry (DInSAR). In doing so, conventional DInSAR procedures are implemented to three repeat passes of RADARSAT-1 SAR fine mode data (F1). Further, a new application of using fuzzy B-spline algorithm is implemented with phase unwrapping technique. The study shows that the performance of DInSAR method using fuzzy B-spline is better than the DInSAR technique, which is vali- dated by the coefficient of determination r² of 0.96, probability p of 0.002, and accuracy (RMSE) of ± 0.034 m, with 90 per cent confidence intervals. In conclusion, integration of fuzzy B-spline with phase unwrapping produces an accurate 3D coastal geomorphology reconstruction.
Czasopismo
Rocznik
Strony
478--493
Opis fizyczny
Bibliogr. 29 poz.
Twórcy
autor
  • Institute for Science and Technology Geospatial (INSTeG), University of Technology, Malaysia (UTM), Skudai, Johor Bahru, Malaysia, maged@utm.my
Bibliografia
  • Anile, A.M., S. Deodato, and G. Privitera (1995), Implementing fuzzy arithmetic, Fuzzy Set. Syst. 72, 2, 239-250, DOI: 10.1016/0165-0114(94)00355-B.
  • Anile, A.M., B. Falcidieno, G. Gallo, M. Spagnuolo, and S. Spinello (2000), Modeling uncertain data with fuzzy B-splines, Fuzzy Set. Syst. 113, 3, 397-410, DOI: 10.1016/S0165-0114(98)00146-8.
  • Askne, J., M. Santoro, G. Smith, and J.E.S. Fransson (2003), Multitemporal repeatpass SAR interferometry of boreal forests, IEEE Trans. Geosci. Remote Sens. 41, 7, 1540-1550, DOI: 10.1109/TGRS.2003.813397.
  • Bürgmann, R., P.A. Rosen, and E.J. Fielding (2000), Synthetic aperture radar interferometry to measure Earth’s surface topography and its deformation, Ann. Rev. Earth Plan. Sci. 28, 169-209, DOI: 10.1146/annurev.earth.28.1.169.
  • Dall, J. (2007), InSAR elevation bias caused by penetration into uniform volumes, IEEE Trans. Geosci. Remote Sens. 45, 7, 2319-2324, DOI: 10.1109/TGRS. 2007.896613.
  • Fan, H., K. Deng, C. Ju, C. Zhu, and J. Xue (2011), Land subsidence monitoring by D-InSAR technique, Min. Sci. Technol. (China) 21, 6, 869-872, DOI: 10.1016/j.mstc.2011.05.030.
  • Fuchs, H., Z.M. Kedem, and S.P. Uselton (1977), Optimal surface re construction from planar contours, Commun. ACM 20, 10, 693-702, DOI: 10.1145/359842.359846.
  • Gens, R. (2000), The influence of input parameters on SAR interferometric processing and its implication on the calibration of SAR interferometric data, Int. J. Remote Sens. 21, 8, 1767-1771, DOI: 10.1080/014311600210056.
  • Hanssen, R.F. (2001), Radar Interferometry: Data Interpretation and Error Analysis, Kluwer Academic Publ., Dordrecht.
  • Lee, H. (2001), Interferometric synthetic aperture radar coherence imagery for land surface change detection, Ph.D. Thesis, University of London.
  • Luo, X., F. Huang, and G. Liu (2006), Extraction co-seismic Deformation of Bam earthquake with Differential SAR Interferometry, J. New Zea. Inst. Surv. 296, 20-23.
  • Marghany, M. (2011), Three-dimensional visualisation of coastal geomorphology using fuzzy B-spline of dinsar technique, Int. J. Phys. Sci. 6, 30, 6967-6971, DOI: 10.5897/IJPS11.768.
  • Marghany, M. (2012), 3-D coastal bathymetry simulation from airborne TOPSAR polarized data. In: P. Blondel (ed.), Bathymetry and Its Applications, In-Tech Open Access Publisher, University Campus STeP Ri, Croatia, 57-76.
  • Marghany, M., and M. Hashim (2009), Differential synthetic aperture radar interferometry (DINSAR) for 3D coastal geomorphology reconstruction, Int. J. Comput. Sci. Network Secur. 9, 5, 59-63.
  • Marghany, M., and M. Hashim (2010a), Different polarised topographic synthetic aperture radar (TOPSAR) bands for shoreline change mapping, Int. J. Phys. Sci. 5, 12, 1883-1889.
  • Marghany, M., and M. Hashim (2010b), Velocity bunching and Canny algorithms for modelling shoreline change rate from synthetic aperture radar (SAR), Int. J. Phys. Sci. 5, 12, 1908-1914.
  • Marghany, M., A.P. Cracknell, and M. Hashim (2010a), 3-D visualizations of coastal bathymetry by utilization of airborne TOPSAR polarized data, Int. J. Dig. Earth 3, 2, 187-206, DOI: 10.1080/17538940903477406.
  • Marghany, M., Z. Sabu, and M. Hashim (2010b), Mapping coastal geomorphology changes using synthetic aperture radar data, Int. J. Phys. Sci. 5, 12, 1890-1896.
  • Massonnet, D., and K.L. Feigl (1998), Radar interferometry and its application to changes in the Earth’s surface, Rev. Geophys. 36, 4, 441-500, DOI: 10.1029/97RG03139.
  • Nizalapur, V., R. Madugundu, and C. Shekhar Jha (2011), Coherence-based land cover classification in forested areas of Chattisgarh, Central India, Rusing environmental satellite – advanced synthetic aperture radar data, J. Appl. Remote Sens. 5, 059501-1-059501-6, DOI: 10.1117/1.3557816.
  • RADARSAT International (2012), RADARSAT application, available online from http:\www.rsi.ca.
  • Rao, K.S., and H.K. Al-Jassar (2010), Error analysis in the digital elevation model of Kuwait desert derived from repeat pass synthetic aperture radar interferometry, J. Appl. Remote Sens. 4, 1-24, DOI: 10.1117/1.3504170.
  • Rao, K.S., H.K. Al-Jassar, S. Phalke, Y.S. Rao, J.P. Muller, and Z. Li (2006), A study on the applicability of repeat-pass SAR interferometry for generating DEMs over several Indian test sites, Int. J. Remote Sens. 27, 3, 595-616, DOI: 10.1080/01431160500239248.
  • Rövid, A., A.R. Várkonyi-Koczy, and P. Várlaki (2004), 3D model estimation from multiple images. In: IEEE Int. Conf. on Fuzzy Systems FUZZ-IEEE’2004, 25-29 July 2004, Budapest, Hungary, 1661-1666, DOI: 10.1109/FUZZY.2004.1375430.
  • Russo, F. (1998), Recent advances in fuzzy techniques for image enhancement, IEEE Trans. Instrum. Meas. 47, 6, 1428-1434, DOI: 10.1109/19.746707.
  • Sumantyo, J.T.S., M. Shimada, P. Mathieu, and H.Z. Abidin (2012), Long-term consecutive DInSAR for volume change estimation of land deformation, IEEE Trans. Geosci. Remote Sens. 50, 1, 259-270, DOI: 10.1109/TGRS.2011.2160455.
  • Yang, J., T. Xiong, and Y. Peng (2007), A fuzzy approach to filtering interferometric SAR data, Int. J. Remote Sens. 28, 6, 1375-1382, DOI: 10.1080/01431160600740715.
  • Zebker, H.A., C.L. Werner, P.A. Rosen, and S. Hensley (1994), Accuracy of topographic maps derived from ERS-1 interferometric radar, IEEE Trans. Geosci. Remote Sens. 32, 4, 823-836, DOI: 10.1109/36.298010.
  • Zebker, H.A., P.A. Rosen, and S. Hensley (1997), Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps, J. Geophys. Res. 102, B4, 7547-7563, DOI: 10.1029/96JB03804.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL1-0025-0029
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