Support vector machine approach to identifying buildings using multi-temporal ALOS/PALSAR data

References

• Angiulli , G. , Barrile , V. and Cacciola , M. 2005 . SAR imagery classification using multi-class support vector machines . Journal of Electromagnetic Waves and Applications , 19 : 1865 – 1872 .
   Web of Science ®Google Scholar
• Ball , G.H. and Hall , D.J. ISODATA, A Novel Method of Data Analysis and Pattern Classification . NTIS Technical Report AD0699616 . 1965 . Menlo Park, CA: Stanford Research Institute
   Google Scholar
• Bolstad , P.V. and Lillesand , T.M. 1991 . Rapid maximum likelihood classification . Photogrammetric Engineering and Remote Sensing , 57 : 67 – 74 .
   Web of Science ®Google Scholar
• Brown , M. , Gunn , S.R. and Lewis , H.G. 1999 . Support vector machines for optimal classification and spectral unmixing . Ecological Modelling , 120 : 167 – 179 .
   Web of Science ®Google Scholar
• Burges , C.J.C. 1998 . A tutorial on support vector machines for pattern recognition . Data Mining and Knowledge Discovery , 2 : 121 – 167 .
   Web of Science ®Google Scholar
• Camps-Valls , G. , Gómez-Chova , L. , Calpe , J. , Soria , E. , Martin , J.D. , Alonso , L. and Moreno , J. 2004 . Robust support vector technique for hyperspectral data classification and knowledge discovery . IEEE Transactions on Geoscience and Remote Sensing , 42 : 1530 – 1542 .
   Web of Science ®Google Scholar
• Chen , Y. , Shi , P. , Fung , T. , Wang , J. and Li , X. 2007 . Object-oriented classification for urban land cover mapping with ASTER imagery . International Journal of Remote Sensing , 28 : 4645 – 4651 .
   Web of Science ®Google Scholar
• Dell'Acqua , F. and Gamba , P. 2006 . Discriminating urban environments using multiscale texture and multiple SAR images . International Journal of Remote Sensing , 27 : 3797 – 3812 .
   Web of Science ®Google Scholar
• Dong , Y. , Forster , B. and Ticehurst , C. 1997 . Radar backscatter analysis for urban environments . International Journal of Remote Sensing , 18 : 1351 – 1364 .
   Web of Science ®Google Scholar
• Eliason , E.M. and McEwen , A.S. 1990 . Adaptive box filters for removal of random noise from digital images . Photogrammetric Engineering and Remote Sensing , 56 : 453 – 458 .
   Web of Science ®Google Scholar
• Foody , G.M. and Mathur , A. 2004 . Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification . Remote Sensing of Environment , 93 : 107 – 117 .
   Web of Science ®Google Scholar
• Foody , G.M. and Mathur , A. 2006 . The use of small training sets containing mixed pixels for accurate hard image classification: training on mixed spectral responses for classification by a SVM . Remote Sensing of Environment , 103 : 179 – 189 .
   Web of Science ®Google Scholar
• Frost , V.S. , Stiles , J.A. , Schanmugan , K.S. and Holzman , J.C. 1982 . A model for radar images and its application to adaptive digital filtering of multiplicative noise . IEEE Transactions on Pattern Analysis and Machine Intelligence , 4 : 157 – 166 .
   PubMed Web of Science ®Google Scholar
• Fukuda , J. and Hirosawa , H. 2001 . Support vector machine classification of land cover: application to polarimetric SAR . Geoscience and Remote Sensing Symposium, 2001. IGARSS ‘01. IEEE 2001 International , 1 : 187 – 189 .
   Google Scholar
• Gagnon , L. and Jouan , A. 1997 . Speckle filtering of SAR images: a comparative study between complex-wavelet-based and standard filters . Proceedings of SPIE , 3169 : 80 – 91 .
   Google Scholar
• Gao , J. and Skillcorn , D. 1998 . Capability of SPOT XS data in producing detailed land cover maps at the urban-rural periphery . International Journal of Remote Sensing , 19 : 2877 – 2891 .
   Web of Science ®Google Scholar
• Gong , P. and Howarth , P.J. 1990 . The use of structural information for improving land cover classification accuracies at the rural-urban fringe . Photogrammetric Engineering and Remote Sensing , 56 : 67 – 73 .
   Web of Science ®Google Scholar
• Henderson , F.M. and Xia , Z. 1997 . SAR applications in human settlement detection, population estimation and urban land use pattern analysis: a status report . IEEE Transactions on Geoscience and Remote Sensing , 35 : 79 – 85 .
   Web of Science ®Google Scholar
• Huang , C. , Davis , L.S. and Townshend , J.R.G. 2002 . An assessment of support vector machines for land cover classification . International Journal of Remote Sensing , 23 : 725 – 749 .
   Web of Science ®Google Scholar
• Inglada , J. 2007 . Automatic recognition of man-made objects in high resolution optical remote sensing images by SVM classification of geometric image features . ISPRS Journal of Photogrammetry and Remote Sensing , 62 : 236 – 248 .
   Web of Science ®Google Scholar
• Kuan , D.T. , Sawchuk , A.A. , Strand , T.C. and Chavel , P. 1987 . Adaptive restoration of images with speckle . IEEE Transactions on Acoustics, Speech, and Signal Processing , 35 : 373 – 383 .
   Google Scholar
• Lee , J.S. 1980 . Digital image enhancement and noise filtering by use of local statistics . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2 : 165 – 168 .
   PubMed Web of Science ®Google Scholar
• Lhomme , S. , He , D.-C. , Weber , C. and Morin , D. 2009 . A new approach to building identification from very-high-spatial-resolution images . International Journal of Remote Sensing , 30 : 1341 – 1354 .
   Web of Science ®Google Scholar
• Lin , G.C.S. and Ho , S.P.S. 2003 . China's land resources and land-use change: insights from the 1996 land survey . Land Use Policy , 20 : 87 – 107 .
   Web of Science ®Google Scholar
• Long , H. , Heilig , G.K. , Li , X. and Zhang , M. 2007 . Socio-economic development and land-use change: analysis of rural housing land transition in the transect of the Yangtse River, China . Land Use Policy , 24 : 141 – 153 .
   Web of Science ®Google Scholar
• Lopes , A. , Touzi , R. and Nezry , E. 1990 . Adaptive speckle filters and scene heterogeneity . IEEE Transactions on Geoscience and Remote Sensing , 28 : 992 – 1000 .
   Web of Science ®Google Scholar
• Lu , D. and Weng , Q. 2004 . Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery . Photogrammetric Engineering and Remote Sensing , 70 : 1053 – 1062 .
   Web of Science ®Google Scholar
• Lu , D. and Weng , Q. 2006 . Use of impervious surface in urban land-use classification . Remote Sensing of Environment , 102 : 146 – 160 .
   Web of Science ®Google Scholar
• Lu , D. and Weng , Q. 2009 . Extraction of urban impervious surfaces from an IKONOS image . International Journal of Remote Sensing , 30 : 1297 – 1311 .
   Web of Science ®Google Scholar
• Mayunga , S.D. , Coleman , D.J. and Zhang , Y. 2007 . A semi-automated approach for extracting buildings from QuickBird imagery applied to informal settlement mapping . International Journal of Remote Sensing , 28 : 2343 – 2357 .
   Web of Science ®Google Scholar
• Mercier , G. and Lennon , M. 2003 . Support vector machines for hyperspectral image classification with spectral-based kernels . Geoscience and Remote Sensing Symposium, 2003. IGARSS ‘03. IEEE 2003 International , 1 : 288 – 290 .
   Google Scholar
• Pal , M. 2006 . Support vector machine-based feature selection for land cover classification: a case study with DAIS hyperspectral data . International Journal of Remote Sensing , 27 : 2877 – 2894 .
   Web of Science ®Google Scholar
• Pal , M. and Mather , P.M. 2005 . Support vector machines for classification in remote sensing . International Journal of Remote Sensing , 26 : 1007 – 1011 .
   Web of Science ®Google Scholar
• Powell , R.L. , Roberts , D.A. , Dennison , P.E. and Hess , L.L. 2007 . Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil . Remote Sensing of Environment , 106 : 253 – 267 .
   Web of Science ®Google Scholar
• Pu , R. , Gong , P. , Michishita , R. and Sasagawa , T. 2008 . Spectral mixture analysis for mapping abundance of urban surface components from the Terra/ASTER data . Remote Sensing of Environment , 112 : 939 – 954 .
   Web of Science ®Google Scholar
• Qu , G. and Li , J. , eds. 1994 . Population and the Environment in China , Boulder : Lynne Rienner Publications .
   Google Scholar
• Quarmby , N.A. and Cushnie , J.L. 1989 . Monitoring urban land cover changes at the urban fringe from SPOT HRV imagery in south-east England . International Journal of Remote Sensing , 10 : 953 – 963 .
   Web of Science ®Google Scholar
• Rosenqvist , A. , Shimada , M. , Ito , N. and Watanabe , M. 2007 . ALOS PALSAR: a pathfinder mission for global-scale monitoring of the environment . IEEE Transactions on Geoscience and Remote Sensing , 45 : 3307 – 3316 .
   Web of Science ®Google Scholar
• Shannon , C.E. 1948 . A mathematical theory of communication . Bell System Technical Journal , 27 : 379 – 423 .
   Web of Science ®Google Scholar
• Shi , Z. and Fung , K.B. 1994 . A comparison of digital speckle filters . Geoscience and Remote Sensing Symposium, 1994. IGARSS ‘94 , 4 : 2129 – 2133 .
   Google Scholar
• Shölkopf , B. , Sung , K.K. , Burges , C. , Girosi , F. , Niyogi , P. , Poggio , T. and Vapnik , V. 1997 . Comparing support vector machines with Gaussian kernels to radial basis function classifiers . IEEE Transactions on Signal Processing , 45 : 2758 – 2765 .
   Web of Science ®Google Scholar
• Skinner , M.W. , Kuhn , R.G. and Joseph , A.E. 2001 . Agricultural land protection in China: a case study of local governance in Zhejiang Province . Land Use Policy , 18 : 329 – 340 .
   Web of Science ®Google Scholar
• State Statistics Bureau . 2009 . China Statistical Yearbook 2008 , Beijing : Statistical Bureau of the People's Republic of China .
   Google Scholar
• Sumantyo , J.T.S. and Amini , J. 2008 . A model for removal of speckle noise in SAR images (ALOS PALSAR) . Canada Journal of Remote Sensing , 34 : 503 – 515 .
   Web of Science ®Google Scholar
• Tan , C.P. , Koay , J.Y. , Lum , K.S. , Ewe , H.T. and Chuah , H.T. 2007 . Classification of multi-temporal SAR images for rice crops using combined entropy decomposition and support vector machine technique . Progress in Electromagnetics Research , 71 : 19 – 39 .
   Web of Science ®Google Scholar
• Thomas , N. , Hendrix , C. and Congalton , R.G. 2003 . A comparison of urban mapping methods using high-resolution digital imagery . Photogrammetric Engineering and Remote Sensing , 69 : 963 – 972 .
   Web of Science ®Google Scholar
• Tso , B. and Mather , P.M. , eds. 2009 . Classification Methods for Remotely Sensed Data , 2nd , 125 – 154 . Boca Raton , FL : CRC Press .
   Google Scholar
• Van de Voorde , T. , De Genst , W. and Canters , F. 2007 . Improving pixel-based VHR land-cover classifications of urban areas with post-classification techniques . Photogrammetric Engineering and Remote Sensing , 73 : 1017 – 1027 .
   Web of Science ®Google Scholar
• Vapnik , V. , ed. 1995 . The Nature of Statistical Learning Theory , New York : Springer-Verlag .
   Google Scholar
• Vapnik , V. , ed. 1998 . Statistical Learning Theory , New York : John Wiley .
   Google Scholar
• Wu , C. 2004 . Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery . Remote Sensing of Environment , 93 : 480 – 492 .
   Web of Science ®Google Scholar
• Wu , C. 2009 . Quantifying high-resolution impervious surfaces using spectral mixture analysis . International Journal of Remote Sensing , 30 : 2915 – 2932 .
   Web of Science ®Google Scholar
• Yang , H. and Li , X. 2000 . Cultivated land and food supply in China . Land Use Policy , 17 : 73 – 88 .
   Web of Science ®Google Scholar
• Zhang , Q. , Wang , J. , Peng , X. , Gong , P. and Shi , P. 2002 . Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data . International Journal of Remote Sensing , 23 : 3057 – 3078 .
   Web of Science ®Google Scholar
• Zhang , Y. , Wang , C. , Wu , J. , Qi , J. and Salas , A.W. 2009 . Mapping paddy rice with multi-temporal ALOS PALSAR imagery in southeast China . International Journal of Remote Sensing , 30 : 6301 – 6315 .
   Web of Science ®Google Scholar