Abstract：In the present paper, the urban land change in Jiading district of Shanghai was studied on the basis of high accuracy classification for 4 epochs of multispectral remotely sensed imageries. A further improved genetic-algorithm optimized back propagation neural network approach was first employed in our study to obtain sorts of land cover types from the remotely sensed imageries. The urban land and non-urban land types were thus extracted based on the classification result. According to the 16 corresponding relationships between the pixel values in the four urban land imageries and the ones in the generated urban land change imagery, the amount of each type pixel in the generated imagery was calculated according to the four plates, and the situation of urban land change was analyzed and investigated for the study area in three year intervals. The urban development in the study area was also preliminarily revealed.
Key words：Genetic algorithms;Neural network classification;Remote sensing;Urban land
童小华，张 学，刘妙龙. 基于多光谱遥感影像分类的城镇用地变化研究[J]. 光谱学与光谱分析, 2009, 29(08): 2131-2135.
TONG Xiao-hua,ZHANG Xue,LIU Miao-long. Urban Land Use Change Detection Based on High Accuracy Classification of Multispectral Remote Sensing Imagery . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(08): 2131-2135.
[1] Crump B, Finnie T W. NTIS，U.S. Department of Commerce. Tenn.: Nashville，1967. 73. [2] John J P. Professional Geographer，1981，33(2):163. [3] Mcconnell K E. Northeastern Journal of Agricultural and Resource Economics，1989，18:63. [4] Epstein J，Payne K，Kramer E. Photogrammetric Engineering and Remote Sensing，2002，68(9):913. [5] Maktav D，Erbek F S，Jürgens C. International Journal of Remote Sensing，2005，26(4):655. [6] Jat M K，Grag P K，Khare D. International Journal of Applied Earth Observation and Geoinformation，2008, 10(1): 26. [7] Harris P M，Ventura S J. Photogrammetric Engineering and Remote Sensing，1995，61(8):993. [8] Omatu S，Yoshida T. Neural Networks，IEEE International Joint Conference on 18-21 November, 1991，4:652. [9] Benediktsson J A，Swain P H，Ersoy O K. IEEE Transactions on Geoscience and Remote Sensing，1990，28(4):540. [10] Foody G M，Arora M K. International Journal of Remote Sensing，1997，18:799. [11] JIA Yong-hong (贾永红). Bulletin of Surveying and Mapping(测绘通报)，2000，(7):7. [12] Toshniwal M. IEEE Proceedings of Networking, Sensing and Control on 19-22 March, 2005. 235. [13] Widyanto M R，Nobuhara H，Kawamoto K, et al. Applied Soft Computing，2005，6(1):72. [14] Nicola’s G P，Domingo O B，Ce’sar H M. Neural Networks，2006，19:514. [15] SUN Xiao-gang，YUAN Gui-bin，DAI Jing-min(孙晓刚，原桂彬，戴景民). Spectroscopy and Spectral Analysis(光谱学与光谱分析)2007，27(2):213. [16] Liu Z J，Liu A X，Wang C Y. Future Generation Computer Systems，2004, 20:1119. [17] TONG Xiao-hua，ZHANG Xue, LIU Miao-long(童小华，张 学，刘妙龙). Journal of Tongji University·Natural Science(同济大学学报·自然科学版)，2008，36(7):985. [18] XIE Huan，TONG Xiao-hua，QIU Yan-ling，et al(谢 欢，童小华，仇雁翎，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2007，27(8):1574. [19] Lillesand T M，Kiefer R W，Chipman J W. Remote Sensing and Image Interpretation，Fourth Edition. New York:John Wiley & Sons. Inc，2003. [20] Congalton R G. Remote Sensing of Environment，1991，37:35.
