高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于递归纹理特征消除的WorldView-2树种分类

刘怀鹏 安慧君 王冰 张秋良

刘怀鹏, 安慧君, 王冰, 张秋良. 基于递归纹理特征消除的WorldView-2树种分类[J]. 北京林业大学学报, 2015, 37(8): 53-59. doi: 10.13332/j.1000-1522.20140311
引用本文: 刘怀鹏, 安慧君, 王冰, 张秋良. 基于递归纹理特征消除的WorldView-2树种分类[J]. 北京林业大学学报, 2015, 37(8): 53-59. doi: 10.13332/j.1000-1522.20140311
LIU Huai-peng, AN Hui-jun, WANG Bing, ZHANG Qiu-liang. Tree species classification using WorldView-2 images based on recursive texture feature elimination[J]. Journal of Beijing Forestry University, 2015, 37(8): 53-59. doi: 10.13332/j.1000-1522.20140311
Citation: LIU Huai-peng, AN Hui-jun, WANG Bing, ZHANG Qiu-liang. Tree species classification using WorldView-2 images based on recursive texture feature elimination[J]. Journal of Beijing Forestry University, 2015, 37(8): 53-59. doi: 10.13332/j.1000-1522.20140311

基于递归纹理特征消除的WorldView-2树种分类

doi: 10.13332/j.1000-1522.20140311
基金项目: 

内蒙古自然科学基金重点项目(20080404Zd10)

详细信息
    作者简介:

    刘怀鹏,博士生。主要研究方向:3S技术应用与资源监测评价。Email:1476829808@qq.com 地址:010019内蒙古自治区呼和浩特市新建东街275号内蒙古农业大学林学院。

    责任作者:

    安慧君,教授,博士生导师。主要研究方向:3S技术应用与资源监测评价。Email:dean6928@sohu.com 地址:同上。

Tree species classification using WorldView-2 images based on recursive texture feature elimination

  • 摘要: 利用遥感影像识别树种是一个尚未解决的科学难题,传统方法在高分辨率影像树种分类中存在着诸多不适宜问题。本文通过提取WorldView-2影像的纹理特征构造高维数据,利用递归特征消除降低数据维数,逐步解除最大似然分类的休斯现象,并将有代表性的纹理特征集合与光谱特征结合,对树种进行分类。结果显示:在递归消除8个纹理特征后,最大似然的休斯现象达到了很好的规避;在结合光谱特征后,分类的总体精度达到了86.39%,Kappa系数达到了0.8410,比基于光谱特征的总体精度和Kappa系数高12.32%和0.1436。研究表明,在高维数据中通过递归特征消除规避最大似然分类的休斯现象,充分结合影像纹理与光谱信息对树种分类可以取得更为理想的结果。

     

  • [1] ZHANG L. Study on the hyperspectral remote sensed image classify based on PCA and SVM[J]. Optical Technique, 2008, 34(Suppl.):184-187.
    [1] MCPHERSON E G, NOWAK D J, ROWNTREE R A. Chicago's urban forest ecosystem: results of the Chicago Urban Forest Climate Project[M].Radnor, PA: Department of Agriculture, Forest Service, Northeastern Forest Experiment Station,1994.
    [2] GOUGEON F A, LECKIE D G. The individual tree crown approach applied to Ikonos images of a coniferous plantation area [J]. Photogrammetric Engineering and Remote Sensing, 2006,72:1287-1297.
    [2] YUAN L H,FU L,YANG Y, et al. Analysis of texture feature extracted by gray level co-occurrence matrix [J]. Journal of Computer Applications, 2009, 29(4): 1018-1021.
    [3] HEUMANN B W. An object-based classification of mangroves using a hybrid decision tree-support vector machine approach[J]. Remote Sensing, 2011, 3(11): 2440-2460.
    [3] LUO J C, WANG Q M, MA J H, et al. The EM-based maximum likelihood classifier for remotely sensed data[J]. Acta Geodaetica et Cartographica Sinica, 2002,31(3):234-239.
    [4] ZHANG H K, HUANG B, YU L. Kernel function in SVM-RFE based hyperspectral data band selection[J]. Remote Sensing Technology and Application, 2013,28(5):747-752,17.
    [4] IMMITZER M,ATZBERGER C,KOUKL T. Tree species classification with random forest using very high spatial resolution 8-Band WorldView-2 satellite data[J]. Remote Sensing, 2012,4:2661-2693.
    [5] IMMITZER M, ATZBERGER C, KOUKL T. Suitability of WorldView-2 data for tree species classification with special emphasis on the four new spectral bands[J]. Photogrammetrie, Fernerkundung, Geoinformation, 2012, 5:573-588.
    [6] PU R, LANDRY S.A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species[J]. Remote Sensing of Environment, 2012, 124:516-533.
    [7] CHO M A, MATHIEU R, ASNER G P, et al. Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system[J]. Remote Sensing of Environment, 2012,125:214-226.
    [8] PEERBHAY K Y, MUTANGA O, ISMAIL R. Investigating the capability of few strategically placed WorldView-2 multispectral bands to discriminate forest species in KwaZulu-Natal, South Africa[J]. IEEE Geoscience & Remote Sensing Society, 2013, 7(1): 307-316.
    [9] DENG S Q, KATOH M,GUAN QW, et al. Interpretation of forest resources at the individual tree level at Purple Mountain, Nanjing City, China, using WorldView-2 imagery by combining GPS, RS and GIS technologies[J]. Remote Sensing, 2014, 6(1):87-110.
    [10] GHOSH A, JOSHI P K. A comparison of selected classification algorithms for mapping bamboo patches in lower Gangetic plains using very high resolution WorldView-2 imagery[J]. International Journal of Applied Earth Observation and Geoinformation, 2014, 26:298-311.
    [11] CLARK M L, ROBERTS D A, CLARK D B. Hyperspectral discrimination of tropicalrain forest tree species at leaf to crown scales[J]. Remote Sensing of Environment, 2005, 96(3-4):375-398.
    [12] 张亮.基于PCA和SVM的高光谱遥感图像分类研究[J].光学技术,2008,34(增刊):184-187.
    [13] 苑丽红,付丽,杨勇,等.灰度共生矩阵提取纹理特征的实验结果分析[J].计算机应用,2009,29(4):1018-1021.
    [14] RYHERD S, WOODCOCK C E. Combining spectral and texture data in the segmentation of remotely sensed image[J]. Pohtorgammetric Engineering and Remote Sensing, 1997, 62:181-194.
    [15] 骆剑承,王钦敏,马江洪,等.遥感图像最大似然分类方法的EM改进算法[J].测绘学报,2002,31(3):234-239.
    [16] GYSELS E, RENEVEY P, CELKA P. SVM-based recursive feature elimination to compare phase synchronization computed from broadband and narrowband EEG signals in brain-computer interfaces[J]. Signal Processing, 2005, 85(11):2178-2189.
    [17] 张汉奎,黄波,俞乐.SVM-REF高光谱数据波段选择中核函数的研究[J].遥感技术与应用,2013,28(5):747-752,17.
    [18] SIMARD M,DE GRANDI G,SAATCHI S, et al. Mapping tropical coastal vegetation using JERS-1 and ERS-l radar data with a decision tree classifier[J]. International Journal of Remote Sensing, 2002,23(7):1461-1474.
    [19] PAL M, MATHER P M. Support vector machines for classification in remote sensing[J]. International Journal of Remote Sensing, 2005,26(5):1007-1011.
  • 加载中
计量
  • 文章访问数:  974
  • HTML全文浏览量:  89
  • PDF下载量:  22
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-09-15
  • 修回日期:  2014-09-15
  • 刊出日期:  2015-08-31

目录

    /

    返回文章
    返回