面向对象分类方法在铁尾矿堆快速提取中的应用研究
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摘要
以黄石市大冶铁矿区为例,利用面向对象分类方法进行铁尾矿堆信息快速提取试验研究。首先,根据WorldView-2影像特点,充分利用其丰富的光谱特征及精确的空间形状特征进行图像分割,突出影像对象边缘、重现地物实际存在情况;其次,分析影像对象的光谱、形状、纹理、拓扑关系等特征信息,建立分类规则进行分类,提取出尾矿堆信息。为了进一步提高分类精度,可以利用eCognition软件RS/GIS数据集成功能,在面向对象分类结果上进行目视解译。试验证明,面向对象分类方法适用于提取矿区尾矿堆信息,是高分辨率遥感影像自动分类的理想选择。
Taking Daye iron deposit in Huangshi as an example,it extracted the information of the iron tailing pile with object-oriented classification method.First of all,the WorldView-II image was segmented by its rich spectral feature and precise special shape feature to enhance the edge of objects and the relative location of the objects;secondly,analyzing the spectrum,shape,texture and topological relation of the objects,to establish the classification rule,and then extracted the gangue information.In order to improve the accuracy of classification,it could use the RS/GIS data integration function of eCognition,to make visual interpretation based on results of object-oriented classification.The experiment had proved that the object-oriented classification method is appropriate for extracting the information of iron tailing pile and it is the best choice of automatic classification of high-resolution remote sensing image.
Taking Daye iron deposit in Huangshi as an example,it extracted the information of the iron tailing pile with object-oriented classification method.First of all,the WorldView-II image was segmented by its rich spectral feature and precise special shape feature to enhance the edge of objects and the relative location of the objects;secondly,analyzing the spectrum,shape,texture and topological relation of the objects,to establish the classification rule,and then extracted the gangue information.In order to improve the accuracy of classification,it could use the RS/GIS data integration function of eCognition,to make visual interpretation based on results of object-oriented classification.The experiment had proved that the object-oriented classification method is appropriate for extracting the information of iron tailing pile and it is the best choice of automatic classification of high-resolution remote sensing image.
引文
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[2]夏平,李学亚,刘斌.尾矿的资源化综合利用[J].矿业快报,2006(5):10-12.
[3]Ketting.R.L,Landgrebe.D.A.Computer classification of remotely sensed multispetral image data by extraction andclassification of homogeneous object[J].IEEE Transactions on Geoscience Electronics,1976,14(l):19-26.
[4]Lobo A,Chic O,Casterad A.Classification of mediterranean crops with multi-sensor data:Per-pixel versus per-object sta-tistics and image segmentation[J].International Journal of Remote Sensing,1996,17(12):2385-2400.
[5]Aplin P,Atkinson P,Curran P.Per-field classification of land use using the forthcoming very fine resolution satellite sen-sors:Problems and potential solutions[C]//Advances in Remote Sensing and GIS Analysis.Chichester:Wiley&Sons,1999:219-239.
[6]Baatz M,Schape A.Object-oriented and multi-scale image analysis in semantic networks[C]//Proc of the 2nd Interna-tional Symposium on Operationalization of Remote Sensing.1999.
[7]Hofmann P.Detecting buildings and roads from IKONOS data using additional elevation information[J].GeoBIT/GIS,2001(6):28-33.
[8]HuangHuiPing,WuBingfang,FanJinlong.Analysis to the relationship of classification accuracy segmentation scale imageresolution[C]//IGARSS.2003:3671-3673.
[9]张建国,李宪文,吴延磊.面向对象的冬小麦种植面积遥感估算研究[J].农业工程学报,2008,24(5):156-160.
[10]刘常娟,杨敏华,张秀英.面向对象的分类方法在土地利用数据库建设中的应用[J].测绘科学,2009,34(1):176-177.
[11]孙晓霞,张继贤,刘正军.利用面向对象的分类方法从IKONOS全色影像中提取河流和道路[J].测绘科学,2006,31(1):61-63.
[12]曾涛,杨武年,黎小东,等.面向对象的高空间分辨率遥感影像信息提取—汶川地震城市震害房屋案例研究[J].自然灾害学报,2010,19(5):81-87.
[13]魏飞鸣.基于对象信息的遥感影像分类研究[D].电子科技大学,2008.
[14]黄惠萍.面向对象影像分析中的尺度问题研究[D].中国科学院遥感应用研究所,2003.
[15]陈秋晓,骆剑承,周成虎,等.基于多特征的遥感影像分类方法[J].遥感学报,2004,8(3):239-245.
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