基于高分二号数据的面向对象城市土地利用分类研究
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摘要
利用国产高分二号数据提取城市地物类别的方法研究具有重要的意义。以鸡西市城区作为研究区域,采用高分二号(GF-2)遥感影像为数据源,对影像进行多尺度分割,建立相应地物的分类规则,采用规则集的面向对象分类方法对地物进行分类,并与支持向量机(Support Vector Machine,SVM)监督分类结果进行比较。实验结果发现:利用面向对象方法对城市土地利用分类的总体精度92.52%,Kappa系数为0.91,与SVM方法相比较,有很大的提高,分类效果更加能体现城市地类形状特征。使用面向对象的分类方法对高分二号影像进行分类效果更好,精度更高,基于高分二号数据面向对象分类方法是提取城市土地利用分类的有效方法。
It is of great significance to study the method of extracting urban features from GF-2 remote sensing data.Taking the urban area of Jixi City as the study area,and the GF-2 image is used as the data source.The image is divided into multiple scales,the classification rules of the corresponding objects are established,and the object-based classification method of the rule set is used to classify the objects.Compare with SVM supervised classification results.The results show that the overall accuracy of object-oriented classification is 92.52%,and the Kappa coefficient is 0.91,which is significantly higher than the SVM supervised classification.Using the object-oriented classification method to classify the GF-2 image is better and the precision is higher.Object-oriented classification method based on GF-2 data is an effective method for extracting urban land use classification.
It is of great significance to study the method of extracting urban features from GF-2 remote sensing data.Taking the urban area of Jixi City as the study area,and the GF-2 image is used as the data source.The image is divided into multiple scales,the classification rules of the corresponding objects are established,and the object-based classification method of the rule set is used to classify the objects.Compare with SVM supervised classification results.The results show that the overall accuracy of object-oriented classification is 92.52%,and the Kappa coefficient is 0.91,which is significantly higher than the SVM supervised classification.Using the object-oriented classification method to classify the GF-2 image is better and the precision is higher.Object-oriented classification method based on GF-2 data is an effective method for extracting urban land use classification.
引文
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[24] Chen Jie,Shao Quanbin,Mei Xiaoming,et al.Object-based Urban Road Extraction from High Resolution Imagery with Space-scale Theory[J].Engineering of Surveying and Mapping,2016,25(12):5-11.[陈杰,邵权斌,梅小明,等.结合尺度空间的面向对象高分辨率影像城市道路提取[J].测绘工程,2016,25(12):5-11.]
[25] Pu Zhi,Liu Ping,Yang Liao,et al.Study on Extraction of Urban Green Space Using Object-oriented Classification Method[J].Journal of Fujian Forestry Science and Technology,2006,33(1):40-44.[蒲智,刘萍,杨辽,等.面向对象技术在城市绿地信息提取中的应用[J].福建林业科技,2006,33(1):40-44.]
[26] Zhao Yuluan,Lin Aiwen.Urban Land Cover Classification Research based on Object- oriented and Multi-scale Image Segmentation Techniques:A Case Study of Downtown Area of Wuhan City[J].Scientific and Technological Management of Land and Resources,2008,25(5):90-95.[赵宇鸾,林爱文.基于面向对象和多尺度影像分割技术的城市用地分类研究——以武汉市城市中心区为例[J].国土资源科技管理,2008,25(5):90-95.]
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[28] Zhang Jun,Zhu Guolong,Li Yan.Scale Effect and Optimal Scale in Object-oriented Information Extraction of High Spatial Resolution Remote Sensing Image[J].Science of Surveying and Mapping,2011,36(2):107-109.[张俊,朱国龙,李妍.面向对象高分辨率影像信息提取中的尺度效应及最优尺度研究[J].测绘科学,2011,36(2):107-109.]
[29] Shi Peirong,Chen Youfu,Liu Hua,et al.Optimized Methodology for Classification of Remote Sensing Images based on Object-oriented:Application to the Typical Forest of Milin in Tibet[J].Remote Sensing Technology and Application,2017,32(3):466-474.[施佩荣,陈永富,刘华,等.基于改进的面向对象遥感影像分类方法研究——以西藏米林县典型林区为例[J].遥感技术与应用,2017,32(3):466-474.]
[30] Sun Zhongping,Bai Jinting,Shi Yuanli,et al.Object-oriented Detection of Land Use Changes based on High Spatial Resolution Remote Sensing Image[J].Transactions of The Chinese Society of Agricultural Machinery,2015(Sup.1):297-303.[孙中平,白金婷,史园莉,等.基于高分影像的面向对象土地利用变化检测方法研究[J].农业机械学报,2015(增刊1):297-303.]
[2] Liu Dandan,Liu Jiang,Zhang Yujuan,et al.Research on the Extracting Buildings from the High Spatial Resolution Images based on the Object-oriented and Multi-scale Method[J].Geomatics & Spatial Information Technology,2016,39(6):17-20.[刘丹丹,刘江,张玉娟,等.面向对象的多尺度高分影像建筑物提取方法研究[J].测绘与空间地理信息,2016,39(6):17-20.]
[3] Sun Xiaoyan,Du Huaqiang,Han Ning,et al.Multi-scale Segmentation,Object-based Extraction of Moso Bamboo Forest from SPOT5 Imagery[J].Scientia Silvae Sinicae,2013,49(10):80-87.[孙晓艳,杜华强,韩凝,等.面向对象多尺度分割的SPOT5影像毛竹林专题信息提取[J].林业科学,2013,49(10):80-87.]
[4] Han Shanshan,Li Haitao,Gu Haiyan.The Study on Land Use Change Detection based on Object-oriented Analysis[J].Remote Sensing Information,2009(3):23-29.[韩闪闪,李海涛,顾海燕.面向对象的土地利用变化检测方法研究[J].遥感信息,2009(3):23-29.]
[5] Liu Jiayu.Classification of Urban Land Using Object-oriented Information Extraction Technology[J].Western Resources,2016(4):156-159.[刘佳雨.利用面向对象的信息提取技术进行城市用地分类[J].西部资源,2016(4):156-159.]
[6] Zhou Chunyan,Wang Ping,Zhang Zhenyong,et al.Classification of Urban Land based on Object-oriented Information Extraction Technology[J].Remote Sensing Technology and Application,2008,23(1):31-35.[周春艳,王萍,张振勇,等.基于面向对象信息提取技术的城市用地分类[J].遥感技术与应用,2008,23(1):31-35.]
[7] Miao Chen,Ding Jianli,Zhan Yulin,et al.Extraction of Soil Salinization in Arid Area base on GF-2 Dada:A Case Study in Ebinur Lake Basin[J].Journal of Guilin University of Technology,2018,38(1):69-77.[缪琛,丁建丽,占玉林,等.基于GF-2数据的田间尺度盐渍化提取——以新疆艾比湖流为例[J].桂林理工大学学报,2018,38(1):69-77.]
[8] Chen Wenqian,Ding Jianli,Wang Jiao,et al.Classification Method of Land Cover based on GF-1 Image[J].Arid Land Geography,2016,39(1):182-189.[陈文倩,丁建丽,王娇,等.基于高分一号影像的土地覆被分类方法初探[J].干旱区地理,2016,39(1):182-189.]
[9] Li Cunjun,Liu Liangyun,Wang Jiyun,et al.IKONOS Shadow Extraction in Urban Region based on Principal Component Fusion Information Distortion[J].Geomatics and Information Science of Wuhan University,2008,33(9):947-950.[李存军,刘良云,王纪华,等.基于主成分融合信息失真的城市IKONOS 影像阴影自动提取研究[J].武汉大学学报(信息科学版),2008,33(9):947-950.]
[10] Liu Shuhan,Gu Xingfa,Yu Tao,et al.Object-oriented Classification Method based on GF-1 Multi-spectral Remote Sensing Image[J].Science of Surveying and Mapping,2014,39(12):91-94.[刘书含,顾行发,余涛,等.高分一号多光谱遥感数据的面向对象分类[J].测绘科学,2014,39(12):91-94.]
[11] Yuan Ze.Research on Segmentation Scale of Information Extraction with Towns based on GF-2 Image[D].Urumqi:Xinjiang University,2016.[袁泽.基于GF-2遥感影像的城镇地物信息提取分割尺度研究[D].乌鲁木齐:新疆大学,2016.]
[12] Geneletti D,Gorte B G H.A Method for Object-oriented Land Cover Classification Combining Landsat TM Data and Aerial Photographs[J].International Journal of Remote Sensing,2003,24(6):1273-1286.
[13] Liu J,Li P,Wang X .A New Segmentation Method for Very High Resolution Imagery Using Spectral and Morphological Information[J].ISPRS Journal of Photogrammetry & Remote Sensing,2015,101(6):145-162.
[14] Shen Zhanfeng,Luo Jiancheng,Hu Xiaodong,et al.A Mean Shift Multi-scale Segmentation for High-resolution Remote Sensing Images[J].Geomatics and Information Science of Wuhan University,2010,35(3):313-317.[沈占锋,骆剑承,胡晓东,等.高分辨率遥感影像多尺度均值漂移分割算法研究[J].武汉大学学报(信息科学版),2010,35(3):313-317.]
[15] Jia Yonghong,He Yanlin.Boundary Extraction Method of Herbage Wetland based on Multi-source Data[J].Journal of Geomatics,2018,43(4):48-50.[贾永红,何彦霖.基于多源数据的草本湿地边界提取方法[J].测绘地理信息,2018,43(4):48-50.]
[16] Liu Q,Huang C,Liu G,et al.Comparison of CBERS-04,GF-1,and GF-2 Satellite Panchromatic Images for Mapping Quasi-Circular Vegetation Patches in the Yellow River Delta,China[J].Sensors,2018,18(8):2733.doi:10.3390/s18082733.
[17] Lu C,Yang X,Wang Z,et al.Using Multi-level Fusion of Local Features for Land-use Scene Classification with High Spatial Resolution Images in Urban Coastal Zones[J].International Journal of Applied Earth Observation and Geoinformation,2018,70:1-12.
[18] Song J,Lin T,Li X,et al.Mapping Urban Functional Zones by Integrating Very High Spatial Resolution Remote Sensing Imagery and Points of Interest:A Case Study of Xiamen,China[J].Remote Sensing,10(11):1737.doi:10.3390/rs10111737.
[19] Wang Junhai,Ruan Renzong,Chai ying,et al.Object-oriented Urban Water Information Extraction based on GF-2[J].Geospatial Information,2018,16(9):10,34-37,40.[王俊海,阮仁宗,柴颖,等.基于高分二号的面向对象城市水体信息提取[J].地理空间信息,2018,16(9):10,34-37,40.]
[20] Wang Lei,Yang Wunian,Ren Jintong,et al.Object-oriented Extraction Method of Typical Urban Features based on GF-2 Images[J].Bulletin of Surveying and Mapping,2018,(1):138-142.[王蕾,杨武年,任金铜,等.GF-2影像面向对象典型城区地物提取方法[J].测绘通报,2018,(1):138-142.]
[21] Sun Rui,Wang Hongguang,Li Junhui,et al.Optimal Scale Selection and Evaluation for Urban Object Classification based on GF-1 and GF-2 Satellite Imagery[J].Geomatics and Spatial Geographic Information,2018,41(10):171-175.[孙瑞,王洪光,李俊辉,等.基于国产高分卫星面向对象城市地物最优尺度选择及评价研究[J].测绘与空间地理信息,2018,41(10):171-175.]
[22] Chen Yepei,Sun Kaimin,Bai Ting,et al.Quality Assessment on Image Fusion Methods for GF-2 Data[J].Science of Surveying and Mapping,2017,42(11):35-40.[陈业培,孙开敏,白婷,等.高分二号影像融合方法质量评价[J].测绘科学,2017,42(11):35-40.]
[23] Huang Huanhuan,Huang Wanli.An Object-oriented Approach to the Classification of Urban Land-use[J].Journal of Fujian Normal University (Natural Science Edition),2014(6):96-102.[黄欢欢,黄万里.基于面向对象分类方法的城市用地类型提取[J].福建师范大学学报(自然科学版),2014(6):96-102.]
[24] Chen Jie,Shao Quanbin,Mei Xiaoming,et al.Object-based Urban Road Extraction from High Resolution Imagery with Space-scale Theory[J].Engineering of Surveying and Mapping,2016,25(12):5-11.[陈杰,邵权斌,梅小明,等.结合尺度空间的面向对象高分辨率影像城市道路提取[J].测绘工程,2016,25(12):5-11.]
[25] Pu Zhi,Liu Ping,Yang Liao,et al.Study on Extraction of Urban Green Space Using Object-oriented Classification Method[J].Journal of Fujian Forestry Science and Technology,2006,33(1):40-44.[蒲智,刘萍,杨辽,等.面向对象技术在城市绿地信息提取中的应用[J].福建林业科技,2006,33(1):40-44.]
[26] Zhao Yuluan,Lin Aiwen.Urban Land Cover Classification Research based on Object- oriented and Multi-scale Image Segmentation Techniques:A Case Study of Downtown Area of Wuhan City[J].Scientific and Technological Management of Land and Resources,2008,25(5):90-95.[赵宇鸾,林爱文.基于面向对象和多尺度影像分割技术的城市用地分类研究——以武汉市城市中心区为例[J].国土资源科技管理,2008,25(5):90-95.]
[27] Zhu Hongchun,Cai Lijie,Liu Haiying,et al.Optimal Segmentation Scale Calculation for High-resolution Remote Sensing Image[J].Science of Surveying and Mapping,2015,40(3):71-75.[朱红春,蔡丽杰,刘海英,等.高分辨率影像分类的最优分割尺度计算[J].测绘科学,2015,40(3):71-75.]
[28] Zhang Jun,Zhu Guolong,Li Yan.Scale Effect and Optimal Scale in Object-oriented Information Extraction of High Spatial Resolution Remote Sensing Image[J].Science of Surveying and Mapping,2011,36(2):107-109.[张俊,朱国龙,李妍.面向对象高分辨率影像信息提取中的尺度效应及最优尺度研究[J].测绘科学,2011,36(2):107-109.]
[29] Shi Peirong,Chen Youfu,Liu Hua,et al.Optimized Methodology for Classification of Remote Sensing Images based on Object-oriented:Application to the Typical Forest of Milin in Tibet[J].Remote Sensing Technology and Application,2017,32(3):466-474.[施佩荣,陈永富,刘华,等.基于改进的面向对象遥感影像分类方法研究——以西藏米林县典型林区为例[J].遥感技术与应用,2017,32(3):466-474.]
[30] Sun Zhongping,Bai Jinting,Shi Yuanli,et al.Object-oriented Detection of Land Use Changes based on High Spatial Resolution Remote Sensing Image[J].Transactions of The Chinese Society of Agricultural Machinery,2015(Sup.1):297-303.[孙中平,白金婷,史园莉,等.基于高分影像的面向对象土地利用变化检测方法研究[J].农业机械学报,2015(增刊1):297-303.]
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