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| 基于面向对象的高分影像分类研究 | |
| 引用本文： | 宋晓阳,姜小三,江东,黄耀欢,万华伟,王昌佐.基于面向对象的高分影像分类研究[J].遥感技术与应用,2015,30(1):99-105. |
| 作者姓名： | 宋晓阳 姜小三 江东 黄耀欢 万华伟 王昌佐 |
| 作者单位： | (1.南京农业大学资源与环境科学学院,江苏 南京210095； 2.中国科学院地理科学与资源研究所资源利用与环境修复重点实验室,北京100101; 3.环境保护部卫星环境应用中心,北京100094) |
| 基金项目： | 国家自然科学青年基金项目（51309210）,高分重大科技专项“环境保护遥感动态监测信息服务系统”,“高分生态环境遥感监测关键技术研究、系统开发与应用示范”（05-Y30B02-9001-13/15-10）,中国科学院地理资源所自主部署创新项目（2012SJ008-01）。 |
| 摘 要： | 遥感技术已经成为实现地表信息提取的主要手段。以高分辨率影像为主要数据源,采用面向对象的多尺度分割算法,根据对象的光谱、形状等特征,实现了面向高分遥感数据的土地利用分类算法。该算法结合了面向地物对象和综合对象特征的分类方法,充分发挥了高分辨率影像进行精细地物分类的优势,得到了高精度的分类结果。通过西双版纳纳板河流域国家级自然保护区实例验证表明:该算法总体精度达到88.58%,Kappa系数达到0.77,精度符合应用要求,能够实现土地利用高精度、快速的分类。 |
| 关 键 词： | 面向对象 多尺度分割 土地利用分类 高分辨影像 |
| 收稿时间： | 2013-12-23 |
Object-oriented Classification of High-resolution Remote Sensing Image |
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| Affiliation: | (1.Resources & Environment Science Department,Nanjing Agricultural University,Nanjing 210095,China;; 2.State Key Lab of Natural Resources and Environmental Security,Institute of Geographic Sciences and; Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;; 3.Satellite Environment Center,Ministry of Environmental Protection,Beijing 100094,China) |
| Abstract: | Remote sensing technology has become the main means to achieve the extraction of ground information.Based on high\|resolution remote sensing image,this paper adopted multi\|scale segmentation algorithm and measured the characters of object spectrum and shape to realize the object\|oriented classification method.The classification method was a combination of object\|oriented method and comprehensively analyzes the features of objects,give full paly to the advantage of the fine features classification of high\|resolution remote sensing image,so that high precision classification results were obtained.The method was tested in Nabanhe River Watershed Nature Reserve,Xishuangbanna,then the method was checked by the total accuracy of classification result reached to 88.58% and Kappa coefficient was 0.77.The method was a high\|precision and rapid classification method. |
| Keywords: | Object-oriented Multi-scale segmentation Land use classification High-resolution Remote Sensing image |
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