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遥感技术与应用
图像与数据处理     
基于特征选择的土地整理地物识别规则的动态提取
吴健生1,2,林 倩1,李卫锋3,刘建政3,彭 建2
(1.北京大学深圳研究生院城市人居环境科学与技术重点实验室,广东 深圳 518055; 2.北京大学城市与环境学院地表过程与模拟教育部重点实验室,北京 100871; 3.香港大学城市规划与设计系,香港)
The Dynamic Extraction of Classification Rules for Land Consolidation through Object-oriented Features Space Optimization
Wu Jiansheng1,2,Lin Qian1,Li Weifeng3,Liu Jianzhen3,Peng Jian2
(1.Key Laboratory for Environmental and Urban Sciences,Shenzhen Graduate School, Peking University,Shenzhen 518055,China; 2.Key Laboratory for Earth Surface Processes,Ministry of Education,College of Urban and Environmental Sciences,Peking University,Beijing 100871,China; 3.Department of Urban Planning and Design,The University of Hongkong,Hongkong,China)
 全文: PDF(4015 KB)  
摘要: 高分辨率遥感影像是精确提取土地整理区地表信息的重要数据来源,提出了一种基于面向对象的规则动态提取方法,借鉴生物学中的遗传定理和人工免疫系统理论,使计算机依据样本信息和影像特征自动进行知识挖掘,提取分类规则以供用户修改与分类。最后结合模糊分类得到的分类结果显示:总体精度从传统方法的40%提高 到基于遗传算法的86%与基于人工免疫算法的90%,Kappa系数也由传统方法的0.3提高到基于遗传算法的0.82与基于人工免疫算法的0.89。结果表明:该方法不仅提高了便捷性与通用性,改变了以往规则提取需要用户大量的试验和先验知识的局面,而且试验结果也表明对于分类精度有显著的提高,对于在土地整理工程中利用高分辨率遥感影像进行地物识别与监测有重要的意义。
关键词: 土地整理特征选择高分辨率遥感影像面向对象遗传算法人工免疫算法    
Abstract: The high resolution remote sensing image is an important data sources for the accurate extraction of land consolidation area surface information.In this paper,a new object-based method,combining with genetic algorithm and artificial immune algorithm,is used to extract classification rules based on the characteristics of the sample image.After fuzzy classification,the results show that overall accuracy is increasing from 40% by traditional method to 86% corresponding to the genetic algorithm and 90% corresponding to the artificial immune algorithm,and the Kappa coefficient is increasing from 0.3 by traditional methods to 0.82 corresponding to the genetic algorithm and 0.89 corresponding to the artificial immune algorithm.All in all,not only this method can improve the convenience and versatility,changing the previous situation that the rule extraction requires users a large amount of priori knowledge and testing,but also the test results show the significant improvement in classification accuracy.Therefore,it has an important significance for land consolidation,especially using the high-remote sensing images for feature identifying and monitoring.
Key words: Land consolidation    Feature selection    High-resolution remote sensing image    Object-based    Genetic algorithm    Artificial immune algorithm
收稿日期: 2012-10-15 出版日期: 2014-03-14
:  TP 79  
基金资助: 国家自然科学基金项目(41271101)资助。
通讯作者: 林 倩(1989-),女,浙江宁波人,硕士研究生,主要从事遥感与景观生态学方面的研究。E-mail:ciaralin@126.com。   
作者简介: 吴健生(1965-),男,湖南新化人,教授,主要从事景观生态与GIS方面的研究。E-mail:wujs@pkusz.edu.cn。
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吴健生,林 倩,李卫锋,刘建政,彭 建. 基于特征选择的土地整理地物识别规则的动态提取[J]. 遥感技术与应用, .

Wu Jiansheng,Lin Qian,Li Weifeng,Liu Jianzhen,Peng Jian. The Dynamic Extraction of Classification Rules for Land Consolidation through Object-oriented Features Space Optimization . Remote Sensing Technology and Application, .

链接本文:

http://www.rsta.ac.cn/CN/        http://www.rsta.ac.cn/CN/Y2013/V28/I5/799

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