张 超,李智晓,李鹏山,杨建宇,朱德海.基于高分辨率遥感影像分类的城镇土地利用规划监测[J].农业机械学报,2015,46(11):323-329.
Zhang Chao,Li Zhixiao,Li Pengshan,Yang Jianyu,Zhu Dehai.Urban rural Land Use Plan Monitoring Based on High Spatial Resolution Remote Sensing Imagery Classification[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(11):323-329.
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基于高分辨率遥感影像分类的城镇土地利用规划监测   [下载全文]
Urban rural Land Use Plan Monitoring Based on High Spatial Resolution Remote Sensing Imagery Classification   [Download Pdf][in English]
投稿时间:2015-04-21  
DOI:10.6041/j.issn.1000-1298.2015.11.044
中文关键词:  城镇土地利用规划 监测 高分辨率遥感影像 WorldView 2 面向对象分类 CART决策树
基金项目:北京市科技计划资助项目(Z141100000614001)
作者单位
张 超 中国农业大学 
李智晓 中国农业大学 
李鹏山 中国农业大学 
杨建宇 中国农业大学
国土资源部农用地质量与监控重点实验室 
朱德海 中国农业大学
国土资源部农用地质量与监控重点实验室 
中文摘要:城镇土地利用规划是城镇化健康有序推进的基础,规划实施监测是其实施的保障。遥感和GIS相结合的方法可快速监测城镇土地利用规划实施情况,保障土地利用规划实施的动态管理。利用0.5m分辨率的WorldView 2卫星遥感影像,采用面向对象的影像分析方法,针对基于知识规则分类特征选取及阈值确定难点,将CART决策树与面向对象分类方法结合,实现参与分类最优对象特征的选择以及特征阈值的自动确定。在分类基础上,对每个规划图斑计算地类规划实施完成率,实现对土地利用规划实施过程进行监测评价。最后,以北京市房山区某区域为研究区,进行了试验验证。结果表明:最终分类总体精度达0.89,Kappa系数为0.87,表明构建的分类算法基本能满足城镇土地利用规划监测的需求。研究区东北部土地利用规划实施情况比西部好,公共绿地、水域等地类需重点调查监测,同时二类居住用地的建筑密度偏高,绿化率偏低。
Zhang Chao  Li Zhixiao  Li Pengshan  Yang Jianyu  Zhu Dehai
China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University;Key Laboratory for Agricultural Land Quality, Monitoring and Control, Ministry of Land and Resources and China Agricultural University;Key Laboratory for Agricultural Land Quality, Monitoring and Control, Ministry of Land and Resources
Key Words:Urban-rural land use plan Monitoring High spatial resolution remote sensing imagery WorldView 2 Object oriented classification CART decision tree
Abstract:Urban-rural land use plan is the foundation of healthily and orderly sustainable development of urbanization and the monitoring of plan implementation is considered as the guarantee. The association of remote sensing and GIS is one of rapid and effective monitoring method for urban-rural land use plan implementation which strongly strengthens the dynamic management of land use plan implementation. We used high spatial resolution remote sensing imagery—WorldView 2 with resolution of 0.5m and the object oriented image analysis method to achieve the classification. The features and thresholds were determined with CART decision tree in object oriented rule classification. On the basis of classification results, the completion rate of land plan for each plan patch was computed with the monitoring and evaluation of land use plan implementation. Finally, a subdistrict of Fangshan District,Beijing City was taken as the study area to illustrate the method. The results showed that the final overall accuracy of classification was 089 and Kappa coefficient was 0.87. The proposed classification algorithm can meet the basic needs of urban rural land use plan monitoring. The implementation of land use plan in northeast study area is better than that in the west. The public green land and water area need to be investigated and monitored further as the key objects, at the same time, the density of second type residential building is a little high, while the green landrate is low.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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