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遥感技术与应用  2019, Vol. 34 Issue (5): 1073-1081    DOI: 10.11873/j.issn.1004-0323.2019.5.1073
遥感应用     
一种基于改进土地覆盖更新方法的新增建设用地自动提取
张因果1,2(),陈芸芝1,2()
1. 福州大学 空间数据挖掘与信息共享教育部重点实验室,福建 福州 350116
2. 卫星空间信息技术综合应用国家地方联合工程研究中心,福建 福州 350116
Automatic Extraction of New Construction Land based on an Improved Method of Updating Land Cover Maps
Yinguo Zhang1,2(),Yunzhi Chen1,2()
1. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350116, China
2. National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350116, China
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摘要:

快速准确掌握新增建设用地信息对城镇化监测研究具有重要意义。基于后验概率变化矢量检测的土地覆盖更新方法中,存在初始样本准确性低、后验概率变化矢量检测精度不理想的问题,结合多元变化检测方法,对基于后验概率变化矢量检测的更新方法进行改进,提出一种可应用于新增建设用地提取的自动化方法。利用两期影像多元变化检测结果提高初始训练样本的准确性,同时在迭代选择样本过程中加入该变化检测结果,改善变化检测更新和重分类过程的精度,更准确地提取新增建设用地。用两期嘉兴地区高分一号影像和前期影像土地利用/覆盖分类数据验证改进效果,并与改进前方法对比。结果表明:改进方法提取的2017年新增建设用地精度更高,提取更新后的2017年建设用地总体精度达到85%,Kappa系数0.7以上,变化检测精度比未改进前显著提高。同时该方法显著减少了迭代次数,提高了提取效率。

关键词: 多元变化检测新增建设用地自动提取后验概率变化矢量检测    
Abstract:

It is of great significance to extracting new construction land information rapidly and accurately for urbanization monitor research. Because of the low accuracy of original samples in the updating land cover method based on Change Vector Analysis in Posterior Probability Space (CVAPS), and the poor accuracy of change detection of CVAPS, the paper proposed a new automatic approach applied to extract new construction land information effectively. This method was improved from the updating land cover method based on CVAPS by combining with Multivariate Alteration Detection (MAD). The method firstly introduced MAD results of bi-temporal images to improve the accuracy of the initial samples, then added MAD results into the process of iterating samples selection in order to improve the accuracy of change detection and reclassification, thereby extracting new construction land more precisely. A case study of bi-temporal GF-1 images and land use/cover map in Jiaxing area was conducted to test performance of the improved method, and compared this method with CVAPS method. The experimental results show that the new construction land extracted by improved method in 2017 has higher accuracy, its overall accuracy of the updated construction land in 2017 reached 85% and its kappa coefficient is above 0.7. The accuracy of change detection is significantly higher than CVAPS method. Meanwhile, the proposed method reduced number of iteration and raised extraction efficiency significantly.

Key words: Multivariate alteration detection    New construction land    Automatic extraction    CVAPS
收稿日期: 2018-08-21 出版日期: 2019-12-05
ZTFLH:  TP79  
基金资助: 国家重点研发计划课题(2017YFB0504203);中央引导地方科技发展专项(2017L3012)
通讯作者: 陈芸芝     E-mail: ygzhangEDU@163.com;chenyunzhi@fzu.edu.cn
作者简介: 张因果(1992-),男,河南信阳人,硕士研究生,主要从事遥感信息处理与应用研究。E?mail:ygzhangEDU@163.com
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引用本文:

张因果,陈芸芝. 一种基于改进土地覆盖更新方法的新增建设用地自动提取[J]. 遥感技术与应用, 2019, 34(5): 1073-1081.

Yinguo Zhang,Yunzhi Chen. Automatic Extraction of New Construction Land based on an Improved Method of Updating Land Cover Maps. Remote Sensing Technology and Application, 2019, 34(5): 1073-1081.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.5.1073        http://www.rsta.ac.cn/CN/Y2019/V34/I5/1073

图1  本文方法技术流程图
图2  研究区位置
图3  研究区实验数据
图4  2017年新增建设用地自动提取结果
图5  本文方法与CVAPS法提取结果局部对比
提取精度用户精度/%制图精度/%总体精度/%Kappa
建设用地非建设用地建设用地非建设用地
本文方法83.3188.2386.2485.6585.920.717
CVAPS方法73.9484.9279.2875.4479.270.587
表1  2017年建设用地精度评价
图6  变化检测结果

变化检测

精度

错检率/%漏检率/%总体精度/%Kappa
变化像元未变化像元变化像元未变化像元
本文方法11.6715.119.398.986.320.722
CVAPS方法21.1414.5216.5218.7182.290.645
MAD检测22.2617.3220.2819.0880.370.605
表2  变化检测结果精度评价
图7  变化检测精度与迭代次数的关系
图8  2017建设用地精度与迭代次数的关系
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