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水利部南京水利水文自动化研究所

基于遥感影像的水域违章建筑识别研究------陈建国,王晨辉, 徐绪堪3,嵇庆才

摘要:在河湖“清四乱”专项活动中,全国各地对乱占、乱采、乱堆、乱建等河湖突出问题开展集中清理整治,针对人工排查工作中存在繁琐、效率低下的问题,以水域遥感影像为研究对象,以提高违章建筑识别正确率和效率为目标,提出一种基于改进PCA和-Means的遥感影像变化检测算法,该算法应用违章建筑的粗筛选和识别

基于遥感影像的水域违章建筑识别研究------陈建国,王晨辉, 徐绪堪3,嵇庆才

摘要:在河湖“清四乱”专项活动中,全国各地对乱占、乱采、乱堆、乱建等河湖突出问题开展集中清理整治,针对人工排查工作中存在繁琐、效率低下的问题,以水域遥感影像为研究对象,以提高违章建筑识别正确率和效率为目标,提出一种基于改进PCA和-Means的遥感影像变化检测算法,该算法应用违章建筑的粗筛选和识别

分类:2021年第01期(总第160期)

发布: 2021-11-10 19:29:48

详情描述

陈建国1,王晨辉2, 徐绪堪3 ,嵇庆才4

(1. 宁夏水利电力工程学校,宁夏 银川 750006;2. 河海大学商学院,江苏 常州 213022;3. 常州工业大数据挖掘与知识管理重点实验室,江苏 常州 213022;4. 镇江新区城乡建设局,江苏 镇江 212132)

  摘 要: 在河湖“清四乱”专项活动中,全国各地对乱占、乱采、乱堆、乱建等河湖突出问题开展集中清理整治,针对人工排查工作中存在繁琐、效率低下的问题,以水域遥感影像为研究对象,以提高违章建筑识别正确率和效率为目标,提出一种基于改进PCA和-Means的遥感影像变化检测算法,该算法应用违章建筑的粗筛选和识别,对遥感影像进行几何校正、转换、特征空间提取、信息映射及构造图像变化特征矩阵;通过改进-Means方法定位变化区域,给出水域违章建筑可能的区域,大大缩小人工检测范围。实验结果表明,该方法可以快速、高精度地提取到用地变化信息,提高水域违章建筑识别效率和河湖监管能力。

  关键词:河湖“清四乱”;主成分分析;

  -Means聚类;水域违章建筑识别

  Research on recognition of illegal buildings in waters based on remote sensing images

  CHEN Jianguo1, WANG Chenhui2, XU Xukan3, JI Qingcai4

  (1.Ningxia Water Conservancy and Electric Power Engineering School, Yinchuan 750006, China;

  2. Business School of Hohai University, Changzhou 213022, China;

  3. Changzhou Key Laboratory of Industrial Big Data Mining and Knowledge Management, Changzhou 213022, China;

  4. Urban and Rural Construction Bureau of Zhenjiang New District, Zhenjiang 212132, China)

  Abstract: In the special activity of “clearing the four chaos” of rivers and lakes, all parts of China carry out centralized clean-up and remediation of prominent problems in rivers and lakes, such as indiscriminate occupation, indiscriminate mining, disorganization, and disorganized construction. Aiming at the problem of tedious and low efficiency in manual inspection work, to improve the accuracy and the efficiency of illegal buildings recognition, the article proposes a remote sensing image change detection algorithm based on improved PCA and k-Means . This algorithm is aimed to give a rough screening and recognition of illegal buildings. Remote sensing images perform geometric correction, conversion, feature space extraction, information mapping and construction of image change feature matrix. Then possible locations of illegal buildings are recognized by means of improved k-Means. It greatly reduce the scope of manual detection. Experiment shows that this method can quickly and accurately extract land use change information, improve the efficiency of recognizing illegal buildings in waters and the ability of river and lake supervision.

  Keywords: rivers and lakes “clearing the four chaos”; principal component analysis; k-Means clustering; recognition of illegal buildings in waters

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版权所有:水利部南京水利水文自动化研究所     苏ICP备05086125号     中企动力  南京