摘要
为了提高矿区土地利用信息遥感分类和提取精度,本文采用多源数据融合技术,利用高分二号卫星数据,融合面向对象思想和支持向量机方法,对河南省禹州市的采矿区进行以露天采场为主的矿区土地利用信息提取。结果表明,融合支持向量机和面向对象方法的矿区信息提取总体精度为86.44%,Kappa系数为0.83,优于融合K近邻和面向对象的方法,表明该方法在矿区信息提取中有理想的精度,可为矿区的环境监测和科学管理提供可靠的技术支撑。
In order to improve the the accuracy of remote sensing classification and extraction of land use information in mining areas,by using multi-source data fusion technology and GF-2 satellite data,the land use information of open pit mining area in Yuzhou City,Henan Province was extracted based on combining support vector machine and object-oriented method.The results showed that the overall accuracy of mining area information extraction based on combing support vector machine and object-oriented method was 86.44%,and the Kappa coefficient was 0.83,which was better than that of the combined K-nearest neighbor algorithm and object-oriented method.It showed that this method had ideal accuracy in mining area information extraction,and could provide reliable technical support for environmental monitoring and scientific management of mining areas.
作者
霍光杰
胡乃勋
陈涛
甄娜
Huo Guangjie;HU Naixun;CHEN Tao;ZHEN Na(Geological Environment Monitoring Institute of Henan Province,Zhengzhou 450000,Henan,China;Key Laboratory of Geological Environment Protection of Henan Province,Zhengzhou 450006,Henan,China;Institute of Geophysics and Geomatics,China University of Geosciences,Wuhan 430074,Hubei,China)
出处
《河南理工大学学报（自然科学版）》
CAS
北大核心
2021年第2期70-75,共6页
Journal of Henan Polytechnic University（Natural Science）
基金
国家自然科学基金资助项目(61601418)
河南省财政项目(豫财预﹝2014﹞134号,﹝2015﹞128号,﹝2016﹞44号)。
关键词
矿区信息提取
面向对象
支持向量机
土地利用
mining area information extraction
object-oriented
support vector machine
land use
