测绘通报 ›› 2023, Vol. 0 ›› Issue (3): 116-122.doi: 10.13474/j.cnki.11-2246.2023.0083

• 技术交流 • 上一篇    下一篇

基于Landsat 8影像的城市蓝色顶面建筑物提取光谱模型构建

程苗苗1, 王世东1, 张学军2, 张合兵1   

  1. 1. 河南理工大学测绘与国土信息工程学院, 河南 焦作 454003;
    2. 河南省地质矿产勘查开发局第二地质矿产调查院, 河南 郑州 450001
  • 收稿日期:2022-03-30 发布日期:2023-04-04
  • 通讯作者: 张学军。E-mail:478441986@qq.com
  • 作者简介:程苗苗(1999-),女,硕士,主要从事地理信息系统研究。E-mail:2136592317@qq.com
  • 基金资助:
    河南省科技攻关重点项目(222102320005);河南省高等学校重点科研项目(22A420002)

Spectral model construction of urban blue roof building extraction based on Landsat 8 image

CHENG Miaomiao1, WANG Shidong1, ZHANG Xuejun2, ZHANG Hebing1   

  1. 1. School of Surveying and mapping and land information engineering, Henan University of technology, Jiaozuo 454003, China;
    2. The Second Institute of Geology and Mineral Resources Survey of Henan Bureau of Geology and Mineral Resources Exploration and Development, Zhengzhou 450001, China
  • Received:2022-03-30 Published:2023-04-04

摘要: 蓝色顶面建筑物作为基础地理数据库中重要的人工目标类型之一,对其进行提取对城市环境监测、违章建筑监测、城市规划和管理具有重要意义。已有的建筑物提取方法准确性低、边界不完整,且存在同谱异物和同物异谱现象。本文以洛阳市为研究区,根据不同地物光谱特征的不同原理,构建一种能增强蓝色顶面信息和弱化其他非目标地物信息的新光谱模型。首先,对待检测的Landsat 8影像进行辐射定标和大气校正等工作,获得地物去除大气影响后的地表反射特征值影像;然后,对影像中的蓝色地物和与蓝色地物较难区分的其他干扰地物,分别采集一定像元数的样本并生成光谱曲线,利用波段相加、差值及正负处理构建一个能增强蓝色地物信息和弱化其他干扰地物信息的新光谱指数;最后,采用密度分割法获得提取蓝色顶面建筑物最合适的阈值范围,进而提取影像中的蓝色顶面建筑物。与最大似然法提取结果进行对比分析及精度评价。结果表明,构建的新光谱指数模型的总体分类精度为94.46%,Kappa系数为0.889 2,准确率为91.95%,召回率为95.19%,均优于最大似然法;根据提取结果计算出洛阳市市区范围内蓝色顶面建筑物的占地面积为16.28 km2,占研究区面积的0.564%,占洛阳市总面积的0.107%。可见本文方法相比最大似然法具有更好的提取效果和提取精度,有一定的优越性和实用性。

关键词: Landsat 8影像, 蓝色顶面建筑物, 光谱模型, 提取

Abstract: As one of the important artificial target types in the basic geographic database, the extraction of blue roof buildings is of great significance to urban environmental monitoring, illegal building monitoring, urban planning and management. In view of the low accuracy and incomplete boundary of the existing building extraction methods, and the phenomenon of foreign matter with the same spectrum and different spectrum of the same object. Taking Luoyang as the research area, according to the principle of different spectral characteristics of different ground objects, a new spectral model which can enhance the blue top information and weaken the information of other non target ground objects is constructed in this paper. Firstly, the Landsat 8 image to be detected is radiometric calibrated and atmospheric corrected to obtain the surface reflection eigenvalue image after removing the atmospheric influence. Secondly, the samples of a certain number of pixels are collected for the blue features in the image and other interfering features that are difficult to distinguish from the blue features, and the spectral curve is generated. The band addition, difference and positive and negative processing are used to construct a new spectral index that can enhance the information of the blue features and weaken the information of other interfering features. Finally, the density segmentation method is used to obtain the most appropriate threshold range for extracting the blue top building, and then extract the blue top building in the image. The results showed that the overall classification accuracy of the new spectral index model is 94.46%, the Kappa coefficient is 0.889 2, the accuracy rate is 91.95%, and the recall rate is 95.19%, which are better than the maximum likelihood method. According to the extraction results, the area of the blue roof buildings in the urban area of Luoyang city is 16.28 km2, accounting for 0.564% of the area of the study area and 0.107% of the total area of Luoyang city. The results show that this method has better extraction effect and accuracy than the maximum likelihood method, and has certain advantages and practicability.

Key words: Landsat 8 image, blue roof building, spectral model, extract

中图分类号: