摘要
高分辨率遥感影像具有高空间分辨率、高清晰度、信息量丰富等优点,它的出现极大提高了遥感在城市土地利用/覆被变化研究中的应用能力.城市土地利用类型的准确分类是城市土地利用/覆被变化研究的重要前提,高分辨遥感影像凭借其自身优势成为最重要的数据源.本研究从高分辨率遥感影像的发展与特点、分类方法及其在城市专题信息提取中的应用3个方面进行综述,重点回顾高分辨率遥感影像用于城市土地利用分类的代表性方法及其在城市系统中提取建筑物、道路和绿地等专题信息的方法和应用进展,最后指出高分辨遥感影像在城市土地利用/覆被变化研究中的不足以及未来需要解决的问题.
Urbanization causes land cover changes which lead to deeper regional social, economic, and environmental changes and have important influences on environment and climate on the global scale. The coarse or moderate resolution remote sensing images may have much mixed pixels which limit their applications in the study of urban remote sensing. High spatial resolution remote sensing images with the advantages of high spatial resolution, high definition, and rich information, greatly improve the application of remote sensing in the research area of land use and land change. Accurate urban land use classification is the basis of the study of urban LUCC, and the high spatial resolution remote sensing images become one of the most important data sources because of their inherent advantages. We report the development and features of high resolution remote sensing images, the methods of remote sensing images classification, and their applications in extracting urban information. Much attention is paid to the representative classification methods in urban land use and to the ways of extracting information of buildings, roads, and vegetation in urban environment. The paper indicates that, compared to the traditional classification methods based on the level of pixels, the object-oriented image classification method which makes full use of high spatial resolution remote sensing images is the most widely used method. The discussion focuses on the current status and perspectives of the object-oriented method. With the help of high spatial resolution remote sensing images, accurate urban thematic information can be extracted effectively and it plays a significant role in the study of urban LUCC.
出处
《中国科学院大学学报（中英文）》
CSCD
北大核心
2016年第3期289-297,共9页
Journal of University of Chinese Academy of Sciences
基金
国家自然科学基金面上项目(41271416)
国家自然科学基金(41301466)资助
关键词
高分辨率遥感
城市LUCC
分类方法
信息提取
high spatial resolution remote sensing
urban LUCC
classification methods
informationextraction
