基于高分辨率遥感影像的城市地表信息提取
Extracting Information of Urban Land Surface with High Resolution Remote Sensing Image
DOI: 10.12677/GSER.2021.104038, PDF,   
作者: 邹 霞：生态环境部长江流域生态环境监督管理局上海生态环境科学研究中心，上海；刘佳明：长江勘测规划设计研究有限责任公司，湖北 武汉
关键词: 高分辨率；遥感影像；城市地表；High Resolution； Remote Sensing Image； Urban Surface
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，为城市地表土地覆盖和土地利用信息的提取提供了可能。本文以高分辨率遥感影像数据worldview为主要数据源，以基于立体像对提取DEM、基于分类的面向对象影像分析方法和基于阴影的建筑物高度获取为主要技术，自动提取武汉市十里铺区域的地表信息，得到了该区域的DEM、土地分类情况以及建筑物高度情况等信息，精度高，速度快，结果表明利用高分辨率的遥感影像对复杂的城市地表信息获取是可行的。
Abstract: With the advantages of high spatial resolution and definition, and rich information, land classification and land utilization of urban surface can be reached by using the high-resolution remote sensing data. Based on the high-resolution remote sensing image data worldview as the main data source, the methods of stereo images, object-oriented technique and architecture shadow are used to extract the information of DEM, land classification and building heights in Wuhan Shilipu district. The results show the high precision and rapid speed when extracting the surface information, and high-resolution remote sensing image is feasible for complex urban surface information acquisition.
文章引用：邹霞, 刘佳明. 基于高分辨率遥感影像的城市地表信息提取[J]. 地理科学研究, 2021, 10(4): 326-335. https://doi.org/10.12677/GSER.2021.104038

参考文献

[1] 王碧辉, 吴运超, 黄晓春. 基于高分辨率遥感影像的城市用地分类研究[J]. 遥感信息, 2011, 27(4): 111-115.
[2] Weng, Q. (2012) Remote Sensing of Impervious Surfaces in the Urban Areas: Requirements, Methods, and Trends. Remote Sensing of Environment, 117, 34-49. [Google Scholar] [CrossRef] 
[3] 宫鹏, 黎夏, 徐冰. 高分辨率影像解译理论与应用方法中的一些研究问题[J]. 遥感学报, 2006, 10(1): 1-5.
[4] 陈述彭, 谢传节. 城市遥感与城市信息系统[J]. 测绘科学, 2000, 25(1): 1-8.
[5] Yang, X. (2011) Urban Remote Sensing: Monitoring, Synthesis and Modelling in the Urban Environment. Wiley-Blackwell, Hoboken. [Google Scholar] [CrossRef] 
[6] Zhou, W. and Troy, A. (2008) An Object-Oriented Approach for Analyzing and Characterizing Urban Landscape at the Parcel Level. International Journal of Remote Sensing, 29, 3119-3135. [Google Scholar] [CrossRef] 
[7] Pu, R., Landry, S. and Yu, Q. (2011) Object-Based Urban Detailed Land Cover Classification with High Spatial Resolution IKONOS Imagery. International Journal of Remote Sensing, 32, 3285-3308. [Google Scholar] [CrossRef] 
[8] 杜培军. 高分辨率遥感影像处理进展与城市应用若干实例[J]. 现代测绘, 2020, 43(1): 1-9.
[9] 杨朝斌, 张树文, 卜坤, 于灵雪, 颜凤芹, 常丽萍, 杨久春. 高分辨率遥感影像在城市LUCC中的应用[J]. 中国科学院大学学报, 2016, 33(3): 289-297.
[10] 刘东升, 任芳, 卫黎光. 国产高分遥感数据处理技术及典型应用[J]. 中国航天, 2020(5): 37-42.
[11] 杨韫澜, 胡海彦. 基于OpenGL的摄影立体量测系统[J]. 海洋测绘, 2007, 27(3): 40-42.
[12] Redfern, S., Lyons, G. and Redfern, R.M. (1999) Digital Elevation Modelling of Individual Monuments from Aerial Photographs. Archaeological Prospection, 6, 211-224. [Google Scholar] [CrossRef] 
[13] Lee, H.Y., Kim, T., Park, W., et al. (2003) Extraction of Digital Elevation Models from Satellite Stereo Images through Stereo Matching Based on Epipolarity and Scene Geometry. Image and Vision Computing, 21, 789-796. [Google Scholar] [CrossRef] 
[14] Ahmad, B.B. (2009) Assessment and Correction of SRTM DEM with Reference to Geo-Hazard Identification in the Cameron Highlands, Malaysia. Geoinformation Science Journal, 9, 32-40.
[15] 仇江啸, 王效科. 基于高分辨率遥感影像的面向对象城市土地覆被分类比较研究[J]. 遥感技术与应用, 2010, 25(5): 653-661.
[16] 关元秀, 程晓阳. 高分辨率卫星影像处理指南[M]. 北京: 科学出版社, 2008.
[17] Wu, C. and Murray, A.T. (2003) Estimating Impervious Surface Distribution by Spectral Mixture Analysis. Remote Sensing of Environment, 84, 493-505. [Google Scholar] [CrossRef] 
[18] Yuan, F. and Bauer, M.E. (2007) Comparison of Impervious Surface Area and Normalized Difference Vegetation Index as Indicators of Surface Urban Heat Island Effects in Landsat Imagery. Remote Sensing of Environment, 106, 375-386. [Google Scholar] [CrossRef] 

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