摘要
GeoEye-1卫星是当前高分辨率商业卫星发展的一个新的里程碑,GeoEye-1卫星在测绘遥感中的应用具备众多传统航测不具有的优势,体现出了较大的潜力,为了能将GeoEye-1影像应用于DEM信息提取、DOM制作、二维特征信息提取、三维特征信息提取和三维电子地图制作,论文分为三个方面展开了研究。
首先,应用数字摄影测量的基本理论,在ERDAS LPS平台下探索应用GeoEye-1立体像对进行DEM和DOM生产的流程和关键技术,研究不同地面控制条件下DEM和DOM制作的精度及误差分布情况。然后,在ERDAS Objective模块下,基于面向对象的思想,分别为GeoEye-1影像设计道路、建筑物和树冠信息的自动提取方案,并成功地进行特征提取试验。最后,研究在Stereo Analyst模块下应用GeoEye-1影像进行三维特征信息提取和三维简单模型构建的原理、流程和精度,并探索应用ERDAS、SketchUp和ArcGIS交互地制作三维电子地图。
研究表明:(1)在少量控制点条件下,GeoEye-1影像能用于生产1:5000以上的大比例尺DEM和DOM,该技术不但适用于平地丘陵地区,也适用于偏远的缺乏控制数据的山地、高山地区。(2)应用GeoEye-1影像自动提取的二维特征信息比应用IKONOS和QuickBird影像的精度高,而且与单独应用全色或多光谱影像相比,应用经HIS方法融合后的“全色+多光谱”影像进行道路、建筑物和树冠的提取,能达到更好的效果,可应用于中等比例尺的数字线划图生产。(3)在Stereo Analyst模块下,能够从GeoEye-1立体影像中直接快速精确地从影像中获取地理要素的三维地理信息。应用ERDAS、SketchUp和ArcGIS交该方法能大大降低三维建筑物建模的难度、解决三维电子地互制作三维电子地图是可行的,图制作过程中的数据获取问题、同时满足应用三维电子地图进行空间分析的需求。
总之,GeoEye-1卫星能够用于快速生产高精度高分辨率的空间数据,为三维电子地图的制作提供可靠稳定的数据源,这对数字三维城市的建设具有重大意义。
GeoEye-1 satellite, which has large advantage over traditional aerial photogrammetry and significant potential in remote sensing and mapping, is a new milestone of the development of high-resolution commercial satellite. The paper’s research is divided into three parts in order that GeoEye-1 images can be applying in DEM extraction, DOM production, two-dimensional feature information extraction, three-dimensional feature information extraction, and production of three-dimensional electronic map.
Firstly, this paper applys the basic theory of digital photogrammetry to explore the production processes and key technology for producing DEM and DOM from GeoEye-1 stereo pair in ERDAS LPS platform. Secondly, based on object-oriented thinking, I designs automatic feature information extraction programs of roads, buildings and tree crowns for GeoEye-1 images in ERDAS Objective module. Finally, this paper explores the principles, processes, and precision of extracting three-dimensional information and building three-dimensional simple model using GeoEye-1 images under Stereo Analyst module .
The research results as follows: (1) Under the conditions of a small number of control points, GeoEye-1 image can be used for DEM and DOM production of 1:5000 or larger scale. This technology could not only be applied to flat and hilly areas, but also to remote mountain areas where lack of control data. (2) Comparing with IKONOS and Quickbird, using GeoEye-1 images to extract automatically two-dimensional feature information could achieve higher accuracy. Comparing with using multi-spectral or panchromatic images images alone, using the output image which is from IHS transformation using multi-spectral and panchromatic images could achieve better results and could be used to produce medium-scale digital line graph. (3) Accurate three-dimensional geographic information of geographic factors can be directly and quickly extracted from GeoEye-1 stereo images under Stereo Analyst module.It is feasible that using ERDAS, SketchUp and ArcGIS interactively to produce three-dimensional electronic map, which can greatly reduces the difficulty of modeling 3D building, solves the data acquisition problem on production process of three-dimensional digital map, as well as meets the need in spatial analysis.
In short, GeoEye-1 satellite is can be used to quickly produce high-precision and high-resolution spatial data, and could provide reliable and stable source for three-dimensional digital map production,which is also have great significance to the construction of digital three-dimensional city.
引文
[1]王任亨.三线阵CCD影像卫星摄影测量原理.北京:测绘出版社, 2006, 4-100
[2]张永生,巩凡超.高分辨率遥感卫星应用:成像模型、处理算法及应用技术.北京:科学出版社, 2004, 124-232
[3]胡著智.航空航天遥感技术与应用.南京:南京大学出版社, 2007,242-322
[4]陈鹰.遥感影像数字摄影测量.上海:同济大学出版社, 2003, 32-66
[5]张祖勋.数字摄影测量研究30年.武汉:武汉大学出版社, 2007,112-242
[6]王之卓.摄影测量原理.武汉:武汉大学出版社, 2007,132-200
[7]李德仁,王树良,李德毅.空间数据挖掘理论与应用.北京:科学出版社, 2006,343-378
[8]戴昌达,姜小光,唐伶俐.遥感图像应用处理与分析.北京:清华大学出版社, 2004:132-176
[9]龚健雅.对地观测数据处理与分析研究进展.武汉:武汉大学出版社, 2007,152-320
[10]柴登峰,张登荣.高分辨率卫星影像几何处理方法.杭州:浙江大学出版社, 2007, 11-79
[11] GeoEye Company. GeoEye product guide. www.geoeye.com, 2009-10-20
[12] C S Fraser. Georeferencing Accuracy of GeoEye-1 Imagery ,Cooperative Research Centre for Spatial Information Department of Geomatics University of Melbourne. www.asprs.org/publications/pers/2009journal/june/feature.pdf, 2009-9-21
[13] Jeff ,Zhizhong Xu. The Rational Function Model (RFM) in Photogrammetric Mapping Method and Accuracy, Earth and Space Science & Engineering, 2004,16(3):204-210
[14] C S Fraser, G Dial, J Grodecki. Sensor orientation via RPCs. ISPRS Journal of Photogrammetry & Remote Sensing , 2006, 12(4):182–194
[15] Saeid S, Mohammad J, Mahmoud R, Ahmad A. Processing of Ikonos imagery for submetre 3D positioning and building extraction. ISPRS Journal of Photogrammetry and Remote Sensing, 2002, 56( 3):177-194
[16] ERDAS, Inc. LPS Automatic Terrain Extraction User’s Guide, 2009,120-160.
[17] J. Poona, C. S. Frasera, C. Zhangb. High-resolution Satellite Imagine For Digital Surface Models, Photogrammetric Engineering and Remote Sensing, 2005, 35(4)
[18] Jiann Y, Liang C. DSM Generation from IKONOS Stereo Imagery,Journal of Photogrammetry and Remote Sensing, 2005, V10( 3): 265-274.
[19] Jacobsen K. Digital surface models of city areas by very high resolution space imagery. EARSeL Workshop on Urban Remote Sensing, 2006,41(2):363-368
[20] Zhang L, Gruen A. Automatic DSM generation from linear array imagery data. International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, 2004,35(B3):128-133
[21] Gruen A, Zhang L, Eisenbeiss H. 3D precision processing of high-resolution satellite imagery. Proceedings of the ASPRS 2005 Annual Conference, Maryland, USA,2005.78-84
[22] Poon J, Fraser C S, Zhang C, et al. Quality assessment of digtal surface models generated from Ikonos imagery. Photogrammetric Record, 2005, 20(110): 162-171.
[23] L Gabet, G. Giraudon, L Renouard. Automatic generation of high resolution urban zone digital elevation models. ISPRS Journal of Photogrammetry and Remote Sensing, 1997, 52(1): 33-47.
[24] Adina E, William F, Yves Arnaud, et al. Evaluating digital elevation models for glaciologic applications: An example from Nevado Coropuna, Peruvian Andes Global and Planetary Change, 2007, V59(4):110-125
[25]刘军,王冬红,毛国苗.基于RPC模型的IKONOS卫星影像高精度立体定位.测绘通报, 2004,9(3): 1-4
[26]陈雨常,白峰. IKONOS立体影像全数字摄影测量试验研究.地理空间信息, 2006, 4(4):19~22.
[27]雷蓉,邱振戈,张士涛.基于遥感影像生成DEM的质量检查.测绘通报, 2005 4(1): 36-39
[28]陈云浩,冯通,史培军.基于面向对象和规则的遥感影像分类研究.武汉大学学报(信息科学版), 2006, 31(4): 316-320.
[29]杜凤兰,田庆久,夏学齐.面向对象的地物分类法分析与评价.遥感技术与应用, 2004, 9(1):20-23
[30]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.遥感学报, 2006, 10(1): l-5.
[31]黄慧萍,吴炳方,李苗苗.高分辨率影像城市绿地快速提取技术与应用.遥感学报, 2004, 8(1): 68-74.
[32]胡进刚,张晓东,沈欣.一种面向对象的高分辨率影像道路提取方法.遥感技术与应用, 2006, 21(3): 184-188.
[33]黄建文,陈永富,鞠洪波.基于面向对象技术的退耕还林树冠遥感信息提取研究.林业科学, 2006, 13(42): 68-71.
[34]黎小东.向对象的高空间分辨率遥感影像城市建筑物震害信息提取——以汶川县城为例: [成都理工大学硕士论文].成都:成都理工大学, 2009,31-45
[35] Rahul J, Shrivastava, Jennifer L. Land cover classification and economic assessment of citrus groves using remote sensing . ISPRS Journal of Photogrammetry and Remote Sensing, 2007, 6l(5): 341-353
[36] Jordi Inglada.Automatic recognition of man-made objects in high resolution optical remote sensing images by SVM classiacation of geometric image features.ISPRS Journal of Photogrammetry and Remote Sensing..COrrected Proof Press, 2007, 54-78
[37] E. Uuemaa, J. Roosaare, U. Mander. Scale dependence of landscape metrics and their indicatory value for nutrient and organic matter losses from catchments. Ecological Indicators, 2005, 5(5): 350-369
[38]游丽平.面向对象的高分辨率遥感影像分类方法研究: [福建师范大学硕士论文].福建:福建师范大学, 2007, 23-58
[39]龚健雅.数字城市的基本概念及实现策略.北京:测绘出版社, 2004, 5-32.
[40]朱庆,林珲.数码城市地理信息系统:虚拟城市环境中的三维城市模型初探.武汉:武汉大学出版社, 2004,132-222
[41]钱健,谭伟贤.数字城市建设.北京:科学出版社, 2007,243-308
[42]李成名,王继周,马照亭.数字城市三维地理空间框架原理与方法.北京:科学出版社, 2008,43-108
[43]罗志华. SketchUp标准实例教程.北京:人民邮电出版社.2008, 12-44
[44]邵振峰.基于航空立体影像对的人工目标三维提取与重建: [武汉大学博士论文]. 2004,14-56
[45]龙毅,温永宁,盛业华.电子地图学.北京:科学出版社,2006,1-20
[46]郑燕玲.景观电子地图的研究与制作: [中国海洋大学硕士论文].青岛:中国海洋大学, 2008, 32-69.
[47]纪菲.网络景观电子地图的设计与研发——以上海市奉贤区为例: [中国海洋大学硕士论文].青岛:中国海洋大学, 2009,21-29
[48]杨鹏.网络电子地图与三维虚拟场景集成研究: [武汉大学硕士论文].武汉:武汉大学, 2005,32-38
[49]张晓辉.电子地图总体设计研究: [解放军信息工程大学硕士论文].郑州:解放军信息工程大学, 2006,23-28
[50] Nobuyuki Bannai, Robert B ,Alexander Agathos. Multiple color texture map fusion for 3D models. Pattern Recognition Letters ,2007, 3(28):748~758.
[51]单楠.基于SketchUp和ArcGIS的三维GIS开发技术研究: [西南大学硕士论文].成都:西南大学, 2009, 32-54.
[52]常河. Google SketchUp与ArcGIS在城市三维地下综合管网中的应用研究:[昆明理工大学硕士论文].昆明:昆明理工大学, 2008,33-54
[53]王海花. GIS三维可视化平台的数据交换与分析: [华东师范大学硕士论文].上海:华东师范大学, 2009,11-29
[54]薛亚婷.基于Google Earth及KML的数字校园设计与实现方法研究: [兰州大学硕士论文].兰州:兰州大学, 2007, 27-36
[55] Open Geospatial Consortium, Inc OpenGIS City Geography Markup Language (CityGML) Encoding Standard .http://www.opengeospatial.org/legal/, 2008-8-18
[56]陈引川.对城市地理标记语言(CityGML)的探讨第34卷第5期.测绘科学. 2009, 34(5): 112-118
[57]孟姣姣,武文波.基于ERDAS IMAGING的三维景观漫游系统的实现.矿山测量. 2007, 6 (2): 123-128
[58]中华人民共和国住房和城乡建设部.城市三维建模技术规范(征求意见稿).北京:测绘标准出版社, 2009,34-55
[59]中国标准出版社第四编辑室.测绘标准汇编--摄影测量遥感卷.北京:中国测绘出版社, 2009,13-25
