Google Earth数据在道路工程可行性研究阶段中的应用
发布时间：2018-08-20 13:02
【摘要】：改革开放以来,中国的交通事业得到大力支持并快速发展,2016年交通基础设施投资将超过2.6万亿。目前,我国公路网络已经基本形成,但还存在着总量不足和结构矛盾等突出问题,到2030年,还有2.6万公里国家高速公路待建,还有10万公里国省干线公路需要改造升级,可见道路工程项目一直有巨大的数量,并且需要更多的投资额。为了工程项目建设的科学决策,可行性研究是道路工程中的重要一环。外业勘测是编制工程可行性研究报告中的一个重要的步骤,这阶段中,一般采用比例尺是1:10000的地形图,外业勘测深度过深则会造成浪费资源,过浅则不满足要求。通常采用航空摄影技术进行测绘,但其缺点是费用高(800-1000元/2km),受天气影响。若全部使用GPS技术进行测量,在地形复杂的区域导致工作艰难,人力消耗很大。为了使地形图测绘更简便、经济,研究利用Google Earth数据帮助测绘制图有重要的现实意义,并在此基础上利用Auto CAD Civil3D帮助进行三维可视化设计。本文以中国某地区经实地勘测的数字地形图为依据,利用Google Earth的地面高程数据与Auto CAD Civil 3D结合进行数字地形图制作和三维道路设计,主要用于道路勘测设计的可行性研究阶段。为了确保Google Earth的高程精度满足实际工程使用要求,并且可以实际地用于道路设计,本文以Google Earth的地面高程精度、提高Google Earth高程精度的方法和Google Earth数据在道路勘测工程中的使用方法为主要研究对象,主要研究内容为:(1)研究Google Earth数据的来源和高程系统,以实际工程的数字地形图高程数据和Google Earth上的高程数据作对比分析,确定Google Earth高程与实际工程高程的误差。(2)与高程异常拟合研究类比,研究二次多项式曲面拟合、三次多项式曲面拟合、Matlab的V4插值法和神经网络法在建立Google Earth数据与实测数据之间高程差模型的优劣。(3)研究提高精度后的Google Earth地面高程数据能否用于道路工程可行性研究阶段,能用的数据是否有局限性;(4)研究通过Google Earth和Auto CAD Civil3D结合,进行三维地形建模和三维道路设计的步骤和优势,发挥Google Earth的实用性和为道路工程设计提供简便的方法。研究结论:Google Earth高程数据的来源是STRM-3数据,与我国工程所用的正常高之间存在着高于1:10000地形图允许的误差;建立地面高程差的拟合或插值模型,灵活使用三次多项式曲面模型和神经网络法进行拟合是合理的选择,能有效预测模型中各个地方的高程差,大幅度提高Google Earth高程精度;以中国某地区的Google Earth数据为例,提高精度后,平地地形区域的Google Earth数据仍不满足1:10000地形图的要求,丘陵地区区域的Google Earth数据可以满足要求;Google Earth和Auto CAD Civil3D可以简单有效地结合,给可行性研究中的道路勘测设计和展示提供更简便、生动具体的设计流程和方法。综上所述,本文的研究可以使道路工程可行性研究阶段中的勘测设计更便捷、更经济,显著提高Google Earth地面高程数据用于实际工程中的精度,并且为道路勘测设计的发展趋势提供了一定参考。
[Abstract]:Since the reform and opening up, China's transportation industry has been strongly supported and developed rapidly, and the investment in transportation infrastructure will exceed 2.6 trillion yuan in 2016. At present, China's highway network has basically formed, but there are still outstanding problems such as insufficient total amount and structural contradictions. By 2030, there will be 26,000 kilometers of national highways to be built and 100,000 kilometers of national highways to be built. In order to make scientific decision for the construction of the project, feasibility study is an important part of the road project. Field survey is an important step in compiling the feasibility study report of the project. Generally, the scale of topographic maps is 1:10000, and the depth of field survey is too deep, which will cause waste of resources, but the shallow is not satisfying. In order to make topographic mapping more convenient and economical, it is of great practical significance to study and use Google Earth data to help mapping, and on this basis, use Auto CAD Civil 3D to help 3D visualization design. The combination of elevation data and Auto CAD Civil 3D for digital topographic mapping and 3D road design is mainly used in the feasibility study stage of road survey and design. The method of high Google Earth elevation accuracy and the method of using Google Earth data in road survey engineering are the main research objects. The main research contents are as follows: (1) The source and elevation system of Google Earth data are studied. The elevation data of digital topographic maps and that of Google Earth are compared and analyzed to determine the Google Earth data. The error between the height of Google Earth and the actual engineering elevation. (2) Analogy with the height anomaly fitting research, quadratic polynomial surface fitting, cubic polynomial surface fitting, V4 interpolation method of MATLAB and neural network method to establish the model of elevation difference between the Google Earth data and the actual measured data. (3) Study the Google Earth ground after improving the accuracy. Whether elevation data can be used in the feasibility study stage of road engineering is limited or not; (4) Study the steps and advantages of 3D terrain modeling and 3D road design through the combination of Google Earth and AutoCAD Civil 3D, give full play to the practicability of Google Earth and provide a simple method for road engineering design. The source of oogle earth elevation data is STRM-3 data, and there is an error higher than 1:10000 allowable topographic map between oogle earth elevation data and normal elevation data used in our country. It is reasonable to establish fitting or interpolation model of ground elevation difference, and flexibly use cubic polynomial surface model and neural network method to fit each of the models. Local elevation difference greatly improves the elevation accuracy of Google Earth. Taking the Google Earth data of a certain area in China as an example, after improving the accuracy, the Google Earth data of flat terrain area still does not meet the requirements of 1:10000 topographic map, and the Google Earth data of hilly area can meet the requirements of simple Google Earth and AutoCAD Civil 3D. In summary, this study can make the survey and design in the feasibility study stage of road engineering more convenient, more economical, and significantly improve the accuracy of Google Earth ground elevation data used in practical engineering. It also provides a reference for the development trend of road survey and design.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U412
本文编号：2193696
[Abstract]:Since the reform and opening up, China's transportation industry has been strongly supported and developed rapidly, and the investment in transportation infrastructure will exceed 2.6 trillion yuan in 2016. At present, China's highway network has basically formed, but there are still outstanding problems such as insufficient total amount and structural contradictions. By 2030, there will be 26,000 kilometers of national highways to be built and 100,000 kilometers of national highways to be built. In order to make scientific decision for the construction of the project, feasibility study is an important part of the road project. Field survey is an important step in compiling the feasibility study report of the project. Generally, the scale of topographic maps is 1:10000, and the depth of field survey is too deep, which will cause waste of resources, but the shallow is not satisfying. In order to make topographic mapping more convenient and economical, it is of great practical significance to study and use Google Earth data to help mapping, and on this basis, use Auto CAD Civil 3D to help 3D visualization design. The combination of elevation data and Auto CAD Civil 3D for digital topographic mapping and 3D road design is mainly used in the feasibility study stage of road survey and design. The method of high Google Earth elevation accuracy and the method of using Google Earth data in road survey engineering are the main research objects. The main research contents are as follows: (1) The source and elevation system of Google Earth data are studied. The elevation data of digital topographic maps and that of Google Earth are compared and analyzed to determine the Google Earth data. The error between the height of Google Earth and the actual engineering elevation. (2) Analogy with the height anomaly fitting research, quadratic polynomial surface fitting, cubic polynomial surface fitting, V4 interpolation method of MATLAB and neural network method to establish the model of elevation difference between the Google Earth data and the actual measured data. (3) Study the Google Earth ground after improving the accuracy. Whether elevation data can be used in the feasibility study stage of road engineering is limited or not; (4) Study the steps and advantages of 3D terrain modeling and 3D road design through the combination of Google Earth and AutoCAD Civil 3D, give full play to the practicability of Google Earth and provide a simple method for road engineering design. The source of oogle earth elevation data is STRM-3 data, and there is an error higher than 1:10000 allowable topographic map between oogle earth elevation data and normal elevation data used in our country. It is reasonable to establish fitting or interpolation model of ground elevation difference, and flexibly use cubic polynomial surface model and neural network method to fit each of the models. Local elevation difference greatly improves the elevation accuracy of Google Earth. Taking the Google Earth data of a certain area in China as an example, after improving the accuracy, the Google Earth data of flat terrain area still does not meet the requirements of 1:10000 topographic map, and the Google Earth data of hilly area can meet the requirements of simple Google Earth and AutoCAD Civil 3D. In summary, this study can make the survey and design in the feasibility study stage of road engineering more convenient, more economical, and significantly improve the accuracy of Google Earth ground elevation data used in practical engineering. It also provides a reference for the development trend of road survey and design.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U412
【参考文献】
相关期刊论文 前10条
1 朱纯强;张欣杰;张善廷;;GPS高程拟合应用精度分析[J];北京测绘;2016年02期
2 何海清;黄声享;陈婷;;一种顾及粗差的径向神经网络高程曲面拟合法[J];武汉大学学报(信息科学版);2015年04期
3 李浩;吴祖海;;GPS高程异常拟合粗差剔除以及精度评价方法研究[J];铁道科学与工程学报;2015年01期
4 江帆;梁勇;龚选林;;基于SketchUp、Google Earth和Civil 3D的矿山排土场联合建模[J];现代矿业;2014年11期
5 计枚选;赵丹华;马鹏涛;薛晶晶;;利用Civil 3D纵断面动态更新功能进行风电场道路选线[J];电子世界;2014年16期
6 张朝忙;刘庆生;刘高焕;丁树文;李贺;董金发;;中国地区SRTM3 DEM高程精度质量评价[J];测绘工程;2014年04期
7 牛志宏;;几种基于神经网络的GPS高程拟合方法比较[J];全球定位系统;2014年02期
8 王苗苗;柯福阳;;多项式曲面拟合和BP神经网络GPS高程拟合方法的比较研究[J];测绘工程;2013年06期
9 王雯珏;;Civil 3D在电厂总图道路设计中的应用[J];武汉大学学报(工学版);2013年S1期
10 胡现辉;刘波;;Google Earth在输电线路勘测设计中的应用[J];北京测绘;2013年05期
相关硕士学位论文 前2条
1 黎剑;区域GPS高程异常拟合及建模方法研究[D];昆明理工大学;2013年
2 左美蓉;SRTM高程数据及其应用研究[D];中南大学;2009年
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