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国土资源遥感  2017, Vol. 29 Issue (3): 124-127    DOI: 10.6046/gtzyyg.2017.03.18
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
无人机农村宅基地高精度确权应用
薛武1, 2, 3, 4, 马永政1, 5, 赵玲1, 莫德林1, 2
1.信息工程大学地理空间信息学院,郑州 450001;
2.地理信息工程国家重点实验室,西安 710054;
3.矿山空间信息技术国家测绘地理信息局重点实验室,焦作 454003;
4.东华理工大学江西省数字国土重点实验室,南昌 330013;
5.集美大学计算机工程学院,厦门 361021
UAV-based rural homestead ownership determination
XUE Wu1, 2, 3, 4, MA Yongzheng1, 5, ZHAO Ling1, MO Delin1, 2
1. Information Engineering University, Zhengzhou 450001, China;
2. State Key Laboratory of Geo-information Engineering,Xi’an 710054, China;
3. Key Laboratory of Mine Spatial Information Technologies of National Adminisration of Surveying,Mapping & Geoinformation, Jiaozuo 454003, China;
4. Jiangxi Province Key Lab for Digital Land East China Institute of Technology, Nanchang 330013, China;
5. Computer Engineering College, Jimei University, Xiamen 361021, China
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摘要 利用无人机进行农村土地确权具有效率高、成本低的优势。通过开展简易无人机低空摄影测量试验,采用运动恢复结构数据处理方法,得到影像外方位元素的近似值,再利用附加参数的自检校光束法进行平差,明显提高了无人机低空摄影测量的定位精度,表明该方法具有一定的实用价值; 通过分析影响无人机摄影测量精度的主要因素,给出了控制无人机低空摄影测量精度的若干建议。
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卜丽静
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关键词 极化SAR分类假彩色增强颜色特征特征向量    
Abstract:Rural homestead ownership determination using unmanned aerial vehicle(UAV) has the advantages of high efficiency and low cost. Low-altitude UAV photogrammetry experiment was conducted to test its positioning accuracy. The simple UAV platform and ordinary digital camera effectively reduced the project cost. Through structure from motion, an approximation of the image exterior orientation elements was computed, and then a self-calibration bundle adjustment with additional parameters was undertaken, which significantly improves the accuracy of low-altitude UAV photography and thus has important practical value. By analyzing the main factors affecting the accuracy of UAV photogrammetry, the authors put forward some suggestions about the control of low altitude UAV photographic measurement accuracy.
Key wordsPolSAR image classification    pseudo color enhancement    color feature    feature vector
收稿日期: 2015-07-24      出版日期: 2017-08-15
作者简介: 薛 武(1988-),男,博士研究生,主要从事无人机摄影测量方面的研究。Email:xuewu_81@126.com。
引用本文:   
薛武, 马永政, 赵玲, 莫德林. 无人机农村宅基地高精度确权应用[J]. 国土资源遥感, 2017, 29(3): 124-127.
XUE Wu, MA Yongzheng, ZHAO Ling, MO Delin. UAV-based rural homestead ownership determination. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(3): 124-127.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2017.03.18      或      https://www.gtzyyg.com/CN/Y2017/V29/I3/124
[1] Eisenbeiβ H.UAV Photogrammetry[D].Zurich:Eth Zurich,2009:1-9.
[2] 于 英.无人机动态摄影测量若干关键技术研究[D].郑州:信息工程大学,2014:1-18.
Yu Y.Research on Key Technologies of UAV Dynamic Photogrammetry[D].Zhengzhou:PLA Information Engineering University,2014:1-8.
[3] 许志华,吴立新,刘 军,等.顾及影像拓扑的SFM算法改进及其在灾场三维重建中的应用[J].武汉大学学报(信息科学版),2015,40(5):599-606.
Xu Z H,Wu L X,Liu J,et al.Modification of SFM algorithm referring to image topology and its application in 3-Dimension reconstruction of disaster area[J].Geomatics and Information Science of Wuhan University,2015,40(5):599-606.
[4] Remondino F,Barazzetti L,Nex F,et al.UAV photogrammetry for mapping and 3D modeling-current status and future perspectives[C]//International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences.Zurich,Switzerland,2011:25-31.
[5] Szeliski R.计算机视觉——算法与应用[M].艾海舟,兴军亮译.北京:清华大学出版社,2012:265-273.
Szeliski R.Computer Vision:Algorithms and Applications[M].Translated by Ai H Z,Xing J L.Beijing:Tsinghua University Press,2012:265-273.
[6] 李德仁,袁修孝.误差处理与可靠性理论[M].2版.武汉:武汉大学出版社,2012:195-197.
Li D R,Yuan X X.Error Processing and Reliability Theory[M].2nd ed.Wuhan:Wuhan University Press,2012:195-197.
[7] 王之卓.摄影测量原理[M].武汉:武汉大学出版社,2007:240-241.
Wang Z Z.Photogrammetry Principle[M].Wuhan:Wuhan University Press,2007:240-241.
[1] 黄鹏艳, 卜丽静, 范永良. 结合视觉特征的极化SAR图像分类[J]. 国土资源遥感, 2020, 32(2): 88-93.
[2] 卜丽静, 黄鹏艳, 沈璐. 一种结合颜色特征的PolSAR图像分类方法[J]. 国土资源遥感, 2017, 29(3): 59-64.
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