An Ecological Irrigation Canal Extraction Algorithm Based on Airborne Lidar Point Cloud Data

被引:0
|
作者
Wang, Guangqi [1 ]
Han, Yu [2 ]
Chen, Jian [1 ]
Pan, Yue [3 ]
Cao, Yi [1 ]
Meng, Hao [1 ]
Du, Nannan [1 ]
Zheng, Yongjun [1 ]
机构
[1] China Agr Univ, Coll Engn, Beijing 100083, Peoples R China
[2] China Agr Univ, Coll Water Resources & Civil Engn, Beijing 100083, Peoples R China
[3] Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Ecological irrigation canal; Unmanned aerial vehicle (UAV); Lidar; Point cloud data; Characteristic line; LOESS PLATEAU; WATER; WHEAT;
D O I
10.1007/978-981-13-6052-7_46
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Accurate and efficient extraction of ecological irrigation canals plays a key role in realizing agricultural modernization. In view of the problem of ecological irrigation canal extraction, this paper proposes an airborne lidar extraction method based on unmanned aerial vehicle (UAV). First, the method of acquiring 3D point cloud data on the ground is derived. The filtering method of mathematical morphology is used to remove ground noise. Then, the characteristic line of the ecological irrigation canal is extracted, a new threshold selection method is put forward according to the characteristics of the ecological irrigation canal. It is helpful to further accurately extract the characteristic lines of the ecological irrigation canal. Finally, the characteristics of the three-dimensional point cloud data and the characteristics of the reflection intensity are analyzed. It is significant to distinguish the ecological irrigation canals and other disturbing terrain. Compared with the traditional extraction method (such as machine vision), the method has the advantages of high efficiency, high precision and no artificial parameters. The model of a small ecological irrigation canal was established by Matlab. It has important practical value for the later planning of ecological irrigation canals and the acceleration of agricultural modernization.
引用
下载
收藏
页码:538 / 547
页数:10
相关论文
共 50 条
  • [31] Point cloud extraction algorithm based on TLS data in railway stations
    Fang, Yipeng
    Song, Zhanfeng
    Li, Jun
    Journal of Railway Science and Engineering, 2024, 21 (02) : 545 - 554
  • [32] Traffic Marking Extraction Algorithm Based on Image and Point Cloud Data
    Wu, Youping
    Mao, Yunlei
    IEEE ACCESS, 2024, 12 : 78328 - 78341
  • [33] Automatic Forest Canopy Removal Algorithm for Underneath Obscure Target Detection by Airborne LiDAR Point Cloud Data
    Chang, Li-Der
    Slatton, K. Clint
    Anand, Vivek
    Liu, Pang-Wei
    Lee, Heezin
    Campbell, Michael V.
    DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XV, 2010, 7664
  • [34] Building Point Clouds Extraction from Airborne LiDAR Data Based on Decision Tree Method
    Lei Zhao
    Xi Xiaohuan
    Wang Cheng
    Wang Pu
    Wang Yongxing
    Yin Guoqing
    LASER & OPTOELECTRONICS PROGRESS, 2018, 55 (08)
  • [35] Airborne LiDAR point cloud classification based on deep residual network
    Zhao, Chuan
    Guo, Haitao
    Lu, Jun
    Yu, Donghang
    Zhang, Baoming
    Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2020, 49 (02): : 202 - 213
  • [36] Building contour extraction from Airborne LiDAR point cloud for Digital Line Graphic
    Kan, Yuhui
    Zhang, Tonggang
    Zhong, Dan
    Jia, Shiqiang
    Xie, Fugui
    SPIE FUTURE SENSING TECHNOLOGIES (2020), 2020, 11525
  • [37] Estimating biomass of individual trees using point cloud data of airborne LIDAR
    Liu Q.
    Li Z.
    Chen E.
    Pang Y.
    Tian X.
    Cao C.
    Gaojishu Tongxin/Chinese High Technology Letters, 2010, 20 (07): : 765 - 770
  • [38] Airborne LiDAR Point Cloud Classification Based on Attention Mechanism Point Convolutional Network
    Wang Liyuan
    Fu Lihua
    LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (10)
  • [39] A graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data
    Strimbu, Victor F.
    Strimbu, Bogdan M.
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 104 : 30 - 43
  • [40] A Filtering Algorithm of Airborne LiDAR Points Cloud Based on Least Square
    Cheng Yinglei
    Zhao Huizhen
    Qu Yayun
    Qiu Langbo
    2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA), 2014, : 24 - 27