IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i11p1863-d1504504.html
   My bibliography  Save this article

Extraction of Canal Distribution Information Based on UAV Remote Sensing System and Object-Oriented Method

Author

Listed:
  • Xuefei Huo

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Li Li

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Xingjiao Yu

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Long Qian

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Qi Yin

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Kai Fan

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Yingying Pi

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Yafei Wang

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Wen’e Wang

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Xiaotao Hu

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

Abstract

At present, the extraction of irrigation canal network distribution information is of great significance for developing a digital twin irrigation district. However, due to the low resolution of remote sensing images, it is difficult to effectively identify the canal networks, especially for channels with a width of less than 1 m, where recognition is insufficient. Therefore, the purpose of this study is to extract canal networks of different widths in an irrigation district in Shaanxi Province as the research area. A rule-based object-oriented classification method was employed, utilizing image data collected by the DJI Mavic 3 multispectral UAV (Unmanned Aerial Vehicle) to explore the accuracy of this method in extracting canal distribution information. Based on UAV multispectral remote sensing imagery, the segmentation parameters for the remote sensing imagery were determined using ENVI 5.6 software, with the segmentation threshold set at 60 and the merging threshold set at 80. By combining the spectral and spatial differences between the canals and other ground objects, rules for extracting canal network distribution information were established, and the information on the distribution of channels in this irrigation area was finally obtained. The experimental results showed a maximum recall rate of 91.88% and a maximum precision rate of 57.59%. The overall recall precision rates for the irrigation district were 85.74% and 55.08%, respectively. This method provides a new solution for identifying and extracting canal systems in irrigation districts, offering valuable insights for acquiring canal distribution information and providing a scientific basis for precision irrigation.

Suggested Citation

  • Xuefei Huo & Li Li & Xingjiao Yu & Long Qian & Qi Yin & Kai Fan & Yingying Pi & Yafei Wang & Wen’e Wang & Xiaotao Hu, 2024. "Extraction of Canal Distribution Information Based on UAV Remote Sensing System and Object-Oriented Method," Agriculture, MDPI, vol. 14(11), pages 1-18, October.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:11:p:1863-:d:1504504
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/11/1863/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/11/1863/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xianyu Yu & Yang Xia & Jianguo Zhou & Weiwei Jiang, 2023. "Correction: Yu et al. Landslide Susceptibility Mapping Based on Multitemporal Remote Sensing Image Change Detection and Multiexponential Band Math. Sustainability 2023, 15 , 2226," Sustainability, MDPI, vol. 15(12), pages 1-2, June.
    2. Louise T. Su, 1994. "The relevance of recall and precision in user evaluation," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(3), pages 207-217, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Azzah Al‐Maskari & Mark Sanderson, 2010. "A review of factors influencing user satisfaction in information retrieval," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(5), pages 859-868, May.
    2. Yue Lin & Ningchuan Xiao, 2023. "Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data: The Case of the 2020 U.S. Census," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(5), pages 1-20, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:11:p:1863-:d:1504504. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.