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    • WHU-RuR： A high-resolution remote sensing benchmark dataset for rural （high-standard farmland） road extraction

    • “In the field of high standard farmland construction, experts have developed the first high-resolution remote sensing image rural road extraction benchmark dataset WHU RuR, providing a solution for rural road extraction.”
      • role：First author第一作者
      • Affiliation：

        School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

        College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China

      • Email：wangningjing@stu.xust.edu.cn
      • Introduction：王宁静，研究方向为高分辨率遥感图像智能解译。E-mail： wangningjing@stu.xust.edu.cn

      WANG Ningjing

      12,
      • role：Corresponding author通信作者
      • Affiliation：

        School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

        Institute of Aerospace Science and Technology, Wuhan University, Wuhan 430079, China

      • Email：wangxinyu@whu.edu.cn
      • Introduction：王心宇，研究方向为遥感信息智能处理与应用。E-mail： wangxinyu@whu.edu.cn

      WANG Xinyu

      14 * ,
      • Affiliation：

        State Key Laboratory of Information Engineering in Surveying, Wuhan University, Wuhan 430079, China

      PAN Yang

      3,
      • Affiliation：

        Department of Land Surveying and Geoinformatics, The Hong Kong Polytechnic University, Hong Kong 999077, China

      LU Xiaoyan

      5,
      • Affiliation：

        College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China

      YAO Wanqiang

      2,
      • Affiliation：

        State Key Laboratory of Information Engineering in Surveying, Wuhan University, Wuhan 430079, China

      ZHONG Yanfei

      3,
      • Affiliation：

        School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

        Institute of Aerospace Science and Technology, Wuhan University, Wuhan 430079, China

      GONG Jianya

      14
    • Vol. 29, Issue 4, Pages: 857-866(2025)  

    • DOI：10.11834/jrs.20253491    

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