Lidar Point Cloud Processing

Lidar Point Cloud Processing is a computational methodology that transforms raw three-dimensional point cloud data acquired through Lidar remote sensing into structured, interpretable information by applying algorithms for filtering, segmentation, classification, and feature extraction specific to the geometric and radiometric properties of the points.

1.3K

Publications

69.2K

Citations

4.1K

Authors

1K

Institutions

Publications per year

2017–2026

859

Authors

4.1K

  1. JL
    Jonathan Li

    University of Waterloo, Canada

    38 publications · 2.3K citations

    25

    h-index

  2. CW
    Cheng Wang

    Xiamen University, China

    25 publications · 1.3K citations

    20

    h-index

  3. YY
    Yongtao Yu

    Huaiyin Institute of Technology, China

    16 publications · 1K citations

    16

    h-index

  4. RW
    Ruisheng Wang

    University of Calgary, Canada

    13 publications · 528 citations

    13

    h-index

  5. BY
    Bisheng Yang

    Wuhan University, China

    13 publications · 1K citations

    13

    h-index

1–5 of 4.1K

Venues

  1. 46

    h-index

  2. Remote Sensing

    120 publications · 5K citations

    41

    h-index

  3. Sensors

    41 publications · 1.8K citations

    25

    h-index

  4. 21

    h-index

  5. arXiv (Cornell University)

    Repository · 37 publications · 1.5K citations

    21

    h-index

1–5