Spacecraft Recovery & Remote Sensing, Volume. 45, Issue 6, 113(2024)

Landcover Classification Method for Multispectral Satellite Remote Sensing Imagery Based on Improved YOLOv5

Yong LIU... Weili YANG, Pengyu GUO, Lu CAO, Xinhui WANG, Ling MENG and Weidong ZHAO |Show fewer author(s)
Author Affiliations
  • National Innovation Institute of Defense Technology, Academy of Military Sciences, Beijing 100071, China
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    Figures & Tables(13)
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    • Table 1. Comparison of performance of different bands

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      Table 1. Comparison of performance of different bands

      波段mIoU稻田灌溉地旱地园地乔木林灌木林自然草地人工草地工业用地城市住宅农村住宅道路河流湖泊池塘
      RGB+NIR55.553.291.147.322.175.617.069.545.263.374.064.459.055.672.423.4
      RGB53.052.887.643.819.573.416.566.242.063.273.963.956.752.971.523.0
    • Table 2. Comparison of FPN and FPN+PAN performance

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      Table 2. Comparison of FPN and FPN+PAN performance

      颈部网络mIoU稻田灌溉地旱地园地乔木林灌木林自然草地人工草地工业用地城市住宅农村住宅道路河流湖泊池塘
      FPN36.141.283.919.310.860.62.054.412.445.061.136.92.535.862.013.3
      FPN+PAN55.553.291.147.322.175.617.069.545.263.374.064.459.055.672.423.4
    • Table 3. Comparison of FCN and ProtoNet performance

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      Table 3. Comparison of FCN and ProtoNet performance

      分割头mIoU稻田灌溉地旱地园地乔木林灌木林自然草地人工草地工业用地城市住宅农村住宅道路河流湖泊池塘
      FCN50.951.685.640.121.474.311.968.430.462.973.461.454.954.470.721.7
      ProtoNet55.553.291.147.322.175.617.069.545.263.374.064.459.055.672.423.4
    • Table 4. Comparison of different networks performance

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      Table 4. Comparison of different networks performance

      网络类型mIoU稻田灌溉地旱地园地乔木林灌木林自然草地人工草地工业用地城市住宅农村住宅道路河流湖泊池塘
      VN-YOLOv5-Seg55.553.291.147.322.175.617.069.545.263.374.064.459.055.672.423.4
      PSPNet52.954.485.640.121.474.311.968.430.462.973.461.454.957.568.028.7
      DeepLabV354.356.689.241.121.270.215.664.537.964.173.962.559.360.973.523.6
      U-Net54.155.790.144.019.574.212.264.038.964.474.463.757.655.270.727.9
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    Yong LIU, Weili YANG, Pengyu GUO, Lu CAO, Xinhui WANG, Ling MENG, Weidong ZHAO. Landcover Classification Method for Multispectral Satellite Remote Sensing Imagery Based on Improved YOLOv5[J]. Spacecraft Recovery & Remote Sensing, 2024, 45(6): 113

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    Paper Information

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    Received: Feb. 21, 2024

    Accepted: Feb. 21, 2024

    Published Online: Jan. 23, 2025

    The Author Email:

    DOI:10.3969/j.issn.1009-8518.2024.06.010

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