| U-Net模型对不同空间分辨率防护林提取精度的影响 |
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| 引用本文： | 王学文,赵庆展,田文忠,龙翔,江萍.U-Net模型对不同空间分辨率防护林提取精度的影响[J].测绘通报,2021,0(6):39-43. |
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| 作者姓名： | 王学文 赵庆展 田文忠 龙翔 江萍 |
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| 作者单位： | 1. 石河子大学信息科学与技术学院, 新疆 石河子 832000;2. 兵团空间信息工程技术研究中心, 新疆 石河子 832000;3. 石河子大学机械电气工程学院, 新疆 石河子 832000 |
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| 基金项目： | 新疆生产建设兵团科技计划（2017DB005）；兵团空间信息工程技术研究中心创建项目（2016BA001）；中央引导地方科技发展专项资金项目（201610011） |
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| 摘 要： | 针对当前无人机影像获取精度高但数据规模小的问题,本文提出通过U-Net模型探讨不同空间分辨率对防护林提取精度的影响.以CW-20复合翼无人机搭载Micro MAC12 Snap多光谱传感器获取的300 m(空间分辨率0.15 m)、400 m(空间分辨率0.20 m)、500 m(空间分辨率0.25 m)3种不同高度的...
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| 关 键 词： | 无人机 多光谱影像 空间分辨率 防护林提取 U-Net模型 |
| 收稿时间： | 2020-11-17 |
Influence of U-Net model on the accuracy of shelter forest extraction with different spatial resolutions |
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| WANG Xuewen,ZHAO Qingzhan,TIAN Wenzhong,LONG Xiang,JIANG Ping.Influence of U-Net model on the accuracy of shelter forest extraction with different spatial resolutions[J].Bulletin of Surveying and Mapping,2021,0(6):39-43. |
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| Authors: | WANG Xuewen ZHAO Qingzhan TIAN Wenzhong LONG Xiang JIANG Ping |
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| Institution: | 1. College of Information Science & Technology, Shihezi University, Shihezi 832000, China;2. Geospatial Information Engineering Research Center, Xinjiang Construction Corps, Shihezi 832000, China;3. College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China |
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| Abstract: | Aiming at the problem of high-accuracy of UAV image acquisition but small data scale, this paper proposes to use U-Net model to explore the influence of different spatial resolution on the extraction accuracy of farmland shelterbelts. Take the CW-20 compound-wing UAV equipped with Micro MAC12 Snap multispectral sensor obtained three different height of 300 m(spatial resolution 0.15 m), 400 m(spatial resolution 0.20 m) and 500 m(spatial resolution 0.25 m) as an example. For remote sensing images, experiments results have shown that the accuracy error of image extraction at three different height is within 1.3%, and the accuracy error of MIoU is within 3.7%. The spatial resolution had little effect on the extraction accuracy of shelterbelts. The image data with high spatial resolution can not significantly improve the extraction accuracy of shelterbelts. This study provides a theoretical basis for the acquisition of large-scale agricultural and forestry remote sensing monitoring data sources. |
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| Keywords: | UAV multi-spectral image spatial resolution shelterbelts extraction U-Net model |
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