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基于语义边缘和空间结构图的高分辨率遥感图像中的作物田提取

IF 3.3 4区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Geocarto International Pub Date : 2024-01-24 DOI:10.1080/10106049.2024.2302176
Liegang Xia, Ruiyan Liu, Yishao Su, Shulin Mi, Dezhi Yang, Jun Chen, Zhanfeng Shen
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引用次数: 0

摘要

作物田边界提取对遥感图像支持农业生产和规划至关重要。近年来，深度卷积神经网络（CNN）在农业领域得到了广泛应用。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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Crop field extraction from high resolution remote sensing images based on semantic edges and spatial structure map
Crop field boundary extraction is crucial to remote sensing images attained to support agricultural production and planning. In recent years, deep convolutional neural networks (CNNs) have gained s...
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来源期刊
Geocarto International
Geocarto International ENVIRONMENTAL SCIENCES-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
6.30
自引率
13.20%
发文量
407
审稿时长
>12 weeks
期刊介绍： Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community. The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines; Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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