利用多尺度遥感图像,基于 G-CNN 进行作物分类

IF 1.4 4区 地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Remote Sensing Letters Pub Date : 2024-08-22 DOI:10.1080/2150704x.2024.2388848
Mengmeng Meng, Kaixin Zhang, Yabo Huang, Ning Li, Zhengwei Guo, Zhimin Zhou
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引用次数: 0

摘要

作物分类对于监测作物生长和确保国家粮食安全非常重要。农作物地块具有复杂的空间种植结构,并有一定程度的破碎化,这就需要对其进行分类。
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Crop classification based on G-CNN using multi-scale remote sensing images
Crop classification is important for monitoring crop growth and ensuring national food security. Crop plots have a complex spatial planting structure with a certain degree of fragmentation, which l...
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来源期刊
Remote Sensing Letters
Remote Sensing Letters REMOTE SENSING-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
4.10
自引率
4.30%
发文量
92
审稿时长
6-12 weeks
期刊介绍: Remote Sensing Letters is a peer-reviewed international journal committed to the rapid publication of articles advancing the science and technology of remote sensing as well as its applications. The journal originates from a successful section, of the same name, contained in the International Journal of Remote Sensing from 1983 –2009. Articles may address any aspect of remote sensing of relevance to the journal’s readership, including – but not limited to – developments in sensor technology, advances in image processing and Earth-orientated applications, whether terrestrial, oceanic or atmospheric. Articles should make a positive impact on the subject by either contributing new and original information or through provision of theoretical, methodological or commentary material that acts to strengthen the subject.
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