摘要
目前国内外对遥感数据云层检测和处理的研究取得了诸多成果,但对各类云层检测和处理算法的整理分析相对滞后,一定程度上阻碍了研究的进展。鉴于此,通过分析拥有代表性的相关文献,对现有云层检测和处理算法进行了整理概括,得到主流算法能有效满足当前需求,但对遥感数据特征的综合运用不足,无法有效满足将来需求的结论。同时,对将来研究的方向进行了展望,认为基于开源在线平台的深度学习和多时相、多源遥感数据处理的综合运用能有效应对云层的检测和处理。
Extensive research into the detection and processing of clouds in remote sensing data has led to the development of different methods,but subsequent categorization and analysis of these findings are largely pending,which now hinders further research.To address this issue,we analyzed representative research findings and gave a brief review on current algorithms of cloud detection and processing.The result shows that mainstream algorithms can effectively deal with current demands,but cannot effectively meet future requirements due to the lack of full use of all available features.The comprehensive application of deep learning based on open source online platform and multi-temporal and multi-source remote sensing data processing can effectively deal with cloud detection and processing.
作者
王叶天鉴
胡昌华
WANG Yetianjian;HU Changhua(Guangzhou Urban Planning&Design Survey Research Institute,Guangzhou 510060,China)
出处
《地理空间信息》
2023年第9期139-144,共6页
Geospatial Information
关键词
云层
多时相
多源遥感数据
时间序列
深度学习
cloud
multi-temporal
multi-source remote sensing data
time series
deep learning