CHEN Yaoyao,DENG Xiaobo,HUANG Qihong,et al.Temporal and Spatial Fusion of Air Temperature based on FY-3D and FY-4A[J].Journal of Chengdu University of Information Technology,2022,37(03):284-289.[doi:10.16836/j.cnki.jcuit.2022.03.008]
基于FY-3D和FY-4A的气温时空融合
- Title:
- Temporal and Spatial Fusion of Air Temperature based on FY-3D and FY-4A
- 文章编号:
- 2096-1618(2022)03-0284-06
- Keywords:
- satellite remote sensing; temperature products; FY-3D; FY-4A; high spatial and temporal resolution; dictionary fusion algorithm
- 分类号:
- TP79
- 文献标志码:
- A
- 摘要:
- 卫星遥感技术可大范围、连续性地获取数据,然而静止卫星的时间分辨率高,空间分辨率低; 极轨卫星的空间分辨率高,时间分辨率低。多源卫星数据融合方法能结合静止卫星的高时间分辨率特性和极轨卫星的高空间分辨率特性,从而得到高时空分辨率数据。选取湖南省作为研究区域,利用静止气象卫星FY4A和极轨气象卫星FY3D的气温产品,使用基于字典融合算法进行气温数据融合,得到时间分辨率为1 h、空间分辨率为250 m的高时空分辨率合成气温数据。从融合结果来看,此方法可以提高气温数据的空间分辨率,从得到的逐小时气温图像来看,此方法可以提高气温数据的时间分辨率。最后,将融合得到的24 h高时空分辨率的气温数据与台站数据进行时空匹配并验证。结果表明,相关系数R为0.764,均方根误差RSME为2.97 ℃,平均偏差BIAS为-1 ℃, 平均绝对百分比误差为-2.75%。
- Abstract:
- Satellite remote sensing technology can obtain data in a large range and continuously. However, geostationary satellites have high temporal resolution but low spatial resolution. Polar-orbiting satellites have high spatial resolution but low temporal resolution. The multi-source satellite data fusion method can combine the high temporal resolution characteristics of geostationary satellite and the high spatial resolution characteristics of polar-orbit satellite to obtain high temporal and spatial resolution data. In this paper, Hunan province is selected as the research area. Temperature products of geostationary meteorological satellite FY-4A and polar-orbit meteorological satellite FY-3D are used to fuse temperature data based on dictionary fusion algorithm, and synthetic temperature data with high temporal and spatial resolution of 1 h and 250 m are obtained. The results show that this method can improve the spatial resolution of air temperature data. According to the hourly temperature images, this method can improve the temporal resolution of temperature data. Finally, the 24 h high spatio-temporal resolution air temperature data obtained by fusion is matched and verified with the station data. The results show that the correlation coefficient R was 0.764, the root mean square error was 2.97 ℃, the mean bias was -1 ℃, and the mean absolute percentage error was -2.75%.
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备注/Memo
收稿日期:2022-03-11
基金项目:四川省科技计划资助项目(2021YJ0280)