摘要
该文针对卫星降水数据空间分辨率较低的问题,以湖北省为研究区域,考虑经纬度、DEM、亮温数据、IMERG插值数据等辅助变量,融合2016年7月19日IMERG日分辨率卫星降水数据与气象站点数据资料.该文提出了点面融合方法和站点偏差校正估计两个融合方案,并选择了自适应样条多元回归、随机森林、高斯过程回归三种算法.结果表明,点面融合方法优于站点偏差校正估计方法,且高斯过程回归的融合结果优于其他两种算法.基于高斯过程方法的融合结果呈现合理的变化细节,符合降水的空间分布变化模式.融合结果的空间分辨率从约0.1°(约10 km)提高到1 km,且精度相对于原始的IMERG数据得到了较大的提升,该研究对高时间分辨率的多源降水数据的融合具有一定的意义.
This paper focuses on the low spatial resolution of satellite precipitation data.The daily IMERG satellite precipitation data with rain gauge data are merged on July 19,2016 and auxiliary variables,such as longitude,latitude,DEM,brightness temperature data,and interpolation data,are considered.Taking the Hubei Province as the study area,in this paper,two fusion schemes,point-to-surface fusion method and bias-correction fusion method,are proposed.Three algorithms are selected including adaptive spline multiple regression,random forest and Gaussian process regression.The results show that the point-surface fusion method is superior to the bias-correction fusion method,and the fusion results by Gaussian process regression are better than other two algorithms.The fusion results based on the Gaussian process method show reasonable change details,which accord with the spatial pattern of precipitation.The spatial resolution of the fusion result has been improved from 0.1°(about 10 km)to 1 km,and the accuracy has been greatly improved compared to the original IMERG data.This research has certain significance for the fusion of multi-source precipitation data with high temporal resolution.
作者
谭伟伟
曾超
沈焕锋
田礼乔
TAN Weiwei;ZENG Chao;SHEN Huanfeng;TIAN Liqiao(State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University Wuhan 430079, China;School of Resource and Environmental Sciences, Wuhan University Wuhan 430079, China;Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China;Key Laboratory of Geographic Information System, Ministry of Education, Wuhan 430079, China)
出处
《华中师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2020年第3期439-446,共8页
Journal of Central China Normal University：Natural Sciences
基金
国家重点研发计划项目(2018YFC1506500)。
关键词
IMERG
降水融合
点面融合
偏差校正
高斯过程回归
IMERG
precipitation fusion
point-to-surface fusion
bias correction
Gaussian process regression
