An improved non-linear inter-calibration method on different radiometers for enhancing coverage of daily LST estimates in low latitudes

doi:10.1016/j.rse.2021.112626

	An improved non-linear inter-calibration method on different radiometers for enhancing coverage of daily LST estimates in low latitudes
	Song, Peilin; Zhang, Yongqiang
刊名	REMOTE SENSING OF ENVIRONMENT
	2021-10-01
卷号	264 页码:17
关键词	FY3B microwave radiation imager (FY3B-MWRI) Brightness temperature (TB) Land surface temperature (LST) Fraction of water surface (FWS) Advanced microwave scanning Radiometer-2 (ASMR-2)
ISSN号	0034-4257
DOI	10.1016/j.rse.2021.112626
通讯作者	Zhang, Yongqiang(zhangyq@igsnrr.ac.cn)
英文摘要	Most polar-orbit-satellite based passive microwave radiometers, e.g. AMSR-2 and the FY-3B Microwave Radiation Imager (FY3B-MWRI), have the revisit cycles of-2 days in low latitudes. This indicates that requirement of complete global coverage on the daily basis has not been met. On the other hand, using synergistic observations from different radiometers seems promising to enhance the temporal resolution of observations in such areas, whereas cross-radiometer inter-calibration is essential prior to their synergism. For this purpose, conventional inter-calibration models are usually built based on linear relations of brightness temperature (TB) between different radiometers. However, the linear model has relatively poor performance in low latitudes primarily due to wet surface conditions. In this study, we propose an improved non-linear model for calibrating MWRI TB against AMSR-2 TB at 18.7 GHz and 23.8 GHz channels. Global land surface temperature (LST) is estimated using the post-calibration MWRI TB data and then validated against AMSR-2 based LST, MODIS based LST, and in situ near-surface air temperature datasets in low latitudes respectively. The validation results show that LST outcome based on the improved non-linear inter-calibration method has smaller global Root Mean Square Errors (RMSEs) below 3.5 K, compared with the RMSEs of-6 K obtained from the conventional linear inter-calibration method and from the results without inter-calibration. Further analysis also shows that synergistic observations between AMSR-2 and MWRI are capable of shortening the maximum global revisit cycle of AMSR-2 LST from-2 days to less than 1.2 days. These results indicate that the improved inter-calibration method is effective for obtaining daily LST datasets with quasi-complete global coverage and reliable accuracy.
资助项目	National Natural Science Foundation of China[42001304] ; National Natural Science Foundation of China[41971032] ; National Natural Science Foundation of China[52009127] ; CAS Pioneer Talents Program ; CAS Special Research Assistant Funding Program
WOS关键词	LAND-SURFACE TEMPERATURE ; SIMPLE RETRIEVAL METHOD ; AMSR-E ; BRIGHTNESS TEMPERATURE ; AIR-TEMPERATURE ; SATELLITE ; SSM/I ; ALGORITHM ; DEPTH ; CHINA
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000688490900004
资助机构	National Natural Science Foundation of China ; CAS Pioneer Talents Program ; CAS Special Research Assistant Funding Program
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/165161]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Yongqiang
作者单位	Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Song, Peilin,Zhang, Yongqiang. An improved non-linear inter-calibration method on different radiometers for enhancing coverage of daily LST estimates in low latitudes[J]. REMOTE SENSING OF ENVIRONMENT,2021,264:17.
APA	Song, Peilin,&Zhang, Yongqiang.(2021).An improved non-linear inter-calibration method on different radiometers for enhancing coverage of daily LST estimates in low latitudes.REMOTE SENSING OF ENVIRONMENT,264,17.
MLA	Song, Peilin,et al."An improved non-linear inter-calibration method on different radiometers for enhancing coverage of daily LST estimates in low latitudes".REMOTE SENSING OF ENVIRONMENT 264(2021):17.