Using Triple Collocation Observations to Estimate Satellite Measurement Noise

doi:10.1109/TGRS.2021.3060781

	Using Triple Collocation Observations to Estimate Satellite Measurement Noise
	Chen, Jun 1; Quan, Wenting 2; Wang, Kexin 3; Han, Qijin 4; Liu, Jia 5; Xing, Qianguo6 ; Xu, Na 7
发表期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN	0196-2892
	2022
卷号	60 页码:11
关键词	Sea measurements Noise measurement Instruments Oceans Image color analysis Satellite broadcasting Atmospheric measurements Instrument noise instrumental noise ocean color remote sensing triple collocation observation (TCO) algorithm
DOI	10.1109/TGRS.2021.3060781
通讯作者	Xu, Na([email protected])
英文摘要	Knowing how much measurement noise is in a signal is critical for evaluating the overall performance of a satellite observation. We developed a triple collocation observation (TCO) algorithm for estimating measurement noise by collocation comparing the local deviations of three satellite data sets. When we evaluated our algorithm with a synthetic data set, the results showed that the algorithm effectively derived measurement noise from satellite signals despite the many intermission signal differences among the satellites. The TCO algorithm produced x003C;6.66x0025; uncertainty in the measurement noise estimates that we derived from the synthetic data set. In addition, to maximally isolate measurement noise from ocean color images, we developed a set of data quality control criteria to apply when identifying synchronous pixel pairs. Using images from the Medium Resolution Spectral Imager II (MERSI II), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, we applied our data quality control criteria and found that the TCO algorithm produced measurement noise consistent with the measured prelaunch or specifications for VIIRS and MERSI II instrument noise. However, the TCO measurement noise was significantly lower than the spaced MODIS noise because MODISx2019;s extended service time likely produced instrument degradation. Overall, MODIS performed better than MERSI II but worse than VIIRS. Furthermore, we found that the residual error in remote sensing reflectance exponentially decreased as the measurement signal-to-noise ratio (MSNR) increased. Because of this exponential relationship, the MSNR should not be lower than 181 to achieve the x003C;5x0025; uncertainty goal of remote sensing reflectance at 443 nm that NASA proposed. Our results suggest that the TCO algorithm is an effective approach for comprehensively estimating and comparing instrument performance.
资助机构	National Natural Science Foundation of China ; International Cooperation in Science and Technology Innovation among Governments ; National Key R&D Program of China
收录类别	SCI
语种	英语
关键词[WOS]	OCEAN-ATMOSPHERE SYSTEM ; REFLECTIVE SOLAR BANDS ; SIGNAL-TO-NOISE ; MODIS AQUA ; CROSS-CALIBRATION ; NPP VIIRS ; COLOR ; SENSORS ; REQUIREMENTS ; DEGRADATION
研究领域[WOS]	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000728266600104
引用统计
文献类型	期刊论文
条目标识符	http://ir.yic.ac.cn/handle/133337/37975
专题	中国科学院海岸带环境过程与生态修复重点实验室中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
通讯作者	Xu, Na
作者单位	1.Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Peoples R China 2.Shaanxi Meteorol Serv Ctr Agr Remote Sensing & Ec, Xian 71000, Peoples R China 3.China Univ Geosci, Sch Ocean Sci, Beijing 100083, Peoples R China 4.Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Peoples R China 5.Chinese Acad Sci, Key Lab Spectral Imaging Technol CAS, Xian Inst Optic & Precis Mech, Xian 71000, Peoples R China 6.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China 7.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Chen, Jun,Quan, Wenting,Wang, Kexin,et al. Using Triple Collocation Observations to Estimate Satellite Measurement Noise[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:11.
APA	Chen, Jun.,Quan, Wenting.,Wang, Kexin.,Han, Qijin.,Liu, Jia.,...&Xu, Na.(2022).Using Triple Collocation Observations to Estimate Satellite Measurement Noise.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,11.
MLA	Chen, Jun,et al."Using Triple Collocation Observations to Estimate Satellite Measurement Noise".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):11.