Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition

	Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition
	Gao, Bo 1; Gong, Huili 1; Wang, Tianxing 1; Jia, Li 1
刊名	REMOTE SENSING
	2016
卷号	8 期号:9
关键词	YUKON RIVER-BASIN SUPPORT VECTOR MACHINES FLUX-TOWER MEASUREMENTS UNITED-STATES LANDSCAPE CONTROLS ESTIMATING CARBON BOREAL FOREST NORTH-AMERICA LANDSAT DATA VARIABILITY
通讯作者	Gong, HL (reprint author), Capital Normal Univ, Beijing Lab Water Resources Secur, Beijing 100048, Peoples R China. ; Gong, HL (reprint author), Capital Normal Univ, Base State Key Lab Urban Environm Proc & Digital, Beijing 100048, Peoples R China. ; Gong, HL (reprint author), Capital Normal Univ, Minist Educ, Key Lab Informat Acquisit & Applicat 3D, Beijing 100048, Peoples R China. ; Gong, HL (reprint author), Capital Normal Univ, Coll Resources Environm & Tourism, Beijing 100048, Peoples R China.
英文摘要	Clouds usually cause invalid observations for sensors aboard satellites, which corrupts the spatio-temporal continuity of land surface parameters retrieved from remote sensing data (e.g., MODerate Resolution Imaging Spectroradiometer (MODIS) data) and prevents the fusing of multi-source remote sensing data in the field of quantitative remote sensing. Based on the requirements of spatio-temporal continuity and the necessity of methods to restore bad pixels, primarily resulting from image processing, this study developed a novel method to derive the spectral reflectance for MODIS band of cloudy pixels in the visual-near infrared (VIS-NIR) spectral channel based on the Bidirectional Reflectance Distribution Function (BRDF) and multi-spatio-temporal observations. The proposed method first constructs the spatial distribution of land surface reflectance based on the corresponding BRDF and the solar-viewing geometry; then, a geographically weighted regression (GWR) is introduced to individually derive the spectral surface reflectance for MODIS band of cloudy pixels. A validation of the proposed method shows that a total root-mean-square error (RMSE) of less than 6% and a total R-2 of more than 90% are detected, which indicates considerably better precision than those exhibited by other existing methods. Further validation of the retrieved white-sky albedo based on the spectral reflectance for MODIS band of cloudy pixels confirms an RMSE of 3.6% and a bias of 2.2%, demonstrating very high accuracy of the proposed method.
学科主题	Remote Sensing
类目[WOS]	Remote Sensing
收录类别	SCI
语种	英语
WOS记录号	WOS:000385488000037
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39544]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.Capital Normal Univ, Beijing Lab Water Resources Secur, Beijing 100048, Peoples R China 2.Capital Normal Univ, Base State Key Lab Urban Environm Proc & Digital, Beijing 100048, Peoples R China 3.Capital Normal Univ, Minist Educ, Key Lab Informat Acquisit & Applicat 3D, Beijing 100048, Peoples R China 4.Capital Normal Univ, Coll Resources Environm & Tourism, Beijing 100048, Peoples R China 5.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Gao, Bo,Gong, Huili,Wang, Tianxing,et al. Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition[J]. REMOTE SENSING,2016,8(9).
APA	Gao, Bo,Gong, Huili,Wang, Tianxing,&Jia, Li.(2016).Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition.REMOTE SENSING,8(9).
MLA	Gao, Bo,et al."Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition".REMOTE SENSING 8.9(2016).