Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle   Implementation of Atmospheric Correction (MAIAC) Data

doi:10.3390/rs9040370

CORC > 北京大学 > 地球与空间科学学院

	Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data
	Chen, Chi ; Knyazikhin, Yuri ; Park, Taejin ; Yan, Kai ; Lyapustin, Alexei ; Wang, Yujie ; Yang, Bin ; Myneni, Ranga B.
刊名	REMOTE SENSING
	2017
关键词	MAIAC MODIS leaf area index (LAI) fraction of photosynthetically active radiation (FPAR) radiative transfer LEAF-AREA INDEX PART 1 SURFACE REFLECTANCE VEGETATION PRODUCTS ALGORITHM FRACTION TERRA VALIDATION AMAZON
DOI	10.3390/rs9040370
英文摘要	Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) absorbed by vegetation are key variables in many global models of climate, hydrology, biogeochemistry, and ecology. These parameters are being operationally produced from Terra and Aqua MODIS bidirectional reflectance factor (BRF) data. The MODIS science team has developed, and plans to release, a new version of the BRF product using the multi-angle implementation of atmospheric correction (MAIAC) algorithm from Terra and Aqua MODIS observations. This paper presents analyses of LAI and FPAR retrievals generated with the MODIS LAI/FPAR operational algorithm using Terra MAIAC BRF data. Direct application of the operational algorithm to MAIAC BRF resulted in an underestimation of the MODIS Collection 6 (C6) LAI standard product by up to 10%. The difference was attributed to the disagreement between MAIAC and MODIS BRFs over the vegetation by -2% to +8% in the red spectral band, suggesting different accuracies in the BRF products. The operational LAI/FPAR algorithm was adjusted for uncertainties in the MAIAC BRF data. Its performance evaluated on a limited set of MAIAC BRF data from North and South America suggests an increase in spatial coverage of the best quality, high-precision LAI retrievals of up to 10%. Overall MAIAC LAI and FPAR are consistent with the standard C6 MODIS LAI/FPAR. The increase in spatial coverage of the best quality LAI retrievals resulted in a better agreement of MAIAC LAI with field data compared to the C6 LAI product, with the RMSE decreasing from 0.80 LAI units (C6) down to 0.67 (MAIAC) and the R-2 increasing from 0.69 to 0.80. The slope (intercept) of the satellite-derived vs. field-measured LAI regression line has changed from 0.89 (0.39) to 0.97 (0.25).; NASA [NNX14AI71G, NNX14AP80A]; HBO contract [21205-14-036]; SCI(E); ARTICLE; 4; 9
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/474158]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Chen, Chi,Knyazikhin, Yuri,Park, Taejin,et al. Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data[J]. REMOTE SENSING,2017.
APA	Chen, Chi.,Knyazikhin, Yuri.,Park, Taejin.,Yan, Kai.,Lyapustin, Alexei.,...&Myneni, Ranga B..(2017).Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data.REMOTE SENSING.
MLA	Chen, Chi,et al."Prototyping of LAI and FPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data".REMOTE SENSING (2017).