A Framework for Consistent Estimation of Leaf Area Index, Fraction of Absorbed Photosynthetically Active Radiation, and Surface Albedo from MODIS Time-Series Data

作者:Xiao, ZQ (Xiao, Zhiqiang)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 2,3 ] ; Wang, JD (Wang, Jindi)[ 1 ] ; Xie, DH (Xie, Donghui)[ 1 ] ; Song, JL (Song, Jinling)[ 1 ] ; Fensholt, R (Fensholt, Rasmus)[ 4 ]

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

卷: 53  期: 6  页: 3178-3197

DOI: 10.1109/TGRS.2014.2370071

出版年: JUN 2015

摘要

Currently available land-surface parameter products are generated using parameter-specific algorithms from various satellite data and contain several inconsistencies. This paper developed a new data assimilation framework for consistent estimation of multiple land-surface parameters from time-series MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data. If the reflectance data showed snow-free areas, an ensemble Kalman filter (EnKF) technique was used to estimate leaf area index (LAI) for a two-layer canopy reflectance model (ACRM) by combining predictions from a phenology model and the MODIS surface reflectance data. The estimated LAI values were then input into the ACRM to calculate the surface albedo and the fraction of absorbed photosynthetically active radiation (FAPAR). For snow-covered areas, the surface albedo was calculated as the underlying vegetation canopy albedo plus the weighted distance between the underlying vegetation canopy albedo and the albedo over deep snow. The LAI/FAPAR and surface albedo values estimated using this framework were compared with MODIS collection 5 eight-day 1-km LAI/FAPAR products (MOD15A2) and 500-m surface albedo product (MCD43A3), and GEOV1 LAI/FAPAR products at 1/112. spatial resolution and a ten-day frequency, respectively, and validated by ground measurement data from several sites with different vegetation types. The results demonstrate that this new data assimilation framework can estimate temporally complete land-surface parameter profiles from MODIS time-series reflectance data even if some of the reflectance data are contaminated by residual cloud or are missing and that the retrieved LAI, FAPAR, and surface albedo values are physically consistent. The root mean square errors of the retrieved LAI, FAPAR, and surface albedo against ground measurements are 0.5791, 0.0453, and 0.0190, respectively.

通讯作者地址: Xiao, ZQ (通讯作者)

Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

[ 3 ] Univ Maryland, Dept Geog, College Pk, MD 20742 USA

[ 4 ] Univ Copenhagen, Dept Geog & Geol, DK-1350 Copenhagen, Denmark