徐保东等:Analysis of Global LAI/FPAR Products from VIIRS and MODIS Sensors for Spatio-Temporal Consistency and Uncertainty from 2012-2016
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2018-05-08
Analysis of Global LAI/FPAR Products from VIIRS and MODIS Sensors for Spatio-Temporal Consistency and Uncertainty from 2012-2016
作者:Xu, BD (Xu, Baodong)[ 1,2,3 ] ; Park, T (Park, Taejin)[ 2 ] ; Yan, K (Yan, Kai)[ 2 ] ; Chen, C (Chen, Chi)[ 2 ] ; Zeng, YL (Zeng, Yelu)[ 4 ] ; Song, WJ (Song, Wanjuan)[ 2 ] ; Yin, GF (Yin, Gaofei)[ 5 ] ; Li, J (Li, Jing)[ 1,3 ] ; Liu, QH (Liu, Qinhuo)[ 3 ] ; Knyazikhin, Y (Knyazikhin, Yuri)[ 2 ] ; Myneni, RB (Myneni, Ranga B.)[ 2 ] 
FORESTS
卷: 9  期: 2
文献号: 73
DOI: 10.3390/f9020073
出版年: FEB 2018
文献类型:Article
 
摘要
The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) algorithm has been successfully implemented for Visible Infrared Imager Radiometer Suite (VIIRS) observations by optimizing a small set of configurable parameters in Look-Up-Tables (LUTs). Our preliminary evaluation showed reasonable agreement between VIIRS and MODIS LAI/FPAR retrievals. However, there is a need for a more comprehensive investigation to assure continuity of multi-sensor global LAI/FPAR time series, as the preliminary evaluation was spatiotemporally limited. In this study, we use a multi-year (2012-2016) global LAI/FPAR product generated from VIIRS and MODIS to evaluate for spatiotemporal consistency. We also quantify uncertainty of the product by utilizing available ground measurements. For both consistency and uncertainty evaluation, we account for variations in biome type and temporal resolution. Our results indicate that the LAI/FPAR retrievals from VIIRS and MODIS are consistent at different spatial (i.e., global and site) and temporal (i.e., 8-day, seasonal and annual) scales. The estimate of mean discrepancy (-0.006 +/- 0.013 for LAI and -0.002 +/- 0.002 for FPAR) meets the stability requirement for long-term LAI/FPAR Earth System Data Records (ESDRs) from multi-sensors as suggested by the Global Climate Observing System (GCOS). It is noteworthy that the rate of retrievals from the radiative transfer-based main algorithm is also comparable between two sensors. However, a relatively larger discrepancy over tropical forests was observed due to reflectance saturation and an unexpected interannual variation of main algorithm success was noticed due to instability in input surface reflectances. The uncertainties/relative uncertainties of VIIRS and MODIS LAI (FPAR) products assessed through comparisons to ground measurements are estimated to be 0.60/42.2% (0.10/24.4%) and 0.55/39.3% (0.11/26%), respectively. Note that the validated LAI were only distributed in low domains (similar to 2.5), resulting in large relative uncertainty. Therefore, more ground measurements are needed to achieve a more comprehensive evaluation result of product uncertainty. The results presented here generally imbue confidence in the consistency between VIIRS and MODIS LAI/FPAR products and the feasibility of generating long-term multi-sensor LAI/FPAR ESDRs time series.
 
通讯作者地址: Park, T (通讯作者)
Boston Univ, Dept Earth & Environm, Boston, MA 02215 USA.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Boston Univ, Dept Earth & Environm, Boston, MA 02215 USA
[ 3 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 4 ] Carnegie Inst Sci, Dept Global Ecol, Stanford, CA 94305 USA
[ 5 ] Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China