Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely appli...Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.展开更多
The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satell...The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.展开更多
现有几何光学方法的二向反射分布函数BRDF(bidirectional reflection distribution function)模型在计算阴影遮蔽效应时普遍应用Blinn几何衰减效应假设,其等倾角V形槽近似得出的分段折线形式的几何衰减因子导致BRDF曲线存在较大的误差....现有几何光学方法的二向反射分布函数BRDF(bidirectional reflection distribution function)模型在计算阴影遮蔽效应时普遍应用Blinn几何衰减效应假设,其等倾角V形槽近似得出的分段折线形式的几何衰减因子导致BRDF曲线存在较大的误差.基于倾斜角随机高斯分布的微面元理论提出了一种新的几何衰减模型,得出了积分形式的几何衰减因子表达式,数值模拟比较了Blinn几何衰减因子与修正后的积分型衰减因子以及对应的BRDF模型曲线.结果表明:提出的几何衰减因子在物理合理性以及模拟精度方面都有明显提升,使BRDF模型曲线与已有BRDF数据之间的标准误差由0.0636减小到0.0084.展开更多
文摘Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.
基金Under the auspices the Fundamental Research Funds for the Central Universities,China(No.2017TD-26)the Plan for Changbai Mountain Scholars of Jilin Province,China(No.JJLZ[2015]54)
文摘The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.
基金We thank Dr Qin Wenhan in SSAI/GSFC,NASA,USA for his directions and help in modeling RGMThis research was supported in part by the National Natural Science Foundation of China(No40371078,40571107)Special Funds for Major State Basic Research Project(G20000779)
文摘现有几何光学方法的二向反射分布函数BRDF(bidirectional reflection distribution function)模型在计算阴影遮蔽效应时普遍应用Blinn几何衰减效应假设,其等倾角V形槽近似得出的分段折线形式的几何衰减因子导致BRDF曲线存在较大的误差.基于倾斜角随机高斯分布的微面元理论提出了一种新的几何衰减模型,得出了积分形式的几何衰减因子表达式,数值模拟比较了Blinn几何衰减因子与修正后的积分型衰减因子以及对应的BRDF模型曲线.结果表明:提出的几何衰减因子在物理合理性以及模拟精度方面都有明显提升,使BRDF模型曲线与已有BRDF数据之间的标准误差由0.0636减小到0.0084.
