双冠层反射率模型分析各向异性平整指数(AFX)对植被参数的敏感性
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摘要
二向反射分布函数包含地表反射的方向性特征信息。研究二向反射分布函数BRDF(Bidirectional Reflectance Distribution Function)形状对植被结构参数的敏感性,有助于理解植被的二向性反射规律,进而反演植被参数。本文耦合双冠层反射率模型和核驱动的罗斯厚核-李氏稀疏互易核模型,利用EFAST全局敏感性分析方法,以各向异性平整指数为BRDF形状变化的衡量指标,研究了不同天空光比例(SKYL)下,各向异性平整指数AFX对植被参数敏感度的变化,以及SKYL=0.1时AFX的敏感性。结果表明:(1)在红波段,上、下层叶面积指数、上层叶绿素含量,以及上层叶倾角分布是AFX的敏感参数,在近红外波段,上、下层叶面积指数LAI是AFX的敏感参数。(2)冠层尺度上的参数敏感度总体大于叶片尺度。(3)晴天时(SKYL=0.1),红波段主敏感度较大的参数分别是上层LAI、上层叶倾角分布和下层叶片结构参数,近红外波段主敏感度较大的参数主要是上、下层LAI。
Bidirectional Reflectance Distribution Function(BRDF) contains directional information on surface reflectance and provides important orientation information in calculating the surface time-space variable elements. The analysis of the sensitivity of BRDF shapes to vegetation structure parameters contributes to understanding the laws of vegetation bidirectional reflectance and increasing the accuracy in inversing vegetation parameters. Numerous scholars have investigated different BRDF models to determine the relationship between vegetation structure parameters and bidirectional reflectance distribution effects of the vegetation surface. Among these models, the two-layer canopy reflectance model(ACRM model) and kernel-driven model are generally accepted as physical and semiempirical models, respectively. This study explores the sensitivity of BRDF shapes to vegetation structure parameters by coupling the ACRM model and kernel-driven Ross-Thick/Li-Sparse-Reciprocal model(RTLSR model). The adopted sensitivity analysis method is the extended Fourier amplitude sensitivity test, one of the global sensitivity analysis methods. The Anisotropic Flat inde X(AFX) is employed as the metric for BRDF shapes to explore the sensitivity change in AFX to vegetation parameters under the condition of different SKY Light ratios(SKYL) and sensitivity with SKYL=0.1. From these variables, this study explores the sensitivity parameters with SKYL=0.1. Then, the relationship between the main sensitivity parameters and AFX is analyzed. Overall, AFX can indicate the change in BRDF shapes. The kernel-driven RTLSR model can fit the data produced by the ACRM model well. Results of the analysis of sensitivity indicate that the change in sky light results in different degrees of sensitivity. Given the influence of sky light, parameter sensitivity at the canopy scale is larger than that at the leaf scale. Under sunny conditions(SKYL=0.1), the total order sensitivity index of the upper Leaf Area Index(LAI) is strongest in the red band, and lower LAI is observed in the near-infrared band.The first-order sensitivity indices of the upper LAI, upper leaf angle distribution, and lower leaf structure parameters are stronger in the red band. Meanwhile, the first-order sensitivity indices of the upper and lower LAI are stronger in the near-infrared band. AFX plays an important role in increasing inversion accuracy. The index is significant in understanding the relationship between AFX and the surface-covering physical parameters for the inversion of the parameters. This study analyzed the sensitivity of AFX to vegetation structure parameters. The results will help researchers understand the effects of changes in vegetation parameters on BRDF shapes.
Bidirectional Reflectance Distribution Function(BRDF) contains directional information on surface reflectance and provides important orientation information in calculating the surface time-space variable elements. The analysis of the sensitivity of BRDF shapes to vegetation structure parameters contributes to understanding the laws of vegetation bidirectional reflectance and increasing the accuracy in inversing vegetation parameters. Numerous scholars have investigated different BRDF models to determine the relationship between vegetation structure parameters and bidirectional reflectance distribution effects of the vegetation surface. Among these models, the two-layer canopy reflectance model(ACRM model) and kernel-driven model are generally accepted as physical and semiempirical models, respectively. This study explores the sensitivity of BRDF shapes to vegetation structure parameters by coupling the ACRM model and kernel-driven Ross-Thick/Li-Sparse-Reciprocal model(RTLSR model). The adopted sensitivity analysis method is the extended Fourier amplitude sensitivity test, one of the global sensitivity analysis methods. The Anisotropic Flat inde X(AFX) is employed as the metric for BRDF shapes to explore the sensitivity change in AFX to vegetation parameters under the condition of different SKY Light ratios(SKYL) and sensitivity with SKYL=0.1. From these variables, this study explores the sensitivity parameters with SKYL=0.1. Then, the relationship between the main sensitivity parameters and AFX is analyzed. Overall, AFX can indicate the change in BRDF shapes. The kernel-driven RTLSR model can fit the data produced by the ACRM model well. Results of the analysis of sensitivity indicate that the change in sky light results in different degrees of sensitivity. Given the influence of sky light, parameter sensitivity at the canopy scale is larger than that at the leaf scale. Under sunny conditions(SKYL=0.1), the total order sensitivity index of the upper Leaf Area Index(LAI) is strongest in the red band, and lower LAI is observed in the near-infrared band.The first-order sensitivity indices of the upper LAI, upper leaf angle distribution, and lower leaf structure parameters are stronger in the red band. Meanwhile, the first-order sensitivity indices of the upper and lower LAI are stronger in the near-infrared band. AFX plays an important role in increasing inversion accuracy. The index is significant in understanding the relationship between AFX and the surface-covering physical parameters for the inversion of the parameters. This study analyzed the sensitivity of AFX to vegetation structure parameters. The results will help researchers understand the effects of changes in vegetation parameters on BRDF shapes.
引文
Bowyer P and Danson F M.2004.Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level.Re mote Sensing of Environment,92(3):297-308[DOI10.1016/j.rse.2004.05.020]
Bréon F M,Maignan F,Leroy M and Grant I.2002.Analysis of ho spot directional signatures measured from space.Journal of Geo physical Research,107(D16):AAC 1-1-AAC 1-15[DOI10.1029/2001JD001094]
Chen J M and Cihlar J.1997.A hotspot function in a simple bidirec tional reflectance model for satellite applications.Journal of Geo physical Research-Atmospheres,102(D22):25907-25913[DOI10.1029/97JD02010]
Cheng Y B,Middleton E M,Zhang Q Y,Corp L A,Dandois J and Kustas W P.2012.The photochemical reflectance index from dir ectional cornfield reflectances:observations and simulations.Re mote Sensing of Environment,124:444-453[DOI10.1016/j.rse.2012.05.030]
Cukier R I,Fortuin C M,Shuler K E,Petschek A G and Schaibly J H1973.Study of the sensitivity of coupled reaction systems to un certainties in rate coefficients.I:theory.The Journal of Chemica Physics,59(8):3873-3878[DOI:10.1063/1.1680571]
Dong Y D,Jiao Z T,Zhang H,Li J Y,Jiao G P and Shi H Y.2014.Ef ficient algorithm for improving the hotspot effect of the operation al MODIS BRDF product.Journal of Remote Sensing,18(4)804-825(董亚冬,焦子锑,张虎,李佳悦,焦广平,石涵予.2014改善MODIS BRDF产品热点效应的方法研究.遥感学报,18(4)804-825)
Eriksson H M,Eklundh L,Kuusk A and Nilson T.2006.Impact of un derstory vegetation on forest canopy reflectance and remotely sensed LAI estimates.Remote Sensing of Environment,103(4)408-418[DOI:10.1016/j.rse.2006.04.005]
Hirsch J E.2005.An index to quantify an individual’s scientific re search output.Proceedings of the National Academy of Sciences of the United States of America,102(46):16569-16572[DOI10.1073/pnas.0507655102]
Jacquemoud S and Baret F.1990.Prospect:a model of leaf optica properties spectra.Remote Sensing of Environment,34(2):75-91[DOI:10.1016/0034-4257(90)90100-Z]
Jacquemoud S and Baret F.1993.Estimating vegetation biophysica parameters by inversion of a reflectance model on high spectra resolution data//Varlet-Grancher C,Bonhomme R and Sinoque H,eds.Crop Structure and Light Microclimate:Characterization and Applications.Versailles(France):Editions de I’INRA339-350
Jacquemoud S,Verhoef W,Baret F,Bacour C,Zarco-Tejada P J,As ner G P,Fran?ois C and Ustin S L.2009.PROSPECT+SAIL mod els:a review of use for vegetation characterization.Remote Sens ing of Environment,113:S56-S66[DOI:10.1016/j.rse2008.01.026]
Jiao Z T,Dong Y D and Li X W.2013.An approach to improve ho spot effect for the MODIS BRDF/albedo algorithm//Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium(IGARSS).Melbourne:IEEE:3037-3039[DOI10.1109/IGARSS.2013.6723466]
Jiao Z T,Hill M J,Schaaf C B,Zhang H,Wang Z S and Li X W.2014An Anisotropic Flat Index(AFX)to derive BRDF archetypes from MODIS.Remote Sensing of Environment,141:168-187[DOI10.1016/j.rse.2013.10.017]
Kuusk A.1991.Determination of vegetation canopy parameters from optical measurements.Remote Sensing of Environment,37(3)207-218[DOI:10.1016/0034-4257(91)90082-H]
Kuusk A.2001.A two-layer canopy reflectance model.Journal o Quantitative Spectroscopy and Radiative Transfer,71(1):1-9[DOI:10.1016/S0022-4073(01)00007-3]
Kuusk A,Lang M and Nilson T.2004.Simulation of the reflectance o ground vegetation in sub-boreal forests.Agricultural and Fores Meteorology,126(1/2):33-46[DOI:10.1016/j.agrformet2004.05.004]
Liu S H,Liu Q,Liu Q H,Wen J G and Li X W.2010.The angular and spectral kernel model for BRDF and albedo retrieval.IEEE Journ al of Selected Topics in Applied Earth Observations and Remote Sensing,3(3):241-256[DOI:10.1109/JSTARS.2010.2048745]
Lucht W,Schaaf C B and Strahler A H.2000.An algorithm for the re trieval of albedo from space using semiempirical BRDF models IEEE Transactions on Geoscience and Remote Sensing,38(2)977-998[DOI:10.1109/36.841980]
Maignan F,Bréon F M and Lacaze R.2004.Bidirectional reflectance of Earth targets:evaluation of analytical models using a large se of spaceborne measurements with emphasis on the Hot Spot.Re mote Sensing of Environment,90(2):210-220[DOI10.1016/j.rse.2003.12.006]
Mc Cartney H A.1978.Spectral distribution of solar radiation.II:glob al and diffuse.Quarterly Journal of the Royal Meteorological So ciety,104(442):911-926[DOI:10.1002/qj.49710444205]
Nicodemus F E,Richmond J C,Hsia J J,Ginsberg I W and Limperis T1977.Geometrical Considerations and Nomenclature for Reflect ance.Washington,DC:National Bureau of Standards,US Depart ment of Commerce
Price J C.1990.On the information content of soil reflectance spectra Remote Sensing of Environment,33(2):113-121[DOI10.1016/0034-4257(90)90037-M]
Roujean J L,Leroy M and Deschamps P Y.1992.A bidirectional re flectance model of the earth’s surface for the correction of remote sensing data.Journal of Geophysical Research-Atmospheres97(D18):20455-20468[DOI:10.1029/92JD01411]
Saltelli A,Tarantola S and Chan K P S.1999.A quantitative model-in dependent method for global sensitivity analysis of model output Technometrics,41(1):39-56[DOI:10.1080/004017061999.10485594]
Schaaf C B,Gao F,Strahler A H,Lucht W,Li X W,Tsang T,Strugnel N C,Zhang X Y,Jin Y F,Muller J P,Lewis P,Barnsley M,Hob son P,Disney M,Roberts G,Dunderdale M,Doll C,D’Entremon R P,Hu B X,Liang S L,Privette J L and Roy D.2002.First oper ational BRDF,albedo nadir reflectance products from MODISRemote Sensing of Environment,83(1/2):135-148[DOI10.1016/S0034-4257(02)00091-3]
Schaepman-Strub G,Schaepman M E,Painter T H,Dangel S and Mar tonchik J V.2006.Reflectance quantities in optical remote sens ing-definitions and case studies.Remote Sensing of Environment103(1):27-42[DOI:10.1016/j.rse.2006.03.002]
Shi R H,Zhuang D F,Niu Z and Wang W.2005.Influence of meso phyll structure on leaf spectra and biochemical inversion.Journa of the Graduate School of the Chinese Academy of Sciences22(5):589-595(施润和,庄大方,牛铮,王汶.2005.叶肉结构对叶片光谱及生化组分定量反演的影响.中国科学院研究生院学报,22(5):589-595)[DOI:10.3969/j.issn.1002-1175.2005.05.009]
Sobol I M.1993.Sensitivity analysis for nonlinear mathematical mod els.Mathematical Modeling and Computational Experiment,1(4)407-414[translation of Sobol I M.(1990).Sensitivity estimates fo nonlinear mathematical models.Matematicheskoe Modelirovanie2(1):112-118(in Russian)]
Wanner W,Li X and Strahler A H.1995.On the derivation of kernel for kernel-driven models of bidirectional reflectance.Journal o Geophysical Research-Atmospheres,100(D10):21077-21089[DOI:10.1029/95JD02371]
Xiao Y F,Zhou D M,Gong H L and Zhao W J.2015.Sensitivity o canopy reflectance to biochemical and biophysical variables Journal of Remote Sensing,19(3):368-374(肖艳芳,周德民,宫辉力,赵文吉.2015.冠层反射光谱对植被理化参数的全局敏感性分析.遥感学报,19(3):368-374)[DOI:10.11834/jrs20153330]
Zhang H,Jiao Z T,Dong Y D,Li J Y and Li X W.2015.Albedo re trieved from BRDF archetype and Surface dirface directional re lectance.Journal of Remote Sensing,19(3):355-367(张虎,焦子锑,董亚东,李佳悦,李小文.2015.利用BRDF原型和单方向反射率数据估算地表反照率.遥感学报,19(3):355-367)[DOI10.11834/jrs20154131]
Bréon F M,Maignan F,Leroy M and Grant I.2002.Analysis of ho spot directional signatures measured from space.Journal of Geo physical Research,107(D16):AAC 1-1-AAC 1-15[DOI10.1029/2001JD001094]
Chen J M and Cihlar J.1997.A hotspot function in a simple bidirec tional reflectance model for satellite applications.Journal of Geo physical Research-Atmospheres,102(D22):25907-25913[DOI10.1029/97JD02010]
Cheng Y B,Middleton E M,Zhang Q Y,Corp L A,Dandois J and Kustas W P.2012.The photochemical reflectance index from dir ectional cornfield reflectances:observations and simulations.Re mote Sensing of Environment,124:444-453[DOI10.1016/j.rse.2012.05.030]
Cukier R I,Fortuin C M,Shuler K E,Petschek A G and Schaibly J H1973.Study of the sensitivity of coupled reaction systems to un certainties in rate coefficients.I:theory.The Journal of Chemica Physics,59(8):3873-3878[DOI:10.1063/1.1680571]
Dong Y D,Jiao Z T,Zhang H,Li J Y,Jiao G P and Shi H Y.2014.Ef ficient algorithm for improving the hotspot effect of the operation al MODIS BRDF product.Journal of Remote Sensing,18(4)804-825(董亚冬,焦子锑,张虎,李佳悦,焦广平,石涵予.2014改善MODIS BRDF产品热点效应的方法研究.遥感学报,18(4)804-825)
Eriksson H M,Eklundh L,Kuusk A and Nilson T.2006.Impact of un derstory vegetation on forest canopy reflectance and remotely sensed LAI estimates.Remote Sensing of Environment,103(4)408-418[DOI:10.1016/j.rse.2006.04.005]
Hirsch J E.2005.An index to quantify an individual’s scientific re search output.Proceedings of the National Academy of Sciences of the United States of America,102(46):16569-16572[DOI10.1073/pnas.0507655102]
Jacquemoud S and Baret F.1990.Prospect:a model of leaf optica properties spectra.Remote Sensing of Environment,34(2):75-91[DOI:10.1016/0034-4257(90)90100-Z]
Jacquemoud S and Baret F.1993.Estimating vegetation biophysica parameters by inversion of a reflectance model on high spectra resolution data//Varlet-Grancher C,Bonhomme R and Sinoque H,eds.Crop Structure and Light Microclimate:Characterization and Applications.Versailles(France):Editions de I’INRA339-350
Jacquemoud S,Verhoef W,Baret F,Bacour C,Zarco-Tejada P J,As ner G P,Fran?ois C and Ustin S L.2009.PROSPECT+SAIL mod els:a review of use for vegetation characterization.Remote Sens ing of Environment,113:S56-S66[DOI:10.1016/j.rse2008.01.026]
Jiao Z T,Dong Y D and Li X W.2013.An approach to improve ho spot effect for the MODIS BRDF/albedo algorithm//Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium(IGARSS).Melbourne:IEEE:3037-3039[DOI10.1109/IGARSS.2013.6723466]
Jiao Z T,Hill M J,Schaaf C B,Zhang H,Wang Z S and Li X W.2014An Anisotropic Flat Index(AFX)to derive BRDF archetypes from MODIS.Remote Sensing of Environment,141:168-187[DOI10.1016/j.rse.2013.10.017]
Kuusk A.1991.Determination of vegetation canopy parameters from optical measurements.Remote Sensing of Environment,37(3)207-218[DOI:10.1016/0034-4257(91)90082-H]
Kuusk A.2001.A two-layer canopy reflectance model.Journal o Quantitative Spectroscopy and Radiative Transfer,71(1):1-9[DOI:10.1016/S0022-4073(01)00007-3]
Kuusk A,Lang M and Nilson T.2004.Simulation of the reflectance o ground vegetation in sub-boreal forests.Agricultural and Fores Meteorology,126(1/2):33-46[DOI:10.1016/j.agrformet2004.05.004]
Liu S H,Liu Q,Liu Q H,Wen J G and Li X W.2010.The angular and spectral kernel model for BRDF and albedo retrieval.IEEE Journ al of Selected Topics in Applied Earth Observations and Remote Sensing,3(3):241-256[DOI:10.1109/JSTARS.2010.2048745]
Lucht W,Schaaf C B and Strahler A H.2000.An algorithm for the re trieval of albedo from space using semiempirical BRDF models IEEE Transactions on Geoscience and Remote Sensing,38(2)977-998[DOI:10.1109/36.841980]
Maignan F,Bréon F M and Lacaze R.2004.Bidirectional reflectance of Earth targets:evaluation of analytical models using a large se of spaceborne measurements with emphasis on the Hot Spot.Re mote Sensing of Environment,90(2):210-220[DOI10.1016/j.rse.2003.12.006]
Mc Cartney H A.1978.Spectral distribution of solar radiation.II:glob al and diffuse.Quarterly Journal of the Royal Meteorological So ciety,104(442):911-926[DOI:10.1002/qj.49710444205]
Nicodemus F E,Richmond J C,Hsia J J,Ginsberg I W and Limperis T1977.Geometrical Considerations and Nomenclature for Reflect ance.Washington,DC:National Bureau of Standards,US Depart ment of Commerce
Price J C.1990.On the information content of soil reflectance spectra Remote Sensing of Environment,33(2):113-121[DOI10.1016/0034-4257(90)90037-M]
Roujean J L,Leroy M and Deschamps P Y.1992.A bidirectional re flectance model of the earth’s surface for the correction of remote sensing data.Journal of Geophysical Research-Atmospheres97(D18):20455-20468[DOI:10.1029/92JD01411]
Saltelli A,Tarantola S and Chan K P S.1999.A quantitative model-in dependent method for global sensitivity analysis of model output Technometrics,41(1):39-56[DOI:10.1080/004017061999.10485594]
Schaaf C B,Gao F,Strahler A H,Lucht W,Li X W,Tsang T,Strugnel N C,Zhang X Y,Jin Y F,Muller J P,Lewis P,Barnsley M,Hob son P,Disney M,Roberts G,Dunderdale M,Doll C,D’Entremon R P,Hu B X,Liang S L,Privette J L and Roy D.2002.First oper ational BRDF,albedo nadir reflectance products from MODISRemote Sensing of Environment,83(1/2):135-148[DOI10.1016/S0034-4257(02)00091-3]
Schaepman-Strub G,Schaepman M E,Painter T H,Dangel S and Mar tonchik J V.2006.Reflectance quantities in optical remote sens ing-definitions and case studies.Remote Sensing of Environment103(1):27-42[DOI:10.1016/j.rse.2006.03.002]
Shi R H,Zhuang D F,Niu Z and Wang W.2005.Influence of meso phyll structure on leaf spectra and biochemical inversion.Journa of the Graduate School of the Chinese Academy of Sciences22(5):589-595(施润和,庄大方,牛铮,王汶.2005.叶肉结构对叶片光谱及生化组分定量反演的影响.中国科学院研究生院学报,22(5):589-595)[DOI:10.3969/j.issn.1002-1175.2005.05.009]
Sobol I M.1993.Sensitivity analysis for nonlinear mathematical mod els.Mathematical Modeling and Computational Experiment,1(4)407-414[translation of Sobol I M.(1990).Sensitivity estimates fo nonlinear mathematical models.Matematicheskoe Modelirovanie2(1):112-118(in Russian)]
Wanner W,Li X and Strahler A H.1995.On the derivation of kernel for kernel-driven models of bidirectional reflectance.Journal o Geophysical Research-Atmospheres,100(D10):21077-21089[DOI:10.1029/95JD02371]
Xiao Y F,Zhou D M,Gong H L and Zhao W J.2015.Sensitivity o canopy reflectance to biochemical and biophysical variables Journal of Remote Sensing,19(3):368-374(肖艳芳,周德民,宫辉力,赵文吉.2015.冠层反射光谱对植被理化参数的全局敏感性分析.遥感学报,19(3):368-374)[DOI:10.11834/jrs20153330]
Zhang H,Jiao Z T,Dong Y D,Li J Y and Li X W.2015.Albedo re trieved from BRDF archetype and Surface dirface directional re lectance.Journal of Remote Sensing,19(3):355-367(张虎,焦子锑,董亚东,李佳悦,李小文.2015.利用BRDF原型和单方向反射率数据估算地表反照率.遥感学报,19(3):355-367)[DOI10.11834/jrs20154131]