基于线性核驱动模型的BRDF模型集成与案例分析
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摘要
二向性反射是自然界中物体表面反射的基本现象。为研究地表的二向性反射特征,国内外学者发展了一系列BRDF模型,其中,半经验、线性、核驱动的BRDF模型已被广泛应用。目前,我们已发布基于线性核驱动模型的可视化界面MaKeMAT。为进一步便于这些模型的应用,本研究将用户常用的物理BRDF模型与线性核驱动BRDF模型进一步集成,在原模型功能的基础上,加强了模型与用户的交互,实现了多个模型的统一调用。同时,初步分析了部分物理BRDF模型与线性核驱动BRDF模型的耦合效果。结果表明:物理BRDF模型与线性核驱动BRDF模型总体耦合精度较高,在红和近红外波段,决定系数R2可达0.899~0.989。该集成有助于用户进行BRDF的研究与应用示范,在遥感模型集成的技术层面上,也可为实现多模型集成提供技术参考。
Anisotropic reflectance is the intrinsic characteristic of an object surface.over the past few decades,various BRDF models have been developed for investigating the relationship between the vegetation canopy and reflectance anisotropy.This helps to retrieve biophysical parameters from the anisotropic reflectance patterns of vegetation canopy.In this study,for the purpose of assisting potential users to use these models,and to improve the understanding of the BRDF modeling,several BRDF models that are widely used in the remote sensing community have been integrated with the current version of the MaKeMAT(Multi-angular Kernel-driven Model Analysis Tool),based on the Interactive Data Language(IDL).This work retains all functions of the current version of the MaKeMAT model,meanwhile,adds some new functions by integrating these physical BRDF models.Undoubtedly,this work facilitates the potential users to process BRDF data and make further analysis in their work by operating a simpler visual interface.This helps to build a rapid communication between the kernel-driven BRDF models and the physical BRDF models.Our initial results show that this model-integration practice is a valuable reference for potential users to devise a similar technique.Our case study in coupling these physical BRDF models with the kernel-driven models present a high correlation between them,with the determination of coefficients(R2)reaching0.899~0.989 in the red and NIR bands.
Anisotropic reflectance is the intrinsic characteristic of an object surface.over the past few decades,various BRDF models have been developed for investigating the relationship between the vegetation canopy and reflectance anisotropy.This helps to retrieve biophysical parameters from the anisotropic reflectance patterns of vegetation canopy.In this study,for the purpose of assisting potential users to use these models,and to improve the understanding of the BRDF modeling,several BRDF models that are widely used in the remote sensing community have been integrated with the current version of the MaKeMAT(Multi-angular Kernel-driven Model Analysis Tool),based on the Interactive Data Language(IDL).This work retains all functions of the current version of the MaKeMAT model,meanwhile,adds some new functions by integrating these physical BRDF models.Undoubtedly,this work facilitates the potential users to process BRDF data and make further analysis in their work by operating a simpler visual interface.This helps to build a rapid communication between the kernel-driven BRDF models and the physical BRDF models.Our initial results show that this model-integration practice is a valuable reference for potential users to devise a similar technique.Our case study in coupling these physical BRDF models with the kernel-driven models present a high correlation between them,with the determination of coefficients(R2)reaching0.899~0.989 in the red and NIR bands.
引文
[1]Liu Jia,Fan Wenyi.Review on BRDF Model and the Inversion Strategy[J],Remote Sensing Technology and Application,2008,24(1):104-110.[刘佳,范文义.BRDF模型及其反演研究的现状及展望[J].遥感技术与应用,2008,24(1):104-110.]
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[5]Wei H,Hua Y.Winter Wheat Leaf Area Index Retrieval with Multi-angle and Multi-spectral Terra/Aqua MODIS Data[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(4):204-212.
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[7]Kuusk A.A Two-Layer Canopy Reflectance Model[J].Journal of Quantitative Spectroscopy&Radiative Transfer,2001,71(1):1-9.
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[10]Chen J M,Menges C H,Leblanc S G.Global Mapping of Foliage Clumping Index Using Multi-angular Satellite Data[J].Remote Sensing of Environment,2005,97(4):447-457.
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[13]Li Xiao,Du Yongming,Xu Daqi et al.A Remote Sensing Model Integration Platform Design and Implementation Oriented the Quantitative Remote Sensing Research[J].Remote Sensing Technology and Application,2015,30(2):285-291.[李晓,杜永明,徐大琦,等.面向定量遥感研究的遥感模型集成平台设计与实现[J].遥感技术与应用,2015,30(2):285-291.]
[14]Zarco-Tejada P J,Miller J R,Verhoef W,et al.FluorMODgui V3.0:A Graphic User Interface for the Spectral Simulation of Leaf and Canopy Chlorophyll Fluorescence[J].Computers&Geosciences,2006,32(5):577-591.
[15]Vermote E F,Tanre D,Deuze J L,et al.Second Simulation of the Satellite Signal in the Solar Spectrum,6S:An Overview[J].1997,35(3):675-686.
[16]Dong Y,Jiao Z,Zhang H,et al.A Visualization Tool for the Kernel-driven Model with Improved Ability in Data Analysis and Kernel Assessment[J].Computers&Geosciences,2016,95:1-10.
[17]Jiao Z,Schaaf C B,Dong Y,et al.A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODIS[J].Remote Sensing of Environment,2016,186:135-151
[18]Kuusk,A.A Markov Chain Model of Canopy Reflectance[J].Agricultural&Forest Meteorology,1995,76(3):221-236.
[19]Kuusk A,Nilson T.A Directional Multispectral Forest Reflectance Model[J].Remote Sensing of Environment,2000,72(2):244-252.
[20]Kuusk A,Lang M,Nilson T.Simulation of the Reflectance of Ground Vegetation in Sub-boreal Forests[J].Agricultural and Forest Meteorology,2004,126(1-2):33-46.
[21]Bai Dongni,Jiao Ziti,Dong Yadong,et al..Analysis of Sensitivity of the Anisotropic Flat Index(AFX)to Vegetation Parameters,based on the Two-Layer Canopy Reflectance Model[J].Journal of Remote Sensing,2017,21(1):1-11.[白冬妮,焦子锑,董亚冬,等.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[J].遥感学报,2017,21(1):1-11.]
[22]Jacquemoud S.Inversion of the PROSPECT+SAIL Canopy Reflectance Model from AVIRIS Equivalent Spectra:Theoretical Study.[J].Remote Sensing of Environment,1993,44(2-3):281-292.
[23]Wang Lijuan,Niu Zheng.Sensitivity Analysis of Vegetation Parameters based on PROSAIL Model[J].Remote Sensing Technology and Application,2014,29(2):219-223.[王李娟,牛铮.PROSAIL模型的参数敏感性研究[J].遥感技术与应用,2014,29(2):219-223.]
[24]Ma Jianwei,Huang Shifeng,Li Jiren,et al.Global Sensitivity Analysis of Parameters in the PROSAIL Model based on Modified Sobol’s Method[J].Bulletin of Surveying and Mapping,2016,(3):33-35.[马建威,黄诗峰,李纪人,等.改进Sobol算法支持下的PROSAIL模型参数全局敏感性分析[J].测绘通报,2016,(3):33-35.]
[25]Tripathi R,Sahoo R N,Sehgal V K,et al.Inversion of PROSAIL Model for Retrieval of Plant Biophysical Parameters[J].Journal of the Indian Society of Remote Sensing,2012,40(1):19-28.
[26]Chen J M,Leblanc S G.A Four-scale Bidirectional Reflectance Model based on Canopy Architecture[J].IEEE Transactions on Geoscience&Remote Sensing,1997,35(5):1316-1337.
[27]Kotchenova S Y,Vermote E F,Matarrese R,et al.Validation of a Vector Version of the 6SRadiative Transfer Code for Atmospheric Correction of Satellite Data.Part I:Path Radiance[J].Optical Applicata,2006,45(26):6762-6774.
[28]Kotchenova S Y,Vermote E F,Levy R,et al.Radiative Transfer Codes for Atmospheric Correction and Aerosol Retrieval:Intercomparison Study[J].Optical Applicata,2008,47(13):2215-2226.
[29]Li X,Strahler A H.Modeling the Gap Probability of a Discontinuous Vegetation Canopy[J].IEEE Transactions on Geoscience&Remote Sensing,1988,26(2):161-170.
[30]Li X,Strahler A H,Woodcock C.A Hybrid Geometric-optical Radiative-Transfer Model for Directional Reflectance of Discontinuous Vegetation Canopies[C]∥Geoscience and Remote Sensing Symposium,1994.IGARSS′94.Surface and Atmospheric Remote Sensing:Technologies,Data Analysis and Interpretation.International.IEEE,1995:1829-1831.
[31]Li C,Song J,Wang J.The Exploring Research of a Geometric Optical Canopy Reflectance Model(GOMS)for Retrieving Leaf Area Index Directly[C]∥IEEE International Geoscience&Remote Sensing Symposium,2014:808-811.
[2]Nicodemus F E,Richmond J C,Hsia J J,et al.Geometrical Considerations and Nomenclature for Reflectance[Z].1977.
[3]Zhao Yingshi.Principle and Method of Remote Sensing Application Analysis[M].Beijing:Science Press,2013.[赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2013.]
[4]Zhang Hu,Jiao Ziti,Dong Yadong,et al.Albedo Retrieved from BRDF Archetype and Surface Directional Reflectance[J],Journal of Remote Sensing,2015,19(3):355-367.[张虎,焦子锑,董亚冬,等.利用BRDF原型和单方向反射率数据估算地表反照率[J].遥感学报,2015,19(3):355-367.]
[5]Wei H,Hua Y.Winter Wheat Leaf Area Index Retrieval with Multi-angle and Multi-spectral Terra/Aqua MODIS Data[J].Transactions of the Chinese Society of Agricultural Engineering,2013,29(4):204-212.
[6]Ma Q,Li J,Liu Q,et al.Calculation of Clumping Index of Mixed Pixel and Scale Analysis.[J].2011,58(11):775-778.
[7]Kuusk A.A Two-Layer Canopy Reflectance Model[J].Journal of Quantitative Spectroscopy&Radiative Transfer,2001,71(1):1-9.
[8]Jacquemoud S P,Verhoef W,Baret F D R,et al.PROSPECT+SAIL Models:A Review of Use for Vegetation Characterization[J].Remote Sensing of Environment,2009,113:56-66.
[9]Leblanc S G,Chen J M.A Windows Graphic User Interface(GUI)for the Five-scale Model for Fast BRDF Simulations[J].Remote Sensing Reviews,2000,19(1-4):293-305.
[10]Chen J M,Menges C H,Leblanc S G.Global Mapping of Foliage Clumping Index Using Multi-angular Satellite Data[J].Remote Sensing of Environment,2005,97(4):447-457.
[11]He L,Chen J M,Pisek J,et al.Global Clumping Index Map Derived from the MODIS BRDF Product[J].Remote Sensing of Environment,2012,119(11):118-130.
[12]Tang Xijin.Model Integration[J],Journal of Systems Engineering,2001,16(5):322-329.[唐锡晋.模型集成[J].系统工程学报,2001,16(5):322-329.]
[13]Li Xiao,Du Yongming,Xu Daqi et al.A Remote Sensing Model Integration Platform Design and Implementation Oriented the Quantitative Remote Sensing Research[J].Remote Sensing Technology and Application,2015,30(2):285-291.[李晓,杜永明,徐大琦,等.面向定量遥感研究的遥感模型集成平台设计与实现[J].遥感技术与应用,2015,30(2):285-291.]
[14]Zarco-Tejada P J,Miller J R,Verhoef W,et al.FluorMODgui V3.0:A Graphic User Interface for the Spectral Simulation of Leaf and Canopy Chlorophyll Fluorescence[J].Computers&Geosciences,2006,32(5):577-591.
[15]Vermote E F,Tanre D,Deuze J L,et al.Second Simulation of the Satellite Signal in the Solar Spectrum,6S:An Overview[J].1997,35(3):675-686.
[16]Dong Y,Jiao Z,Zhang H,et al.A Visualization Tool for the Kernel-driven Model with Improved Ability in Data Analysis and Kernel Assessment[J].Computers&Geosciences,2016,95:1-10.
[17]Jiao Z,Schaaf C B,Dong Y,et al.A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODIS[J].Remote Sensing of Environment,2016,186:135-151
[18]Kuusk,A.A Markov Chain Model of Canopy Reflectance[J].Agricultural&Forest Meteorology,1995,76(3):221-236.
[19]Kuusk A,Nilson T.A Directional Multispectral Forest Reflectance Model[J].Remote Sensing of Environment,2000,72(2):244-252.
[20]Kuusk A,Lang M,Nilson T.Simulation of the Reflectance of Ground Vegetation in Sub-boreal Forests[J].Agricultural and Forest Meteorology,2004,126(1-2):33-46.
[21]Bai Dongni,Jiao Ziti,Dong Yadong,et al..Analysis of Sensitivity of the Anisotropic Flat Index(AFX)to Vegetation Parameters,based on the Two-Layer Canopy Reflectance Model[J].Journal of Remote Sensing,2017,21(1):1-11.[白冬妮,焦子锑,董亚冬,等.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[J].遥感学报,2017,21(1):1-11.]
[22]Jacquemoud S.Inversion of the PROSPECT+SAIL Canopy Reflectance Model from AVIRIS Equivalent Spectra:Theoretical Study.[J].Remote Sensing of Environment,1993,44(2-3):281-292.
[23]Wang Lijuan,Niu Zheng.Sensitivity Analysis of Vegetation Parameters based on PROSAIL Model[J].Remote Sensing Technology and Application,2014,29(2):219-223.[王李娟,牛铮.PROSAIL模型的参数敏感性研究[J].遥感技术与应用,2014,29(2):219-223.]
[24]Ma Jianwei,Huang Shifeng,Li Jiren,et al.Global Sensitivity Analysis of Parameters in the PROSAIL Model based on Modified Sobol’s Method[J].Bulletin of Surveying and Mapping,2016,(3):33-35.[马建威,黄诗峰,李纪人,等.改进Sobol算法支持下的PROSAIL模型参数全局敏感性分析[J].测绘通报,2016,(3):33-35.]
[25]Tripathi R,Sahoo R N,Sehgal V K,et al.Inversion of PROSAIL Model for Retrieval of Plant Biophysical Parameters[J].Journal of the Indian Society of Remote Sensing,2012,40(1):19-28.
[26]Chen J M,Leblanc S G.A Four-scale Bidirectional Reflectance Model based on Canopy Architecture[J].IEEE Transactions on Geoscience&Remote Sensing,1997,35(5):1316-1337.
[27]Kotchenova S Y,Vermote E F,Matarrese R,et al.Validation of a Vector Version of the 6SRadiative Transfer Code for Atmospheric Correction of Satellite Data.Part I:Path Radiance[J].Optical Applicata,2006,45(26):6762-6774.
[28]Kotchenova S Y,Vermote E F,Levy R,et al.Radiative Transfer Codes for Atmospheric Correction and Aerosol Retrieval:Intercomparison Study[J].Optical Applicata,2008,47(13):2215-2226.
[29]Li X,Strahler A H.Modeling the Gap Probability of a Discontinuous Vegetation Canopy[J].IEEE Transactions on Geoscience&Remote Sensing,1988,26(2):161-170.
[30]Li X,Strahler A H,Woodcock C.A Hybrid Geometric-optical Radiative-Transfer Model for Directional Reflectance of Discontinuous Vegetation Canopies[C]∥Geoscience and Remote Sensing Symposium,1994.IGARSS′94.Surface and Atmospheric Remote Sensing:Technologies,Data Analysis and Interpretation.International.IEEE,1995:1829-1831.
[31]Li C,Song J,Wang J.The Exploring Research of a Geometric Optical Canopy Reflectance Model(GOMS)for Retrieving Leaf Area Index Directly[C]∥IEEE International Geoscience&Remote Sensing Symposium,2014:808-811.