基于LAI的航天遥感图像仿真与系统集成
摘要
本文在系统地介绍了国内外光学成像仿真技术发展概况的基础上,分别对地表反射率生成、大气辐射传输、光学传感器原理进行了分析,提出基于叶面积指数等地表参数的航天遥感图像仿真流程。研究了基于先验知识的地表反射率生成思路,确立了获取LAI的模型和方法。通过对辐射传输模型MODTRAN4各输入参数进行深入分析,确定了各参数所使用的插值方法及插值点,建立了样条插值和线性插值相结合的大气辐射传输查找表查找方法。分别研究了传感器空间响应、光谱响应、噪声模拟及采样和量化等过程。利用Matlab编写各个过程的程序代码,集成了航天遥感图像仿真系统。该系统以LAI为输入信息,可以对不同的大气状况及传感器状况进行模拟,最终实现对任意传感器进行图像模拟。
The development of optical imaging Simulation is introduced, and space remote sensing image simulation process based on the leaf area index and other surface parameters is studied in the paper, which anglicizing the surface reflectivity, atmospheric radiation transfer and optical sensor theory. In this paper the model and method for LAI is researched and the generating ideas about earth's surface albedo based in priori knowledge is established. The radiative transfer model based on the input parameters of MODTRAN4 are in deep analysis. determining the parameters of the interpolation method and points, the atmospheric look-up-table are constructed with the spline and linear interpolation.
In this paper, sensor spatial response, spectral response and the process of sampling and quantization are also introduced. Matlab is used to write the procedure of process, integrating the space remote sensing image simulation system. LAI data is input in this system, simulating for the different atmospheric conditions and sensor, and finally got the image of any sensors.
The development of optical imaging Simulation is introduced, and space remote sensing image simulation process based on the leaf area index and other surface parameters is studied in the paper, which anglicizing the surface reflectivity, atmospheric radiation transfer and optical sensor theory. In this paper the model and method for LAI is researched and the generating ideas about earth's surface albedo based in priori knowledge is established. The radiative transfer model based on the input parameters of MODTRAN4 are in deep analysis. determining the parameters of the interpolation method and points, the atmospheric look-up-table are constructed with the spline and linear interpolation.
In this paper, sensor spatial response, spectral response and the process of sampling and quantization are also introduced. Matlab is used to write the procedure of process, integrating the space remote sensing image simulation system. LAI data is input in this system, simulating for the different atmospheric conditions and sensor, and finally got the image of any sensors.
引文
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Allen,W.A.,Gausman,H.W.,Richardson,A.J. Plant canopy irradiance specified by the Duntley equations [J].Opt.Soc.Am.1970,60:372-376.
Amundsen R. M., Feldhaus W. S, Little A D, et al. Integration of design, structural, thermal and optical analysis and user's guide for structural-to-optical translator (PATCOD)[M].NASA TM-110153.1995:22
Bacour C., Baret F., Beal D., et al. Neural network estimation of LAI, fAPAR, fCover and LAI×Cab,from top of canopy MERIS reflectance data:principles and validation[J]. Remote Sensing of Environment,2006,105:313-325.
Banon G.J.F., Fonseca L.M.G. CBERS simulation from SPOT and its restoration[G]//CP 515,12201-970 Sao Jose dos Campos, SP. Brazil:Institute National de Pesquisas Espaciais-INPE.1998
Berk, Anderson G. P., Acharya P. K, et al. MODTRAN4 USER'S MANUAL[R].1999,6.
Chen J. M., Black T A Defining leaf-area index for non-flat leaves[J].Plant Cell.Environ.1992,15,421-429.
Chen J.M., Chen X. Y., Ju W. M. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs[J].Journal of Hydrology,2005,305:15-39
Chen J.M., Cihlar J. Retrieving Leaf Area Index for Boreal Conifer Forests Using Landsat TM Images [J].Remote Sensing of Environment,1996,55:153-162.
Chen J.M., Leblanc S.A.4-Scale Bidirectional Reflection Model Based on Canopy Architecture[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35:1316-1337.
Chen J.M. Evaluation of Vegetation Indices and a Modified Simple Ratio for Boreal Applications [J].IEEE Transactions on Geoscience and Remote Sensing,1996,34:1353-1368.
Dereniak, E.L. and G.D. Boreman. Infrared Detectors and Systems. New York, NY, Wiley-Inter-science,1996,560 p.
Gasser G. Application research toolbox technology overview:NASA earth science applications directorate [M].[S.l.]John C Space Center,2001
Goel N.S. Models of Vegetation Canopy Reflectance and Their Use in Estimation of Biophysical Parameters from Reflectance Data [J]. Remote Sens. Rev.1988,4:1-212
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Jacquemoud,S. and Baret,F. Andrieu,B.et al. Extraction of vegetation biophysical parameters by inversion of the PROSPECT+SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors [J].Remote Sens.Envir.,1995,52:163-172
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Kuusk,A. The hotspot effect of a uniform vegetation cover[J].Remote Sens,1985,3:646-658.
Lacia A.A, Hansen J.E, A parameterization for the absorption of solar radiation in the earth's atmosphere[J].Atmos.Sci.1974,31:118-133.
Landsberg J.J, Kaufmann M.R., Binkley D., et al. Evaluating progress toward closed forest models based on fluxes of carbon water and land nutrients[J].Tree Physiol.1991,9:1-15.
Li X., Strahler A. A geometric-optical bi-directional reflectance modeling of a Conifer Forest Canopy [J].IEEE Transaction Geoscience Remote Sens,1986,24(6):906-919.
Li X., Strahler A. Geometric-Optical Modeling of a Conifer Forest Canopy[J].IEEE Transaction on Geoscience and Remote Sensing,1985,23(5):705-720.
Markham, B. L. The Landsat sensors' spatial responses[J]. IEEE Transactions on Geoscience and Remote Sensing GE,1985,23(6):864-875.
Markham, B.L. and J.L. Barker, (Eds.). Special LIDQA Issue. Photogrammetric Engineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing.1985
Menghua Wang. An efficient method for multiple radiative transfer computations and lookup table generation Journal of Quantitative Spectroscopy & Radiative Transfer,2003,78:471-480.
Nikolov Ned, Zeller Karl. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments[J].Environmental Pollution,2006,141:539-549
Nilson T., Kuusk A. A reflectance model for the homogeneous plant canopy and its inversion. Remote Sens. Environ [J].1989,27:157-167.
Park, S.K., Schowengerdt R. and Kaczynski M.A. Modulation-transfer-function analysis for sampled imaging systems [J]. Applied Optics.1984,23(15):2572-2582.
PcModWin4.0 Manual[M].Ontar Corporation,2001
Qi J., Kerr Y H, et al. Leaf Area Index estimates using remotely sensed data and BRDF models in a semiarid region [J]. Remote Sensing of Environment,2000,73:18-30.
Reichenbach S.E., Koehler D.E.and Strelow D.W. Restoration and reconstruction of AVHRR images[J]. IEEE Transactions on Geoscience and Remote Sensing 1995.33(4):997-1007.
Robert A. Schowengerdt. Remote Sensing Models and Methods for Image Processing[M].
Running S.W., Newmani R.R. Relating seasonal patterns of the AVHRR Vegetation index to simulated photosynthesis and transpiration of forests on different climates[J]. Remote Sens. Environ,1988,24:347-367.
Storey J.C. Landsat 7 on-orbit modulation transfer function estimation[J]. In Sensors, Systems, and Next-Generation Satellites V, Toulouse, France, SPIE,2001,4540:50-61.
Suits G.H. The calculation of the directional reflectance of vegetation canopy [J]. Remote Sen.Environ.1972,2:117-125
Tanre D., Deroo C., Duhaut P. et al. Description of a computer code to simulate the satellite signal in the solar spectrum:the 5S code[J]. International Journal of Remote Sensing,1990,11:659-668.
Tarantola A. Inverse Problem Theory:Methods for Data Fitting and Model parameter Estimation [M]. Elsevier Science Publishing Company Inc.,New York,1987.
Ushada M., Murase H., Fukuda H. Non-destructive sensing and its inverse model for canopy parameters using texture analysis and artificial neural network[J].Computers and Electronics in Agriculture,2007,57:149-165
Verger A., Baret F.,Weiss M.. Performances of neural networks for deriving LAI estimates from existing CYCLOPES and MODIS products [J]. Remote Sensing of Environment,2008,112 (6): 2789-2803
Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling:the SAIL model. Remote Sensing of Environment[J],1984,16:125-141
Vermote Eric, Tanre D., Deuze J.L. et al. Second simulation of the Satellite Signalin the Solar Spectrum 6S:An overview[J].IEEE Trans Geosci Remote Sens,1997,35:675-686
Yamamoto G. Direct absorption of solar radiation by atmospheric water vapor, carbon dioxide and molecular oxygen[J].Atmos. Sci.1962,13:182-188
Zhang Ping, Anderson Bruce, Tan Bin et al. Potential monitoring of crop production using a satellite-based Climate-Variability Impact Index[J].Agricultural and Forest Meteorology,2005,132:344-358.
陈世平.空间相机设计与试验[M].北京：宇航出版社,2003
段民征,吕达仁.适用于遥感应用的辐射传输高精度快速计算方法[J].遥感学报,2005,(03)：359-366
宫鹏,史培军,浦瑞良等.对地观测技术与地球系统科学[M].北京：科学出版社,1996.
郭兆曾,周凡.卫星遥感图像几何质量的仿真评价[J].中国空间科学技术.1994,06：26-33
何立明,王华,阎广建,李小文,朱文娇,王锦地.气溶胶光学厚度与水平气象视距相互转换的经验公式及其应用[J].遥感学报.2003,7(5)：372-378
何贤强,潘德炉,白雁等.基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型[J].中国科学.D辑：地球科学,2006,(09)：860-870.
焦斌亮,高志强,李素静等.大气辐射传输模型及其软件[J].计算机应用与技术进展,2007,386-390
李栋.卫星遥感成像计算机仿真系统的研究与应用[D].长春：长春理工大学,2006
李克煌.气候资源学[M].河南：河南大学出版社,1990
梁顺林著,范闻捷等译.定量遥感[M].北京：科学出版社,2009
廖国男.大气辐射导论[M].北京：气象出版社,1985
林如强,刘士宽,余涛,胡新礼.一种基于遥感图像仿真的大气查找表优化方法[J].甘肃理工大学学报,2010,36(3)：1-4
刘长盛,刘文保.大气辐射学[M].南京：南京大学出版社,1990
刘晓冰,Stephen HJ作物产量潜力的5P理论及其研究范畴[J].中国农学通报,2001,17(4)：65-66
浦瑞良,宫鹏.高光谱遥感及其应用[M].北京：高等教育出版社,2000
王炳忠.太阳辐射计算讲座第一讲太阳能中天文参数计算[J].太阳能,1999,(02)：8-10
王精业,杨学会.仿真科学与技术的发展及其理论体系[J].计算机仿真.2006,23(1)：1-4
吴北婴.大气辐射传输实用算法[M].北京：气象出版社,1998
武佳丽.基于SAIL+ANN算法的HJ-1卫星CCD数据的LAI反演算法研究[D].北京：中国科学院,2009
肖青,柳钦火,李小文等.高分辨率机载遥感数据的交叉辐射影响及其校正[J].遥感学报,2005,(06)：625-633
徐希孺.遥感物理[M].北京：北京大学出版社,2005.
杨贵军,柳钦火,刘强等.中红外大气辐射传输解析模型及遥感成像模拟[J].光谱学与光谱分析,2009,(03)：629-634
姚延娟,阎广建,王锦地.多光谱多角度遥感数据综合反演叶面积指数方法研究[J].遥感学报,2005,9(2)：117-122.
尹宏.大气辐射学基础[M].北京,气象出版社,1993
张佳华,符淙斌,延晓冬等.全球植被叶面积指数对温度和降水的响应研究[J].地球物理学报,2002,45(5)：631-637
张佳华.自然植被第一性生产力和作物产量估测模型研究[J].上海农业学报,2001,17(3)：83-89
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Allen,W.A.,Gausman,H.W.,Richardson,A.J. Plant canopy irradiance specified by the Duntley equations [J].Opt.Soc.Am.1970,60:372-376.
Amundsen R. M., Feldhaus W. S, Little A D, et al. Integration of design, structural, thermal and optical analysis and user's guide for structural-to-optical translator (PATCOD)[M].NASA TM-110153.1995:22
Bacour C., Baret F., Beal D., et al. Neural network estimation of LAI, fAPAR, fCover and LAI×Cab,from top of canopy MERIS reflectance data:principles and validation[J]. Remote Sensing of Environment,2006,105:313-325.
Banon G.J.F., Fonseca L.M.G. CBERS simulation from SPOT and its restoration[G]//CP 515,12201-970 Sao Jose dos Campos, SP. Brazil:Institute National de Pesquisas Espaciais-INPE.1998
Berk, Anderson G. P., Acharya P. K, et al. MODTRAN4 USER'S MANUAL[R].1999,6.
Chen J. M., Black T A Defining leaf-area index for non-flat leaves[J].Plant Cell.Environ.1992,15,421-429.
Chen J.M., Chen X. Y., Ju W. M. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs[J].Journal of Hydrology,2005,305:15-39
Chen J.M., Cihlar J. Retrieving Leaf Area Index for Boreal Conifer Forests Using Landsat TM Images [J].Remote Sensing of Environment,1996,55:153-162.
Chen J.M., Leblanc S.A.4-Scale Bidirectional Reflection Model Based on Canopy Architecture[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35:1316-1337.
Chen J.M. Evaluation of Vegetation Indices and a Modified Simple Ratio for Boreal Applications [J].IEEE Transactions on Geoscience and Remote Sensing,1996,34:1353-1368.
Dereniak, E.L. and G.D. Boreman. Infrared Detectors and Systems. New York, NY, Wiley-Inter-science,1996,560 p.
Gasser G. Application research toolbox technology overview:NASA earth science applications directorate [M].[S.l.]John C Space Center,2001
Goel N.S. Models of Vegetation Canopy Reflectance and Their Use in Estimation of Biophysical Parameters from Reflectance Data [J]. Remote Sens. Rev.1988,4:1-212
Gregory P., Asner., Jonathan M.O., et al. Global synthesis of leaf area index observation:implications for ecological and remote sensing studies. Global Ecology & Biogeography [J],2003,12:191-205.
Jacquemoud,S. and Baret,F. Andrieu,B.et al. Extraction of vegetation biophysical parameters by inversion of the PROSPECT+SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors [J].Remote Sens.Envir.,1995,52:163-172
Jacquemoud,S. and Baret,F. PROSPECT:A model of leaf optical properties spectra[J].Remote Sens.Envir.,1990,34:75-91
Jacquemoud,S. Inversion of PROSPECT+SAIL canopy reflectance models from aviris equivalent spectra:theoretical study [J].Remote Sens.Envir.,1993,44:281-292.
Kuusk,A. The hotspot effect of a uniform vegetation cover[J].Remote Sens,1985,3:646-658.
Lacia A.A, Hansen J.E, A parameterization for the absorption of solar radiation in the earth's atmosphere[J].Atmos.Sci.1974,31:118-133.
Landsberg J.J, Kaufmann M.R., Binkley D., et al. Evaluating progress toward closed forest models based on fluxes of carbon water and land nutrients[J].Tree Physiol.1991,9:1-15.
Li X., Strahler A. A geometric-optical bi-directional reflectance modeling of a Conifer Forest Canopy [J].IEEE Transaction Geoscience Remote Sens,1986,24(6):906-919.
Li X., Strahler A. Geometric-Optical Modeling of a Conifer Forest Canopy[J].IEEE Transaction on Geoscience and Remote Sensing,1985,23(5):705-720.
Markham, B. L. The Landsat sensors' spatial responses[J]. IEEE Transactions on Geoscience and Remote Sensing GE,1985,23(6):864-875.
Markham, B.L. and J.L. Barker, (Eds.). Special LIDQA Issue. Photogrammetric Engineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing.1985
Menghua Wang. An efficient method for multiple radiative transfer computations and lookup table generation Journal of Quantitative Spectroscopy & Radiative Transfer,2003,78:471-480.
Nikolov Ned, Zeller Karl. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments[J].Environmental Pollution,2006,141:539-549
Nilson T., Kuusk A. A reflectance model for the homogeneous plant canopy and its inversion. Remote Sens. Environ [J].1989,27:157-167.
Park, S.K., Schowengerdt R. and Kaczynski M.A. Modulation-transfer-function analysis for sampled imaging systems [J]. Applied Optics.1984,23(15):2572-2582.
PcModWin4.0 Manual[M].Ontar Corporation,2001
Qi J., Kerr Y H, et al. Leaf Area Index estimates using remotely sensed data and BRDF models in a semiarid region [J]. Remote Sensing of Environment,2000,73:18-30.
Reichenbach S.E., Koehler D.E.and Strelow D.W. Restoration and reconstruction of AVHRR images[J]. IEEE Transactions on Geoscience and Remote Sensing 1995.33(4):997-1007.
Robert A. Schowengerdt. Remote Sensing Models and Methods for Image Processing[M].
Running S.W., Newmani R.R. Relating seasonal patterns of the AVHRR Vegetation index to simulated photosynthesis and transpiration of forests on different climates[J]. Remote Sens. Environ,1988,24:347-367.
Storey J.C. Landsat 7 on-orbit modulation transfer function estimation[J]. In Sensors, Systems, and Next-Generation Satellites V, Toulouse, France, SPIE,2001,4540:50-61.
Suits G.H. The calculation of the directional reflectance of vegetation canopy [J]. Remote Sen.Environ.1972,2:117-125
Tanre D., Deroo C., Duhaut P. et al. Description of a computer code to simulate the satellite signal in the solar spectrum:the 5S code[J]. International Journal of Remote Sensing,1990,11:659-668.
Tarantola A. Inverse Problem Theory:Methods for Data Fitting and Model parameter Estimation [M]. Elsevier Science Publishing Company Inc.,New York,1987.
Ushada M., Murase H., Fukuda H. Non-destructive sensing and its inverse model for canopy parameters using texture analysis and artificial neural network[J].Computers and Electronics in Agriculture,2007,57:149-165
Verger A., Baret F.,Weiss M.. Performances of neural networks for deriving LAI estimates from existing CYCLOPES and MODIS products [J]. Remote Sensing of Environment,2008,112 (6): 2789-2803
Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling:the SAIL model. Remote Sensing of Environment[J],1984,16:125-141
Vermote Eric, Tanre D., Deuze J.L. et al. Second simulation of the Satellite Signalin the Solar Spectrum 6S:An overview[J].IEEE Trans Geosci Remote Sens,1997,35:675-686
Yamamoto G. Direct absorption of solar radiation by atmospheric water vapor, carbon dioxide and molecular oxygen[J].Atmos. Sci.1962,13:182-188
Zhang Ping, Anderson Bruce, Tan Bin et al. Potential monitoring of crop production using a satellite-based Climate-Variability Impact Index[J].Agricultural and Forest Meteorology,2005,132:344-358.
陈世平.空间相机设计与试验[M].北京：宇航出版社,2003
段民征,吕达仁.适用于遥感应用的辐射传输高精度快速计算方法[J].遥感学报,2005,(03)：359-366
宫鹏,史培军,浦瑞良等.对地观测技术与地球系统科学[M].北京：科学出版社,1996.
郭兆曾,周凡.卫星遥感图像几何质量的仿真评价[J].中国空间科学技术.1994,06：26-33
何立明,王华,阎广建,李小文,朱文娇,王锦地.气溶胶光学厚度与水平气象视距相互转换的经验公式及其应用[J].遥感学报.2003,7(5)：372-378
何贤强,潘德炉,白雁等.基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型[J].中国科学.D辑：地球科学,2006,(09)：860-870.
焦斌亮,高志强,李素静等.大气辐射传输模型及其软件[J].计算机应用与技术进展,2007,386-390
李栋.卫星遥感成像计算机仿真系统的研究与应用[D].长春：长春理工大学,2006
李克煌.气候资源学[M].河南：河南大学出版社,1990
梁顺林著,范闻捷等译.定量遥感[M].北京：科学出版社,2009
廖国男.大气辐射导论[M].北京：气象出版社,1985
林如强,刘士宽,余涛,胡新礼.一种基于遥感图像仿真的大气查找表优化方法[J].甘肃理工大学学报,2010,36(3)：1-4
刘长盛,刘文保.大气辐射学[M].南京：南京大学出版社,1990
刘晓冰,Stephen HJ作物产量潜力的5P理论及其研究范畴[J].中国农学通报,2001,17(4)：65-66
浦瑞良,宫鹏.高光谱遥感及其应用[M].北京：高等教育出版社,2000
王炳忠.太阳辐射计算讲座第一讲太阳能中天文参数计算[J].太阳能,1999,(02)：8-10
王精业,杨学会.仿真科学与技术的发展及其理论体系[J].计算机仿真.2006,23(1)：1-4
吴北婴.大气辐射传输实用算法[M].北京：气象出版社,1998
武佳丽.基于SAIL+ANN算法的HJ-1卫星CCD数据的LAI反演算法研究[D].北京：中国科学院,2009
肖青,柳钦火,李小文等.高分辨率机载遥感数据的交叉辐射影响及其校正[J].遥感学报,2005,(06)：625-633
徐希孺.遥感物理[M].北京：北京大学出版社,2005.
杨贵军,柳钦火,刘强等.中红外大气辐射传输解析模型及遥感成像模拟[J].光谱学与光谱分析,2009,(03)：629-634
姚延娟,阎广建,王锦地.多光谱多角度遥感数据综合反演叶面积指数方法研究[J].遥感学报,2005,9(2)：117-122.
尹宏.大气辐射学基础[M].北京,气象出版社,1993
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