陆地生态系统碳监测卫星远红波段叶绿素荧光反演算法设计
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摘要
太阳诱导叶绿素荧光(Solar-Induced Chlorophyll Fluorescence,SIF)是陆表植被在自然光照条件下进行光合作用时释放的一种光信号。SIF携带有重要的光合作用信息,通过卫星遥感的方法探测区域—全球SIF信号为大尺度植被光合作用监测打开了新世界的大门。我国预计于2020年前后发射的陆地生态系统碳卫星(陆碳卫星)将搭载超光谱分辨率载荷,有望成为全球范围内第一个针对陆表植被SIF进行专门观测的卫星传感器。数据驱动算法是陆碳卫星远红波段SIF反演的主算法,作为一种半经验算法,需结合传感器指标进行参数优化。依据陆碳卫星超光谱载荷的设计指标,基于仿真数据进行了端对端反演模拟,讨论了不同潜在反演窗口下SIF反演的精度(精密度与准确度),确定了不同反演窗口所需的主成分个数(n_v),分析了不同反演窗口内反演精度对荧光波形函数(h_F)的敏感性。结果表明:随着反演窗口的拓宽,SIF反演的精密度(鲁棒性)提升,但准确度下降,且对n_v及h_F的敏感性增强。综合考虑各因素,确定了735～758 nm作为陆碳卫星远红波段SIF反演的主窗口,同时n_v取6,h_F设置为单峰高斯函数(μ=740 nm,σ=30 nm)。基于近地表和航空遥感数据的SIF反演结果验证了所设计算法的可行性和合理性。研究结果将为陆碳卫星升空后SIF的反演及产品发布提供重要参考。
Solar-Induced Chlorophyll Fluorescence(SIF),which is emitted by photosystem during photosynthesis under natural illumination,carries important information of actual photosynthesis of plants.Spaceborne remote sensing of SIF provides an unprecedented opportunity for monitoring global photosynthesis at regional to global scales.Up to date,in-orbit operational spaceborne sensors that are available for SIF retrieval are originally designed for atmosphere monitoring.The hyperspectral sensor onboard Chinese Terrestrial Ecosystem Carbon Inventory Satellite(CTECS) is expected to be the first operational spaceborne sensor that is specifically designed for sensing SIF from space(scheduled to be launched around 2020,2 years before the Fluorescence Explorer(FLEX) Mission).Data-driven approach has been selected as the main algorithm for far-red SIF retrieval for CTECS,but is to be refined and assessed according to sensor specifications(e.g.spectral resolution and signal-to-noise ratio).In this context,this study aims to improve the designment of far-red SIF retrieval method for CTECS.based on end-to-end simulation,we evaluate the precision and accuracy of SIF retrieval in several potential windows.We then analyze the sensitivity of SIF retrieval to number of features(n_v) and fluorescence spectral shape function(h_F) in the forward model in different windows.Results show that a broader fitting window increases retrieval precision,but is accompanied with lower accuracy and stronger sensitivity to n_v and h_F.Considering both retrieval precision and accuracy,the window of 735～758 nm with n_v set to 6 and h_F set as single peak Gaussian function(μ=740 nm and σ=30 nm) is selected as optimal fitting window for CTECS.SIF retrieval results based on proximal and airborne remote sensing data demonstrate the feasibility and reasonability of the designed method.Our results provide an important reference for far-red SIF retrieval for CTECS.
Solar-Induced Chlorophyll Fluorescence(SIF),which is emitted by photosystem during photosynthesis under natural illumination,carries important information of actual photosynthesis of plants.Spaceborne remote sensing of SIF provides an unprecedented opportunity for monitoring global photosynthesis at regional to global scales.Up to date,in-orbit operational spaceborne sensors that are available for SIF retrieval are originally designed for atmosphere monitoring.The hyperspectral sensor onboard Chinese Terrestrial Ecosystem Carbon Inventory Satellite(CTECS) is expected to be the first operational spaceborne sensor that is specifically designed for sensing SIF from space(scheduled to be launched around 2020,2 years before the Fluorescence Explorer(FLEX) Mission).Data-driven approach has been selected as the main algorithm for far-red SIF retrieval for CTECS,but is to be refined and assessed according to sensor specifications(e.g.spectral resolution and signal-to-noise ratio).In this context,this study aims to improve the designment of far-red SIF retrieval method for CTECS.based on end-to-end simulation,we evaluate the precision and accuracy of SIF retrieval in several potential windows.We then analyze the sensitivity of SIF retrieval to number of features(n_v) and fluorescence spectral shape function(h_F) in the forward model in different windows.Results show that a broader fitting window increases retrieval precision,but is accompanied with lower accuracy and stronger sensitivity to n_v and h_F.Considering both retrieval precision and accuracy,the window of 735～758 nm with n_v set to 6 and h_F set as single peak Gaussian function(μ=740 nm and σ=30 nm) is selected as optimal fitting window for CTECS.SIF retrieval results based on proximal and airborne remote sensing data demonstrate the feasibility and reasonability of the designed method.Our results provide an important reference for far-red SIF retrieval for CTECS.
引文
[1] Christian B,Markus R,Enrico T,et al.Terrestrial Gross Carbon Dioxide Uptake:Global Distribution and Covariation with Climate[J].Science,2010,329(5993):834-838.
[2] Guan K,Berry J A,Zhang Y,et al.Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence[J].Global Change Biology,2016,22(2):716-726.
[3] Zhang L F,Jiao W Z,Zhang H M,et al.Studying Drought Phenomena in the Continental United States in 2011 and 2012 Using Various Drought Indices[J].Remote Sensing of Environment,2017,190:96-106.
[4] Porcar-Castell A,Tyystjarvi E,Atherton J,et al.Linking Chlorophyll a Fluorescence to Photosynthesis for Remote Sensing Applications:Mechanisms and Challenges[J].Journal of Experimental Botany,2014,65(15):4065-4095.
[5] Zhang Y,Xiao X M,Zhang Y G,et al.On the Relationship Between Sub-Daily Instantaneous and Daily Total Gross Primary Production:Implications for Interpreting Satellite-based SIF Retrievals[J].Remote Sensing of Environment,2018,205:276-289.
[6] Zhang Y G,Guanter L,Joiner J,et al.Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-based Chlorophyll Fluorescence Data[J].Remote Sensing of Environment,2018,210:362-374.
[7] Walther S,Voigt M,Thum T,et al.Satellite Chlorophyll Fluorescence Measurements Reveal Large-Scale Decoupling of Photosynthesis and Greenness Dynamics in Boreal Evergreen Forests[J].Global Change Biology,2016,22(9):2979-2996.
[8] Joiner J,Yoshida Y,Vasilkov A P,et al.The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and Its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange[J].Remote Sensing of Environment,2014,152:375-391.
[9] Guanter L,Zhang Y G,Jung M,et al.Global and Time-resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence[J].Proceedings of the National Academy of Sciences of the United States of America,2014,111(14):1327-1333.
[10] K?hler P,Guanter L,Kobayashi H,et al.Assessing the Potential of Sun-Induced Fluorescence and the Canopy Scattering Coefficient to Track Large-Scale Vegetation Dynamics in Amazon Forests[J].Remote Sensing of Environment,2018,204:769-785.
[11] Sun Y,Frankenberg C,Wood J D,et al.OCO-2 Advances Photosynthesis Observation from Space via Solar-Induced Chlorophyll Fluorescence[J].Science,2017,358(6360):5747.
[12] Joiner J,Yoshida Y,Vasilkov A P,et al.First Observations of Global and Seasonal Terrestrial Chlorophyll Fluorescence from Space[J].Biogeosciences,2011,8(3):637-651.
[13] Frankenberg C,Fisher J B,Worden J,et al.New Global Observations of the Terrestrial Carbon Cycle from GOSAT:Patterns of Plant Fluorescence with Gross Primary Productivity[J].Geophysical Research Letters,2011,38(17).doi:10.1029/2011GL048738.
[14] Guanter Luis,Frankenberg Christian,Dudhia Anu,et al.Retrieval and Global Assessment of Terrestrial Chlorophyll Fluorescence from GOSAT Space Measurements[J].Remote Sensing of Environment,2012,121:236-251.
[15] Joiner J,Yoshida Y,Guanter Luis,et al.New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyper-Spectral Satellite Instruments:Simulations and Application to GOME-2 and SCIAMACHY[J].Atmospheric Measurement Techniques Discussions,2016:1-41.
[16] Sanders A,Verstraeten W,Kooreman M,et al.Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements[J].Remote Sensing,2016,8(12):895.doi:103390/rs8110895.
[17] K?hler P,Guanter L,Joiner J.A Linear Method for the Retrieval of Sun-Induced Chlorophyll Fluorescence from GOME-2 and SCIAMACHY Data[J].Atmospheric Measurement Techniques,2015,8(6):2589-2608.
[18] Guanter L,Aben I,Tol P,et al.Potential of the Tropospheric Monitoring Instrument (TROPOMI) Onboard the Sentinel-5 Precursor for the Monitoring of Terrestrial Chlorophyll Fluorescence[J].Atmospheric Measurement Techniques,2015,8(3):1337-1352.
[19] Joiner J,Guanter L,Lindstrot R,et al.Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements:Methodology,Simulations,And Application to GOME-2[J].Atmospheric Measurement Techniques,2013,6(10):2803-2823.
[20] Frankenberg C,O’dell C,Berry J,et al.Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2[J].Remote Sensing of Environment,2014,147:1-12.
[21] Sun Y,Frankenberg C,Jung M,et al.Overview of Solar-Induced Chlorophyll Fluorescence (SIF) from the Orbiting Carbon Observatory-2:Retrieval,Cross-Mission Comparison,And Global Monitoring for GPP[J].Remote Sensing of Environment,2018,209:808-823.
[22] K?ehler P,Frankenberg C,Magney T S,et al.Global Retrievals of Solar Induced Chlorophyll Fluorescence with TROPOMI:First Results and Inter-Sensor Comparison to OCO-2[J].Geophysical Research Letters,2018,45(19):10456-10463.
[23] Du S S,Liu L Y,Liu X J,et al.Retrieval of Global Terrestrial Solar-Induced Chlorophyll Fluorescence from Tansat Satellite[J].Science Bulletin,2018,63(22):1502-1512.
[24] Meroni M,Rossini M,Guanter L,et al.Remote Sensing of Solar-Induced Chlorophyll Fluorescence:Review of Methods and Applications[J].Remote Sensing of Environment,2009,113(10):2037-2051.
[25] Zhang Lifu,Wang Siheng,Huang Changping.Top-of-Atmosphere Hyperspectral Remote Sensing of Solar-Induced Chlorophyll Fluorescence:A Review of Methods.Journal of Remote Sensing,2018,22(1):1-12.[张立福,王思恒,黄长平.太阳诱导叶绿素荧光的卫星遥感反演方法[J].遥感学报,2018,22(1):1-12.]
[26] Coppo P,Taiti A,Pettinato L,et al.Fluorescence Imaging Spectrometer (FLORIS) for ESA FLEX Mission[J].Remote Sensing,2017,9(7):649.doi:10.3390/rs9070649.
[27] Guanter L,Rossini M,Colombo R,et al.Using Field Spectroscopy to Assess the Potential of Statistical Approaches for the Retrieval of Sun-Induced Chlorophyll Fluorescence from Ground and Space[J].Remote Sensing of Environment,2013,133:52-61.
[28] Berk A,Anderson G P,Acharya P K,et al.MODTRAN 5:A Reformulated Atmospheric Band Model with Auxiliary Species and Practical Multiple Scattering Options:Update;Proceedings of the Algorithms and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery XI,F,2005[C]//International Society for Optics and Photonics,2005.
[29] Van der Tol C,Verhoef W,Timmermans J,et al.An Integrated Model of Soil-Canopy Spectral Radiances,Photosynthesis,Fluorescence,Temperature and Energy Balance[J].Biogeosciences,2009,6(12):3109-3129.
[30] Zhang L F,Wang S H,Huang C P,et al.Retrieval of Sun-Induced Chlorophyll Fluorescence Using Statistical Method Without Synchronous Irradiance Data[J].IEEE Geoscience and Remote Sensing Letters,2017,14(3):384-388.
[31] Liu X J,Liu L Y.Influence of the Canopy BRDF Characteristics and Illumination Conditions on the Retrieval of Solar-Induced Chlorophyll Fluorescence[J].International Journal of Remote Sensing,2018,39(6):1782-1799.
[32] Liu X,Liu L,Zhang S,et al.New Spectral Fitting Method for Full-Spectrum Solar-Induced Chlorophyll Fluorescence Retrieval based on Principal Components Analysis[J].Remote Sensing,2015,7(8):10626-45.
[33] Zhang Y,Joiner J,Alemohammad S H,et al.A Global Spatially Continuous Solar Induced Fluorescence (CSIF) Dataset Using Neural Networks[J].Biogeosciences Discussions,2018:1-34.
[34] Gentine P,Alemohammad S H.Reconstructed Solar-Induced Fluorescence:A Machine Learning Vegetation Product based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence[J].Geophysical Research Letters,2018,45(7):3136-3146.
[2] Guan K,Berry J A,Zhang Y,et al.Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence[J].Global Change Biology,2016,22(2):716-726.
[3] Zhang L F,Jiao W Z,Zhang H M,et al.Studying Drought Phenomena in the Continental United States in 2011 and 2012 Using Various Drought Indices[J].Remote Sensing of Environment,2017,190:96-106.
[4] Porcar-Castell A,Tyystjarvi E,Atherton J,et al.Linking Chlorophyll a Fluorescence to Photosynthesis for Remote Sensing Applications:Mechanisms and Challenges[J].Journal of Experimental Botany,2014,65(15):4065-4095.
[5] Zhang Y,Xiao X M,Zhang Y G,et al.On the Relationship Between Sub-Daily Instantaneous and Daily Total Gross Primary Production:Implications for Interpreting Satellite-based SIF Retrievals[J].Remote Sensing of Environment,2018,205:276-289.
[6] Zhang Y G,Guanter L,Joiner J,et al.Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-based Chlorophyll Fluorescence Data[J].Remote Sensing of Environment,2018,210:362-374.
[7] Walther S,Voigt M,Thum T,et al.Satellite Chlorophyll Fluorescence Measurements Reveal Large-Scale Decoupling of Photosynthesis and Greenness Dynamics in Boreal Evergreen Forests[J].Global Change Biology,2016,22(9):2979-2996.
[8] Joiner J,Yoshida Y,Vasilkov A P,et al.The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and Its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange[J].Remote Sensing of Environment,2014,152:375-391.
[9] Guanter L,Zhang Y G,Jung M,et al.Global and Time-resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence[J].Proceedings of the National Academy of Sciences of the United States of America,2014,111(14):1327-1333.
[10] K?hler P,Guanter L,Kobayashi H,et al.Assessing the Potential of Sun-Induced Fluorescence and the Canopy Scattering Coefficient to Track Large-Scale Vegetation Dynamics in Amazon Forests[J].Remote Sensing of Environment,2018,204:769-785.
[11] Sun Y,Frankenberg C,Wood J D,et al.OCO-2 Advances Photosynthesis Observation from Space via Solar-Induced Chlorophyll Fluorescence[J].Science,2017,358(6360):5747.
[12] Joiner J,Yoshida Y,Vasilkov A P,et al.First Observations of Global and Seasonal Terrestrial Chlorophyll Fluorescence from Space[J].Biogeosciences,2011,8(3):637-651.
[13] Frankenberg C,Fisher J B,Worden J,et al.New Global Observations of the Terrestrial Carbon Cycle from GOSAT:Patterns of Plant Fluorescence with Gross Primary Productivity[J].Geophysical Research Letters,2011,38(17).doi:10.1029/2011GL048738.
[14] Guanter Luis,Frankenberg Christian,Dudhia Anu,et al.Retrieval and Global Assessment of Terrestrial Chlorophyll Fluorescence from GOSAT Space Measurements[J].Remote Sensing of Environment,2012,121:236-251.
[15] Joiner J,Yoshida Y,Guanter Luis,et al.New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyper-Spectral Satellite Instruments:Simulations and Application to GOME-2 and SCIAMACHY[J].Atmospheric Measurement Techniques Discussions,2016:1-41.
[16] Sanders A,Verstraeten W,Kooreman M,et al.Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements[J].Remote Sensing,2016,8(12):895.doi:103390/rs8110895.
[17] K?hler P,Guanter L,Joiner J.A Linear Method for the Retrieval of Sun-Induced Chlorophyll Fluorescence from GOME-2 and SCIAMACHY Data[J].Atmospheric Measurement Techniques,2015,8(6):2589-2608.
[18] Guanter L,Aben I,Tol P,et al.Potential of the Tropospheric Monitoring Instrument (TROPOMI) Onboard the Sentinel-5 Precursor for the Monitoring of Terrestrial Chlorophyll Fluorescence[J].Atmospheric Measurement Techniques,2015,8(3):1337-1352.
[19] Joiner J,Guanter L,Lindstrot R,et al.Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements:Methodology,Simulations,And Application to GOME-2[J].Atmospheric Measurement Techniques,2013,6(10):2803-2823.
[20] Frankenberg C,O’dell C,Berry J,et al.Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2[J].Remote Sensing of Environment,2014,147:1-12.
[21] Sun Y,Frankenberg C,Jung M,et al.Overview of Solar-Induced Chlorophyll Fluorescence (SIF) from the Orbiting Carbon Observatory-2:Retrieval,Cross-Mission Comparison,And Global Monitoring for GPP[J].Remote Sensing of Environment,2018,209:808-823.
[22] K?ehler P,Frankenberg C,Magney T S,et al.Global Retrievals of Solar Induced Chlorophyll Fluorescence with TROPOMI:First Results and Inter-Sensor Comparison to OCO-2[J].Geophysical Research Letters,2018,45(19):10456-10463.
[23] Du S S,Liu L Y,Liu X J,et al.Retrieval of Global Terrestrial Solar-Induced Chlorophyll Fluorescence from Tansat Satellite[J].Science Bulletin,2018,63(22):1502-1512.
[24] Meroni M,Rossini M,Guanter L,et al.Remote Sensing of Solar-Induced Chlorophyll Fluorescence:Review of Methods and Applications[J].Remote Sensing of Environment,2009,113(10):2037-2051.
[25] Zhang Lifu,Wang Siheng,Huang Changping.Top-of-Atmosphere Hyperspectral Remote Sensing of Solar-Induced Chlorophyll Fluorescence:A Review of Methods.Journal of Remote Sensing,2018,22(1):1-12.[张立福,王思恒,黄长平.太阳诱导叶绿素荧光的卫星遥感反演方法[J].遥感学报,2018,22(1):1-12.]
[26] Coppo P,Taiti A,Pettinato L,et al.Fluorescence Imaging Spectrometer (FLORIS) for ESA FLEX Mission[J].Remote Sensing,2017,9(7):649.doi:10.3390/rs9070649.
[27] Guanter L,Rossini M,Colombo R,et al.Using Field Spectroscopy to Assess the Potential of Statistical Approaches for the Retrieval of Sun-Induced Chlorophyll Fluorescence from Ground and Space[J].Remote Sensing of Environment,2013,133:52-61.
[28] Berk A,Anderson G P,Acharya P K,et al.MODTRAN 5:A Reformulated Atmospheric Band Model with Auxiliary Species and Practical Multiple Scattering Options:Update;Proceedings of the Algorithms and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery XI,F,2005[C]//International Society for Optics and Photonics,2005.
[29] Van der Tol C,Verhoef W,Timmermans J,et al.An Integrated Model of Soil-Canopy Spectral Radiances,Photosynthesis,Fluorescence,Temperature and Energy Balance[J].Biogeosciences,2009,6(12):3109-3129.
[30] Zhang L F,Wang S H,Huang C P,et al.Retrieval of Sun-Induced Chlorophyll Fluorescence Using Statistical Method Without Synchronous Irradiance Data[J].IEEE Geoscience and Remote Sensing Letters,2017,14(3):384-388.
[31] Liu X J,Liu L Y.Influence of the Canopy BRDF Characteristics and Illumination Conditions on the Retrieval of Solar-Induced Chlorophyll Fluorescence[J].International Journal of Remote Sensing,2018,39(6):1782-1799.
[32] Liu X,Liu L,Zhang S,et al.New Spectral Fitting Method for Full-Spectrum Solar-Induced Chlorophyll Fluorescence Retrieval based on Principal Components Analysis[J].Remote Sensing,2015,7(8):10626-45.
[33] Zhang Y,Joiner J,Alemohammad S H,et al.A Global Spatially Continuous Solar Induced Fluorescence (CSIF) Dataset Using Neural Networks[J].Biogeosciences Discussions,2018:1-34.
[34] Gentine P,Alemohammad S H.Reconstructed Solar-Induced Fluorescence:A Machine Learning Vegetation Product based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence[J].Geophysical Research Letters,2018,45(7):3136-3146.