非线性最优化的MODIS气溶胶多参数反演研究
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摘要
为了弥补地基观测气溶胶光学厚度(Aerosol Optical Depth,AOD)范围受限等缺点,通过卫星影像反演AOD的方法逐渐兴起,而简化气溶胶反演算法(Simplified Aerosol Retrieval Algorithm,SARA)与传统反演方法相比更具普适性。为进一步提升精度,提出了一种非线性最优化的中分辨率成像光谱仪(Moderate-resolution Imaging Spectroradiometer,MODIS)气溶胶多参数反演方法。该方法以SARA反演的AOD为初始值,对AOD、单次散射反照率(Single Scattering Albedo,SSA)(ω)、不对称性因子(Asymmetric Factor,ASY)(g)、地表反射率拟合参数(ρ′s=k*ρs+b)同时优化,以期得到最优解。结果表明,同等条件下,非线性最优化方法明显优于SARA。单点精度验证结果与全球气溶胶自动观测网(Aerosol Robotic Network,AERONET)相比,非线性最优化方法的相关系数为0.8118,优于SARA的0.2624。与官方气溶胶产品(MOD04)相比,7月6日非线性最优化方法的相关系数为0.7612,优于SARA的0.5916;5月3日非线性最优化方法的相关系数为0.9036,优于SARA的0.8788。
To overcome the shortcoming of traditional ground-based methods of which the observation is limited,the method of inverting aerosol optical depth(AOD)by remote sensing image is gradually emerging.Compared with the traditional inversion methods,the Simplified Aerosol Retrieval Algorithm(SARA)is more universal.To further improve the accuracy,a nonlinear optimization method which uses multi-parameters to invert aerosol from Moderate-resolution Imaging Spectroradiometer(MODIS)is proposed.By treating the aerosol optical depth inverted by SARA as the initial value,the method optimizes the optical thickness,single scattering albedo(ω),asymmetry factor(g)and surface reflectance fitting parameter(ρ′s=k*ρs+b)simultaneously,so as to obtain the optimal solution.The results show that under the same conditions,the nonlinear optimization method is obviously superior to the SARA.The correlation coefficient of the nonlinear optimization method for single point precision verification is 0.8118,which is better than the 0.2624 of SARA.Compared with the inversion values from MODIS aerosol product(MOD04),for the case of July 6,the correlation coefficient of the nonlinear optimization method is 0.7612,which is better than 0.5916 of SARA.For the case of May 3,the correlation coefficient of nonlinear optimization method is 0.9036,which is better than 0.8788 of SARA.
To overcome the shortcoming of traditional ground-based methods of which the observation is limited,the method of inverting aerosol optical depth(AOD)by remote sensing image is gradually emerging.Compared with the traditional inversion methods,the Simplified Aerosol Retrieval Algorithm(SARA)is more universal.To further improve the accuracy,a nonlinear optimization method which uses multi-parameters to invert aerosol from Moderate-resolution Imaging Spectroradiometer(MODIS)is proposed.By treating the aerosol optical depth inverted by SARA as the initial value,the method optimizes the optical thickness,single scattering albedo(ω),asymmetry factor(g)and surface reflectance fitting parameter(ρ′s=k*ρs+b)simultaneously,so as to obtain the optimal solution.The results show that under the same conditions,the nonlinear optimization method is obviously superior to the SARA.The correlation coefficient of the nonlinear optimization method for single point precision verification is 0.8118,which is better than the 0.2624 of SARA.Compared with the inversion values from MODIS aerosol product(MOD04),for the case of July 6,the correlation coefficient of the nonlinear optimization method is 0.7612,which is better than 0.5916 of SARA.For the case of May 3,the correlation coefficient of nonlinear optimization method is 0.9036,which is better than 0.8788 of SARA.
引文
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[13]唐家奎,薛勇,虞统,等.MODIS陆地气溶胶遥感反演-利用TERRA和AQUA双星MODIS数据协同反演算法[J].中国科学(D辑:地球科学),2005,35(05):474--481.
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[15]毛节泰,李成才,张军华,等.MODIS卫星遥感北京地区气溶胶光学厚度及与地面光度计遥感的对比[J].应用气象学报,2002,13(S1):127--135.
[16]杨东旭,韦晶,钟永德.利用MODIS卫星资料反演北京地区气溶胶光学厚度[J].光谱学与光谱分析,2018,38(11):3464--3469.
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[18]Ichoku C,Kaufman Y J,Remer L A,et al.Global Aerosol Remote Sensing from MODIS[J].Advances in Space Research,2004,34(4):820--827.
[19]夏祥鳌.全球陆地上空MODIS气溶胶光学厚度显著偏高[J].科学通报,2006,51(19):2297--2303.
[20]戴燃坡,谢勇,马青玉.基于两天MODIS数据的气溶胶光学厚度反演[J].南京师大学报(自然科学版),2016,39(1):139--144.
[21]李晓静,刘玉洁,邱红,等.利用MODIS资料反演北京及其周边地区气溶胶光学厚度的方法研究[J].气象学报,2003,61(5):580--591.
[22]范娇,郭宝峰,何宏昌.基于MODIS数据的杭州地区气溶胶光学厚度反演[J].光学学报,2015,35(1):9--17.
[23]Bilal M,Nichol J E,Bleiweiss M P,et al.ASimplified high resolution MODIS Aerosol Retrieval Algorithm(SARA)for Use over Mixed Surfaces[J].Remote Sensing of Environment,2013,136:135--145.
[24]Bilal M,Nichol J E,Chan P W.Validation and Accuracy Assessment of a Simplified Aerosol Retrieval Algorithm(SARA)over Beijing under Llow and High Aerosol Loadings and Dust Storms[J].Remote Sensing of Environment,2014,153:50--60.
[25]Bilal M,Nichol J E.Evaluation of MODIS Aerosol Retrieval Algorithms over the Beijing-TianjinHebei Region during Low to very High Pollution E-vents[J].Journal of Geophysical Research:Atmospheres,2015,120(15):7941--7957.
[26]王晶杰,李琦.基于SARA算法的京津冀地区气溶胶遥感反演[J].地球科学,2015,5(3):47--54.
[27]Li Z,Zhao X,Kahn R,et al.Uncertainties in Satellite Remote Sensing of Aerosols and Impact on Monitoring its Long-term Trend:a Review and Perspective[J].Annales Geophysicae,2009,27(7):2755--2770.
[28]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.
[29]许万智.北京地区气溶胶光学特性与辐射效应的观测研究[D].中国气象科学研究院,2012.
[2]汤玉明,邓孺孺,刘永明,等.大气气溶胶遥感反演研究综述[J].遥感技术与应用,2018,33(1):25--34.
[3]李加恒,刘厚凤,赵丹婷.基于MODIS的气溶胶光学厚度反演算法及应用进展[J].绿色科技,2012(2):108--111.
[4]余卫国,房世波,余学祥.中国卫星遥感气溶胶研究进展[J].能源环境保护,2016,30(1):1--6.
[5]王磊,张鹏,孙凌,等.多角度气溶胶遥感研究进展[J].遥感信息,2012(1):110--115.
[6]宋薇,张镭.大气气溶胶光学厚度遥感研究概况[J].干旱气象,2007,25(3):76--81.
[7]Kaufman Y J,TanréD,Remer L A,et al.Operational Remote Sensing of Tropospheric Aerosol over Land from EOS Moderate Resolution Imaging Spectroradiometer[J].Journal of Geophysical Research:Atmospheres,1997,102(D14):17051--17067.
[8]Hsu N C,Tsay S,King M D,et al.Aerosol Properties over Bright-reflecting Source Regions[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(3):557--569.
[9]Leeuw G D,Holzer-Popp T,Bevan S,et al.E-valuation of Seven European Aerosol Optical Depth Retrieval Algorithms for Climate Analysis[J].Remote Sensing of Environment,2015,162:295--315.
[10]Tanre D,Deschamps P Y,Devaux C,et al.Estimation of Saharan Aerosol Optical Thickness from Blurring Effects in Thematic Mapper Data[J].Journal of Geophysical Research,1988,93(D12):15955.
[11]DeuzéJ L,Bréon F M,Devaux C,et al.Remote Sensing of Aerosols over Land Surfaces from POL-DER-ADEOS-1Polarized Measurements[J].Journal of Geophysical Research:Atmospheres,2001,106(D5):4913--4926.
[12]Hsu N C,Jeong M J,Bettenhausen C,et al.Enhanced Deep Blue Aerosol Retrieval Algorithm:The Second Generation[J].Journal of Geophysical Research:Atmospheres,2013,118(16):9296--9315.
[13]唐家奎,薛勇,虞统,等.MODIS陆地气溶胶遥感反演-利用TERRA和AQUA双星MODIS数据协同反演算法[J].中国科学(D辑:地球科学),2005,35(05):474--481.
[14]Chu D A,Kaufman Y J,Ichoku C,et al.Validation of MODIS Aerosol Optical Depth Retrieval over Land[J].Geophysical Research Letters,2002,29(12):1--4.
[15]毛节泰,李成才,张军华,等.MODIS卫星遥感北京地区气溶胶光学厚度及与地面光度计遥感的对比[J].应用气象学报,2002,13(S1):127--135.
[16]杨东旭,韦晶,钟永德.利用MODIS卫星资料反演北京地区气溶胶光学厚度[J].光谱学与光谱分析,2018,38(11):3464--3469.
[17]刘佳雨,杨武年.基于MODIS数据的气溶胶光学厚度反演[J].地理信息世界,2014,21(3):20--32.
[18]Ichoku C,Kaufman Y J,Remer L A,et al.Global Aerosol Remote Sensing from MODIS[J].Advances in Space Research,2004,34(4):820--827.
[19]夏祥鳌.全球陆地上空MODIS气溶胶光学厚度显著偏高[J].科学通报,2006,51(19):2297--2303.
[20]戴燃坡,谢勇,马青玉.基于两天MODIS数据的气溶胶光学厚度反演[J].南京师大学报(自然科学版),2016,39(1):139--144.
[21]李晓静,刘玉洁,邱红,等.利用MODIS资料反演北京及其周边地区气溶胶光学厚度的方法研究[J].气象学报,2003,61(5):580--591.
[22]范娇,郭宝峰,何宏昌.基于MODIS数据的杭州地区气溶胶光学厚度反演[J].光学学报,2015,35(1):9--17.
[23]Bilal M,Nichol J E,Bleiweiss M P,et al.ASimplified high resolution MODIS Aerosol Retrieval Algorithm(SARA)for Use over Mixed Surfaces[J].Remote Sensing of Environment,2013,136:135--145.
[24]Bilal M,Nichol J E,Chan P W.Validation and Accuracy Assessment of a Simplified Aerosol Retrieval Algorithm(SARA)over Beijing under Llow and High Aerosol Loadings and Dust Storms[J].Remote Sensing of Environment,2014,153:50--60.
[25]Bilal M,Nichol J E.Evaluation of MODIS Aerosol Retrieval Algorithms over the Beijing-TianjinHebei Region during Low to very High Pollution E-vents[J].Journal of Geophysical Research:Atmospheres,2015,120(15):7941--7957.
[26]王晶杰,李琦.基于SARA算法的京津冀地区气溶胶遥感反演[J].地球科学,2015,5(3):47--54.
[27]Li Z,Zhao X,Kahn R,et al.Uncertainties in Satellite Remote Sensing of Aerosols and Impact on Monitoring its Long-term Trend:a Review and Perspective[J].Annales Geophysicae,2009,27(7):2755--2770.
[28]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.
[29]许万智.北京地区气溶胶光学特性与辐射效应的观测研究[D].中国气象科学研究院,2012.