基于参数不确定性分析的SAR土壤水分反演精度控制方法
|
摘要
参数不确定性是SAR反演土壤水分的重要不确定性来源,为控制土壤水分反演精度,提出一种基于参数不确定性的有效控制土壤水分反演精度的方法,使用该方法可以控制参数的误差范围。首先使用全局敏感性分析方法,确定后向影响散射系数输出的主要参数;在不同量级高斯噪声随机扰动下,将大量各参数采值输入AIEM模型中,得到带噪声的后向散射系数集合;再使用LUT法反演土壤水分,计算反演结果满足误差量级控制范围。以此为基础,利用ENVISAT ASAR双极化数据(VV、VH)和实测土壤水分数据进行验证,利用LUT法反演得到带噪声的土壤水分,计算ASAR影像中采样点土壤水分反演值RMSE<0.04cm3/cm3。结果表明各影响参数误差量级控制范围可有效控制土壤水分反演精度,在较大的入射角范围内都适用。
There is a lot of uncertainty about using SAR to retrieve soil moisture in bare soil,in which parameter uncertainty is an important part.In order to control the accuracy of soil moisture retrieval,a method based on parameter uncertainty for controlling soil moisture retrieval accuracy is proposed.The error control range of parameters can be obtained by using this method.Firstly,the global sensitivity analysis method is used to analyze the AIEM(Advanced Integral Equation Model)model,and the main influence parameters of the backscattering coefficient are obtained.Then,a large number of parameter sampling values are obtained by adding random noise of different orders of magnitude to Gauss in the main influence parameters,and these sampled values are input into the AIEM model to obtain a set of backscatter coefficients with noise.LUT(look-up tables)method is used to retrieve the soil moisture,and the RMSE of the inversion result is calculated.The error control range of influence parameter which satisfies certain inversion precision is obtained.Finally,the error control range is extended to adapt to different incidence angles.The results are validated by using Envisat ASAR(advanced synthetic aperture radar)C-band dual polarization(VV,HH)data and the observed values of ground truth measurements synchronizing with Envisat ASAR.The parameter error control range is used as the sensitive parameter to add the disturbance noise,and LUT method is used to retrieve the soil moisture with noise.The RMSE of inversion result in the sampling area is calculated.The results(RMSE<0.04 cm3/cm3)show that error control range of influence parameter proposed by this paper can effectively control the inversion accuracy of soil moisture,and can be applied to a larger range of incidence angles.
There is a lot of uncertainty about using SAR to retrieve soil moisture in bare soil,in which parameter uncertainty is an important part.In order to control the accuracy of soil moisture retrieval,a method based on parameter uncertainty for controlling soil moisture retrieval accuracy is proposed.The error control range of parameters can be obtained by using this method.Firstly,the global sensitivity analysis method is used to analyze the AIEM(Advanced Integral Equation Model)model,and the main influence parameters of the backscattering coefficient are obtained.Then,a large number of parameter sampling values are obtained by adding random noise of different orders of magnitude to Gauss in the main influence parameters,and these sampled values are input into the AIEM model to obtain a set of backscatter coefficients with noise.LUT(look-up tables)method is used to retrieve the soil moisture,and the RMSE of the inversion result is calculated.The error control range of influence parameter which satisfies certain inversion precision is obtained.Finally,the error control range is extended to adapt to different incidence angles.The results are validated by using Envisat ASAR(advanced synthetic aperture radar)C-band dual polarization(VV,HH)data and the observed values of ground truth measurements synchronizing with Envisat ASAR.The parameter error control range is used as the sensitive parameter to add the disturbance noise,and LUT method is used to retrieve the soil moisture with noise.The RMSE of inversion result in the sampling area is calculated.The results(RMSE<0.04 cm3/cm3)show that error control range of influence parameter proposed by this paper can effectively control the inversion accuracy of soil moisture,and can be applied to a larger range of incidence angles.
引文
[1]李大治,晋锐,车涛,等.联合机载PLMR微波辐射计和MODIS产品反演黑河中游张掖绿洲土壤水分研究[J].地球科学进展,2014,29(2):295-305.
[2]ENGMAN E T,CHAUHAN N.Status of microwave soil moisture measurements with remote sensing[J].Remote Sensing of Environment,1995,51(1):189-198.
[3]KEYSER E D,VERNIEUWE H,LIEVENS H,et al.Assessment of SAR-retrieved soil moisture uncertainty induced by uncertainty on modeled soil surface roughness[J].International Journal of Applied Earth Observations&Geoinformation,2012,18(1):176-182.
[4]FERNNDEZ-GLVEZ J.Errors in soil moisture content estimates induced by uncertainties in the effective soil dielectric constant[J].International Journal of Remote Sensing,2008,29(11):3317-3323.
[5]MA C,LI X,NOTARNICOLA C,et al.Uncertainty Quantification of Soil Moisture Estimations Based on a Bayesian Probabilistic Inversion[J].IEEE Transactions on Geoscience&Remote Sensing,PP(99):1-14.
[6]李大治.L波段土壤水分反演的不确定性分析及其反演策略研究——以HiWATER PLMR数据为例[D].北京:中国科学院寒区旱区环境与工程研究所,2014.
[7]VERHOEST N E C,LIEVENS H,WAGNER W,et al.On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar[J].Sensors,2008,8(7):4213.
[8]RAHMAN M M,MORAN M S,THOMA D P,et al.A derivation of roughness correlation length for parameterizing radar backscatter models[J].International Journal of Remote Sensing,2007,28(18):3995-4012.
[9]DAVIDSON M,TOAN T L,MATTIA F,et al.On the characterization of agricultural soil roughness for radar remote sensing studies[J].IEEE Transactions on Geoscience&Remote Sensing,2000,38(2):630-640.
[10]郭立新,王蕊,吴振森.随机粗糙面散射的基本理论与方法[M].北京:科学出版社,2010.32-39.
[11]SHI J,CHEN K S,LI Q,et al.A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer[J].IEEE Transactions on Geoscience&Remote Sensing,2010,40(12):2674-2686.
[12]余凡,李海涛,张承明,等.利用双极化微波遥感数据反演土壤水分的新方法[J].武汉大学学报(信息科学版),2014,39(2):225-228.
[13]陈晶,贾毅,余凡.双极化雷达反演裸露地表土壤水分[J].农业工程学报,2013,29(10):109-116.
[14]LIEVENS H,VERHOSET N E C,KEYSER E D,et al.Effective roughness modelling as a tool for soil moisture retrieval from C-and L-band SAR[J].Hydrology&Earth System Sciences Discussions,2010,7(4):151-162.
[15]SALTELLI A,TARANTOLA S,CHAN K P S,et al.A quantitative model-independent method for global sensitivity analysis of model output[J].Technometrics,1999,41(1):39-56.
[16]CUKIER R,FORTUIN C,SHULER K,et al.Study of the sensitivity of the coupled reaction systems to uncertainties in rate coefficients:I.Theory[J].The Journal of Chemical Physics,1973,59:3873
[17]郝崇清,王江,邓斌,等.基于稀疏贝叶斯学习的复杂网络拓扑估计[J].物理学报,2012,61(14):497-505.
[18]OH Y,HONG J Y.Effect of Surface Profile Length on the Backscattering Coefficients of Bare Surfaces[J].IEEE Transactions on Geoscience&Remote Sensing,2007,45(3):632-638.
[19]SU Z,TROCH P A,DE TROCH F P.Remote sensing of soil moisture using EMAC/ESAR data[C]//Geoscience and Remote Sensing Symposium,1996.IGARSS’96.‘Remote Sensing for a Sustainable Future.’,International.IEEE,1997:1303-1305vol.2.
[20]BAGHDADI N,HOLAH N,ZRIBI M.Soil moisture estimation using multi‐incidence and multi‐polarization ASAR data[J].International Journal of Remote Sensing,2006,27(10):1907-1920.
[21]ALVAREZ-MOZOS J,CASALI J,GONZALEZ-AUDICANA M,et al.Assessment of the operational applicability of RADARSAT-1data for surface soil moisture estimation[J].IEEE Transactions on Geoscience&Remote Sensing,2006,44(4):913-924.
[22]甄珮珮.基于粗糙度参数的风沙滩地区土壤水分微波遥感反演模型研究[D].西安:长安大学,2016.
[2]ENGMAN E T,CHAUHAN N.Status of microwave soil moisture measurements with remote sensing[J].Remote Sensing of Environment,1995,51(1):189-198.
[3]KEYSER E D,VERNIEUWE H,LIEVENS H,et al.Assessment of SAR-retrieved soil moisture uncertainty induced by uncertainty on modeled soil surface roughness[J].International Journal of Applied Earth Observations&Geoinformation,2012,18(1):176-182.
[4]FERNNDEZ-GLVEZ J.Errors in soil moisture content estimates induced by uncertainties in the effective soil dielectric constant[J].International Journal of Remote Sensing,2008,29(11):3317-3323.
[5]MA C,LI X,NOTARNICOLA C,et al.Uncertainty Quantification of Soil Moisture Estimations Based on a Bayesian Probabilistic Inversion[J].IEEE Transactions on Geoscience&Remote Sensing,PP(99):1-14.
[6]李大治.L波段土壤水分反演的不确定性分析及其反演策略研究——以HiWATER PLMR数据为例[D].北京:中国科学院寒区旱区环境与工程研究所,2014.
[7]VERHOEST N E C,LIEVENS H,WAGNER W,et al.On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar[J].Sensors,2008,8(7):4213.
[8]RAHMAN M M,MORAN M S,THOMA D P,et al.A derivation of roughness correlation length for parameterizing radar backscatter models[J].International Journal of Remote Sensing,2007,28(18):3995-4012.
[9]DAVIDSON M,TOAN T L,MATTIA F,et al.On the characterization of agricultural soil roughness for radar remote sensing studies[J].IEEE Transactions on Geoscience&Remote Sensing,2000,38(2):630-640.
[10]郭立新,王蕊,吴振森.随机粗糙面散射的基本理论与方法[M].北京:科学出版社,2010.32-39.
[11]SHI J,CHEN K S,LI Q,et al.A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer[J].IEEE Transactions on Geoscience&Remote Sensing,2010,40(12):2674-2686.
[12]余凡,李海涛,张承明,等.利用双极化微波遥感数据反演土壤水分的新方法[J].武汉大学学报(信息科学版),2014,39(2):225-228.
[13]陈晶,贾毅,余凡.双极化雷达反演裸露地表土壤水分[J].农业工程学报,2013,29(10):109-116.
[14]LIEVENS H,VERHOSET N E C,KEYSER E D,et al.Effective roughness modelling as a tool for soil moisture retrieval from C-and L-band SAR[J].Hydrology&Earth System Sciences Discussions,2010,7(4):151-162.
[15]SALTELLI A,TARANTOLA S,CHAN K P S,et al.A quantitative model-independent method for global sensitivity analysis of model output[J].Technometrics,1999,41(1):39-56.
[16]CUKIER R,FORTUIN C,SHULER K,et al.Study of the sensitivity of the coupled reaction systems to uncertainties in rate coefficients:I.Theory[J].The Journal of Chemical Physics,1973,59:3873
[17]郝崇清,王江,邓斌,等.基于稀疏贝叶斯学习的复杂网络拓扑估计[J].物理学报,2012,61(14):497-505.
[18]OH Y,HONG J Y.Effect of Surface Profile Length on the Backscattering Coefficients of Bare Surfaces[J].IEEE Transactions on Geoscience&Remote Sensing,2007,45(3):632-638.
[19]SU Z,TROCH P A,DE TROCH F P.Remote sensing of soil moisture using EMAC/ESAR data[C]//Geoscience and Remote Sensing Symposium,1996.IGARSS’96.‘Remote Sensing for a Sustainable Future.’,International.IEEE,1997:1303-1305vol.2.
[20]BAGHDADI N,HOLAH N,ZRIBI M.Soil moisture estimation using multi‐incidence and multi‐polarization ASAR data[J].International Journal of Remote Sensing,2006,27(10):1907-1920.
[21]ALVAREZ-MOZOS J,CASALI J,GONZALEZ-AUDICANA M,et al.Assessment of the operational applicability of RADARSAT-1data for surface soil moisture estimation[J].IEEE Transactions on Geoscience&Remote Sensing,2006,44(4):913-924.
[22]甄珮珮.基于粗糙度参数的风沙滩地区土壤水分微波遥感反演模型研究[D].西安:长安大学,2016.