机载遥感数据的定量化研究
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摘要
本文的研究工作围绕高分辨率机载遥感数据的定量化处理展开，在总结当前辐射校正方面已有成果的基础上，对机载可见、近红外、短波红外以及热红外各个波段遥感数据定量化处理中遇到的问题进行了系统论述，从大气影响和地表本身复杂性两个角度机载遥感数据的定量化进行了深入研究。
大气对机载遥感数据影响的特点主要表现在大气的时空多变性上，本文针对机载数据获取特点，提出了基于地表对空红外辐射测量的大气温度和水汽剖面反演的两参数算法。该算法模拟实验的结果显示，可以较准确地反演大气柱水汽量和0—3km温度剖面的变化。
地表的复杂性在可见／近红外波段体现在由非均匀造成的交叉辐射影响和非朗伯双向反射特性两个方面。为此本文利用MODTRAN4从传感器入瞳辐射中环境辐射所占比例的角度分析了低空机载测量中影响交叉辐射的各种因素。结果显示，对于机载测量，大气交叉辐射影响随测量条件不同而改变，需要实时计算。为此，本文将传感器IFOV引进大气点扩散函数的解析近似算法，并将该算法与MODTRAN4辐射传输模型相结合，设计了校正大气交叉辐射影响的算法。对AMTIS图像的处理结果显示，该算法提高了地表反射比的计算精度。
为处理多角度数据，我们研制了多角度数据处理系统。该系统是针对机载AMTIS的数据的特点采用了模块化设计，也可以用于其它类型遥感数据的处理工作。
在热红外方面，红外发射率差异是地表复杂性的表现之一。本文在实验室内进行了非同温混合像元观测实验，验证了李小文等提出的非同温混合像元尺度效应，并指出面积比在组分温度反演中是影响组分温度反演精度的一个重要因素。同时本文还基于光谱平滑的温度／发射率迭代算法，设计了一种热红外发射率的野外测量方法，对土壤的含沙量、粒径、含水量与热红外发射率的相关性进行了研究。实验结果表明，在8-9.51μm波长范围内土壤的发射率随沙子含量增加而减少，但是随含水量的增加而增加；在11-13μm波长范围内土壤的发射率基本保持不变。本文根据土
中国科学院遥感应用研究所博士学位论文
壤热红外发射率的特点，设计了土壤发射率反演的 仍算法，并提出了利用红外通
道发射率比值进行土壤表层含水量反演的新思路。
最后对机载热红外数据处理流程进行了全面论述。对辐射定标中存在的噪声进
行了系统分析，并根据机载测量噪声的特点设计了基于样条拟合消除条带噪声的算
＼ 法，在处理机载OMIS热红外数据时较好地消除了条带噪声。
。本文的研究将促进机载多角度和机载多光谱遥感数据的定量化处理和应用。
In order to retrieve surface parameters, such as surface reflectance and temperature etc., it is very important to improve the quantitative processing accuracy of airborne remote sensing data with high spatial resolution and spectral resolution. After the major bottlenecks are summarized at first, this paper is devoted to solve these problems based on two aspects: the atmospheric attenuation and the surface complexity.
The atmospheric influences of the airborne remote sensing data are mainly due to the variability of low-layer atmosphere. According to the analysis of features of the data acquired from airplane, a new algorithm for retrieving atmospheric column water vapor and temperature profile is suggested based on measurements of downward sky thermal radiation above the surface. The results show that the new algorithm can estimate atmospheric column water vapor accurately, and air temperature at lower than 3 kilometers can also be retrieved.
The complexity of surface parameters can be characterized by cross radiance and BRDF in VIS/NIR band. At first, the proportion of cross radiance to the radiance received by sensor is analyzed using MODTRAN4 code, and then the influences of a set of factors on cross radiance are simulated. The main factors considered in this paper include: variation of aerosol phase function, aerosol optical thickness, sensor IFOV and viewing angle, flying height, and wavelength. The results show that the variance of cross radiance could be resulted from every factor mentioned above, so it must be computed based measurement condition. A new methodology is developed to eliminate cross radiance from total radiance based on a modification of analytical solution of PSF and combination of it with radiation transfer code of MODTRAN. The applications to AMTIS image show a good precision.
For the retrieval of BRDF information from airborne AMTIS data, a software system is modularized based on features of AMTIS data, and can also be used for processing of other types remote sensing data.
As-for the thermal infrared band, the thermal emissivity is the major factor of surface complexity. In this thesis a series of tests have been done in order to find out the IR feature of mixed pixel composed by objects with different temperatures. The results show that the augment of the effective emissivity exists when we define the temperature as an area
1U
weighted average temperature. The test validated Li-Wang-Strahler's scale-corrected Planck law for non-isothermal surfaces. And also in the dissertation, an experiment method is suggested to measure surface emissivity in field based on ISSTES algorithm (Iterative spectrally smooth temperature-emissvity separation). A deliberately designed set of measurements was carried out to study feature of the spectral emissivity of soil with different grain size or with different SiO2 and water content. The result shows that emissvity becomes lower with increasing sand content and higher with increasing water content in 8-9.5um region; In 1 l-14um region, the variance of emissivity is not as obvious as in 8-11 jam region. According to the result, a method is proposed for retrieving parameters of soil from TTR emissivity ratio.
By the end of this dissertation, the processing flow of airborne thermal multi-band data is represented in details. The noises in the radiative calibration of airborne thermal infrared data are analyzed systematically, and a new algorithm used for eliminating the striped noise based on the spline interpolation is developed. The results show a good effect in the processing of airborne OMIS thermal infrared data.
Our research could improve the quantitative research of airborne multi-angle and multi-band remote sensing data.
大气对机载遥感数据影响的特点主要表现在大气的时空多变性上，本文针对机载数据获取特点，提出了基于地表对空红外辐射测量的大气温度和水汽剖面反演的两参数算法。该算法模拟实验的结果显示，可以较准确地反演大气柱水汽量和0—3km温度剖面的变化。
地表的复杂性在可见／近红外波段体现在由非均匀造成的交叉辐射影响和非朗伯双向反射特性两个方面。为此本文利用MODTRAN4从传感器入瞳辐射中环境辐射所占比例的角度分析了低空机载测量中影响交叉辐射的各种因素。结果显示，对于机载测量，大气交叉辐射影响随测量条件不同而改变，需要实时计算。为此，本文将传感器IFOV引进大气点扩散函数的解析近似算法，并将该算法与MODTRAN4辐射传输模型相结合，设计了校正大气交叉辐射影响的算法。对AMTIS图像的处理结果显示，该算法提高了地表反射比的计算精度。
为处理多角度数据，我们研制了多角度数据处理系统。该系统是针对机载AMTIS的数据的特点采用了模块化设计，也可以用于其它类型遥感数据的处理工作。
在热红外方面，红外发射率差异是地表复杂性的表现之一。本文在实验室内进行了非同温混合像元观测实验，验证了李小文等提出的非同温混合像元尺度效应，并指出面积比在组分温度反演中是影响组分温度反演精度的一个重要因素。同时本文还基于光谱平滑的温度／发射率迭代算法，设计了一种热红外发射率的野外测量方法，对土壤的含沙量、粒径、含水量与热红外发射率的相关性进行了研究。实验结果表明，在8-9.51μm波长范围内土壤的发射率随沙子含量增加而减少，但是随含水量的增加而增加；在11-13μm波长范围内土壤的发射率基本保持不变。本文根据土
中国科学院遥感应用研究所博士学位论文
壤热红外发射率的特点，设计了土壤发射率反演的 仍算法，并提出了利用红外通
道发射率比值进行土壤表层含水量反演的新思路。
最后对机载热红外数据处理流程进行了全面论述。对辐射定标中存在的噪声进
行了系统分析，并根据机载测量噪声的特点设计了基于样条拟合消除条带噪声的算
＼ 法，在处理机载OMIS热红外数据时较好地消除了条带噪声。
。本文的研究将促进机载多角度和机载多光谱遥感数据的定量化处理和应用。
In order to retrieve surface parameters, such as surface reflectance and temperature etc., it is very important to improve the quantitative processing accuracy of airborne remote sensing data with high spatial resolution and spectral resolution. After the major bottlenecks are summarized at first, this paper is devoted to solve these problems based on two aspects: the atmospheric attenuation and the surface complexity.
The atmospheric influences of the airborne remote sensing data are mainly due to the variability of low-layer atmosphere. According to the analysis of features of the data acquired from airplane, a new algorithm for retrieving atmospheric column water vapor and temperature profile is suggested based on measurements of downward sky thermal radiation above the surface. The results show that the new algorithm can estimate atmospheric column water vapor accurately, and air temperature at lower than 3 kilometers can also be retrieved.
The complexity of surface parameters can be characterized by cross radiance and BRDF in VIS/NIR band. At first, the proportion of cross radiance to the radiance received by sensor is analyzed using MODTRAN4 code, and then the influences of a set of factors on cross radiance are simulated. The main factors considered in this paper include: variation of aerosol phase function, aerosol optical thickness, sensor IFOV and viewing angle, flying height, and wavelength. The results show that the variance of cross radiance could be resulted from every factor mentioned above, so it must be computed based measurement condition. A new methodology is developed to eliminate cross radiance from total radiance based on a modification of analytical solution of PSF and combination of it with radiation transfer code of MODTRAN. The applications to AMTIS image show a good precision.
For the retrieval of BRDF information from airborne AMTIS data, a software system is modularized based on features of AMTIS data, and can also be used for processing of other types remote sensing data.
As-for the thermal infrared band, the thermal emissivity is the major factor of surface complexity. In this thesis a series of tests have been done in order to find out the IR feature of mixed pixel composed by objects with different temperatures. The results show that the augment of the effective emissivity exists when we define the temperature as an area
1U
weighted average temperature. The test validated Li-Wang-Strahler's scale-corrected Planck law for non-isothermal surfaces. And also in the dissertation, an experiment method is suggested to measure surface emissivity in field based on ISSTES algorithm (Iterative spectrally smooth temperature-emissvity separation). A deliberately designed set of measurements was carried out to study feature of the spectral emissivity of soil with different grain size or with different SiO2 and water content. The result shows that emissvity becomes lower with increasing sand content and higher with increasing water content in 8-9.5um region; In 1 l-14um region, the variance of emissivity is not as obvious as in 8-11 jam region. According to the result, a method is proposed for retrieving parameters of soil from TTR emissivity ratio.
By the end of this dissertation, the processing flow of airborne thermal multi-band data is represented in details. The noises in the radiative calibration of airborne thermal infrared data are analyzed systematically, and a new algorithm used for eliminating the striped noise based on the spline interpolation is developed. The results show a good effect in the processing of airborne OMIS thermal infrared data.
Our research could improve the quantitative research of airborne multi-angle and multi-band remote sensing data.
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68． Griggs M.,Emissivities of natural surfaces in the 8-to 14-micon spectral region. J.Geophys.Res.,1968, 73:7545-7551．
69． Nerry F.,J.Labed and M.P.Stoll,Emissivity signatures in the thermal infrared band for remote sensing: calibration procedure and method of measurement. Appl.Optics, 1988,27:758-764．
70． Hepplewhite C.L., Remote observation of the sea surface and atmosphere: the oceanic skin effect, Int.J. Remote Sensing, 1989, 10:80 1-810．
71． Becker F.,and Li Z., Temperature-independent spectral indices in thermal infrared bands. Remote Sens.Environ. 1990,32:17-33．
72． Wan Zhengming, and J. Dozier, Land surface temperature measurement from space: physical principled and inverse modeling, IEEE Transaction on Geosicience and Remote Sensing, 1989,27(3) :
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74． Nerry F., J. Labed and M.P.Stoll,Emissivity signatures in the thermal infrared band for remote sensing: calibration procedure and method of measurement. Appl.Optics, 1988,27:758-764．
75． Rivard B., P. J.Thomas and J.Giroux, Precise emissivity of rock samples, Remote Sens.Environ. 1995,54:152-160．
76． 张仁华，田国良，常温比辐射率测量，科学通报，1981，26(5) ：297-300．
77． Nerry F.,J.Labed and M.P.Stoll,Spectral properties of land surfaces in the thermal infrared.Part 1:Laberatery measurements of absolute spectral emssivity signature, J.Geophys.Res. 1990a, 95(B5) :7027-7044．
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79． Coll C.,V.Caselles,and T.J.Schmugge,Estimation of land surface emissivity differences in the split-window channels of AVHRR, Remote Sens.Environ., 1993,48:127-134．
80． Salisbury J.W., Emissivity of terrestrial materials in the 3-5 um atmosphere window, Remote Sens.Environ. 1994,47:345-361．
81． Barton I.J.,and T.Talashima,An AVHRR investigation of surface emissivity near lake Eyre,Australia, Remote Sens.Environ., 1986,20:153-163．
82． Buettener K.J.K.,and C.D.Kem,The determination of infrared emissivity of terrestrial surfaces. J.Geophys.Res.,1965,70:1329-1337．
83． 张仁华，比辐射率的非封闭测定法初步探讨，科学通报，1981，26(23) ：1444-1447．
84． Rubio E.,V.Caselles, and C.Badenas,Emissivity measurements of several soils and vegetation types in the 8-14 um wave band:analysis of two field methods, Remote Sens. Environ.
1997,59:490-520.
85. Li Xiaowen, Wang Jindi, A.H.Strahler. Scale effect of Planck law for non-isothermal blackbody surface [J]. Science in China(E), 1999, 29(5):422—426.1999, 29(5):422—426.]
86. Becker, F., Z. Li.Surface temperature and emissivity at various scales: Definition,measurement,and related problems[J], Remote sensing Reviews, 1995, 12:225—253.
87. Dozier, J. A method for satellite identification of surface temperature fields of subpixel resolution[J], Remote Sensing of Environment,1981, 11:221—229.
88. Paul M.,Ingram and A.Henry Muse,Sensivity of Iterative Spectrally Smooth Temperature/Emissivity Separation to Algorithmic Assumptions and Measurement Noise. IEEE Transactions on Geoscience and Remote Sensing, 39, No 10, Oct. 2001,2158-2167.
89．陈良富，庄家礼，徐希孺，1999a，“热红外遥感中通道间信息相关性及其对陆面温度反演的影响”，科学通报，44(19)：2122-2127。
90．张霞，张兵等，航空热红外多光谱数据的地物发射率谱信息提取模型及其应用研究，红外与毫米波报，第19卷第5期，2000年10月。
91．宋宁，胡逢曜，殷宗敏，航天遥感器热红外波段辐射精度分析，激光与红外，2001年6月，163-165，vol．31，no．3。
92．陈衡，红外物理，国防工业出版社。
93. D'Agostino,J.A.,Webb,C.M.Three-dimensional analysis framework and measurement methology fro imageing system noise[J].SPIE Symposium on Aerospace Sensing,1991,1488:110-21
94．王杰生，TM热红外图像的横纹条带噪声及消除，遥感技术与应用，1995年2月，53-56,Vol．10，No．1。
95．张仁华，实验遥感模型及地面基础，科学出版社，1996年第一版。
96. Lyon, R, J. P., Analysis of Rocks by Spectral Infrared Emission (8 tO 25μm). Econ. Geol.60,715-736,1965.
97．沈鸣明，刘银年，方抗美，肖金才等，MIS成像光谱仪系统评价及飞行试验。
98．柳钦火，顾行发，李小文等，2000a，“地表热红外辐射方向特性的航空飞行实验研究”，中国科学(E)，30(增)：99-105。
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