合肥大气下行长波辐射估算模型研究与改进

大气下行辐射是地表辐射和能量平衡中的一个关键参数, 在反演地表温度和发射率、开展气候变化研究 中起着关键作用。基于现有的大气下行辐射测量方法的分析比较, 开展了合肥大气下行长波辐射的研究。利用 MODTRAN 辐射传输模型模拟计算了合肥大气下行辐射通量, 并以该方法获取的大气下行辐射通量为基准, 对广 泛应用的个晴天经验模型进行性能评价, 验证了 Idso 模型和 Ångstrom ¨ 模型对于合肥大气条件的适用性。进而利用 MODTRAN 辐射传输模型模拟数据对 Idso 模型中的参数进行修正, 提高了该模型的模拟精度。该研究为方便快捷准 确地获取合肥大气下行辐射通量提供了可靠方法。     

分裂窗辐射量线形组合反演陆面温度的影响因子分析

大气特性与地物发射率是影响陆温反演精度的主要因素,不同的分裂窗表达式用于陆温反演存在不同的反演结果,其中两通道辐射量线形组合形式的分裂窗算法受大气影响最小,反演温度的误差也最小.其反演温度的误差与大气透过率和大气向上辐射无关,但与地物的发射率、大气向下辐射相关.分裂窗表达式B(λ,′Ts°)=a.I(λ1)+b.I(λ2)+c中的反演系数a、b与大气向上辐射无关,但分别与通道1、通道2的大气透过率成反比.当定标点发射率不完全一致时,二者还与大气向下辐射相关;相反,如果定标点发射率完全一致,二者与大气向下辐射无关.使用辐射量线性组合的分裂窗形式反演陆温时,当大气向下辐射与地物的P lanck辐射越相近,误差越小.     

基于大气吸收线特征的高光谱热红外数据地表温度/比辐射率反演算法

地表温度和比辐射率的准确提取和反演是热红外遥感的核心问题之一.由于地表温度/比辐射率反演问题的病态性,以及地表—大气强耦合特征等诸多问题,导致目前反演精度仍有待进一步提高.通过深入挖掘大气吸收峰/谷通道处下行辐射偏移量特性,提出了一种基于大气吸收线特征的高光谱热红外温度/比辐射率反演方法,并通过最优通道选择提高了算法的效率和精度.算法一定程度上可抑制大气校正不准确引入的误差,能够有效提高低比辐射率地物的反演精度.模拟数据结果表明:针对高比辐射率地物,算法与ISSTES方法的反演精度基本一致;针对低比辐射率地物,算法最大可提高温度0.48 K和比辐射率2.1%的精度.地面实测数据结果表明:约77%的样本温度反演误差优于1K,比辐射率误差均值优于0.01.     

中红外双通道夜间数据地表温度反演方法

地表温度反演是红外定量遥感的核心内容之一.与热红外(8~14μm)数据相比,中红外(3~5μm)波谱区大气透过率更高、对发射率的敏感性更低,在温度反演方面具有独特的优势.引入热红外地表温度反演思路,发展了仅利用夜间中红外双通道数据的地表温度反演算法,分析了宽通道组合(3~4μm和4~5μm)和窄通道组合(3.929~3.989μm和4.020~4.080μm)模式下的温度反演精度以及模型对噪声和发射率的敏感性.结果表明,宽、窄两种通道组合模型的温度反演精度分别为~0.5 K和~0.3 K;噪声等效温差和地表发射率误差对窄通道组合模型的影响更大.     

大气气溶胶对用红外窗区通道遥感陆面温度的影响

分析了大气气溶胶对红外窗区通道辐射传输的影响,考察了在用红外窗区通道反演陆面温度中,大气温度和湿度廓线没有误差时,大气气溶胶的不确定性对反演精度的影响,以及大气温度、湿度和气溶胶同时有偏差对地面温度反演精度的影响.     

遥感试验数据确定大气气溶胶类型的方法研究

以太湖为研究区,通过水面光谱实验采集,地基太阳光度计大气测量,和当天的MODIS遥感影像,联合遥感太湖地区的大气光学特性,提出了一种实验确定气溶胶类型的方法.通过与卫星影像准同步的地面光谱和太阳光度计试验,利用辐射传输模式6S,变化气溶胶类型各组分,建立关于星上辐射的查找表,并利用定义的相对误差参量,在其总误差最小时确定气溶胶类型.将其用于改进后的Mie散射程序来计算大气气溶胶粒子群包括偏振散射相函数等的光学特性,并用于太湖地区大气气溶胶光学厚度的反演中,所得结果参考CE318实测值,反演精度有了较大的提高.该研究方法与结果可为大气气溶胶光学特性计算,大气辐射传输方程,气溶胶光学厚度反演,卫星数据大气校正等遥感应用提供支持.     

基于NOAA卫星图像信息的大气辐射校正方法研究

探讨一种基于NOAA卫星图像信息的大气辐射校正方法.选用实测的海陆边界表面大气水汽压eD,并合理选择海陆分界表面物体的发射率ε,利用图像信息对大气影响进行校正.由于采用同一时刻、同一条件下图像大气辐射信息,该方法具有时效性.并用该方法选取NOAA卫星图像中海陆边界区域进行反演试验,得出该方法是正确可行的.同时利用大气辐射传输模型MODTRAN程序,选定了几种大气模式,设定1976年美国标准大气作为标准,进行了算法间的对比分析.分析结果表明:该方法校正效果明显,操作简单,实用性强.     

基于FY-3C/MWHTS资料的海洋晴空大气温湿廓线反演方法研究

针对搭载于风云三号C星(FY-3C)上的微波湿温探测仪(Microwave Humidity and Temperature Sounder, MWHTS), 建立了海洋晴空大气条件下温湿廓线同时反演的一维变分反演系统.通过对影响反演精度的各个因素进行分析, 确立了该系统的输入参数.对于FY-3C/MWHTS观测亮温与快速辐射传输(Radiative Transfer Model for TOVS, RTTOV)模型的模拟亮温之间的偏差和角度依赖性, 采用逐像元统计回归校正方法进行校正.选择西北太平洋海域晴空条件下的校正亮温数据进行温湿廓线的反演, 并利用欧洲中期天气预报中心再分析数据集对反演结果进行验证, 结果表明:反演的温度廓线和相对湿度廓线的最大平均偏差分别为1.09 K和5.4%, 最大均方根误差分别为1.48 K和22.69%, 与未校正亮温的反演结果相比, 温度廓线的均方根误差最大可减小1.56 K, 湿度廓线的均方根误差最大可减小14.71%.反演温湿廓线与背景廓线的精度对比表明:反演的温度廓线在10~70 hPa、300~350 hPa和700~850 hPa内的精度高于背景廓线的精度, 而反演湿度廓线的精度除了825~875 hPa, 其他范围均高于背景廓线的精度, 因此FY-3C/MWHTS观测亮温的反演结果可进一步提高预报廓线精度.     

基于NOAA卫星图像信息的大气校正方法研究

给出一种基于NOAA卫星图像信息的大气辐射校正方法.选用实测的海陆边界表面大气水汽压eD,并合理选择海陆分界表面物体的发射率ε,利用图像信息对大气的影响进行校正.由于采用同一时刻、同一条件下的自身大气辐射信息,该方法具有时效性.对NOAA卫星图像中海陆边界不同区域的反演结果表明:该方法校正效果明显、操作简单且实用性强.     

部分云覆盖下红外辐射传输模型及对火山灰云的敏感性研究

针对我国新一代地球同步气象卫星FY-4的预期发射和数据应用,本文借助与FY-4卫星成像仪类似的Meteosat-8卫星的SEVIRI仪器数据资料开展先期研究,建立了一种部分云覆盖条件下红外辐射传输模型,模拟了不同大气条件、火山灰云高度、有效云量和观测天顶角情况下卫星观测的红外通道的亮度温度的变化。美国标准气候态大气廓线和火山灰区实时大气廓线两种模拟结果都表明,模型模拟的8.3~9.1μm,9.8~11.8μm,11~13μm,12.4~14.4μm的入瞳亮度温度对云高度、有效云量较为敏感,基本呈线性相关;卫星天顶角对模拟的辐射亮温的影响相对较小。通过不同大气廓线状态和火山灰云发射率情景下的测试结果表明,只有同时考虑大气条件和火山灰云通道发射率的差异后,模式才能够较好地模拟出火山爆发情景下火山灰云中酸性物质在11μm和12μm的反吸收特性。与大气条件相比,通道的发射率差异对火山灰云的遥感建模更为重要。因此,可在传统的分裂窗通道的基础上,通过热红外多通道亮温及亮温差异信息联合反演火山灰云高度和有效云量等因子,提高部分覆盖下火山灰云的微物理参数的反演精度。本研究为建立基于我国新一代静止气象卫星FY-4数据的火山灰云浓度定量反演模型提供了理论基础。     

基于订正ALPHA差值谱的热红外温度与发射率分离算法

与可见光遥感不同，热红外传感器测得的辐射亮度值是温度和发射率的函数，因此，对于热红外遥感，温度和发射率的分离是一个关键问题？本研究从普朗克方程的维恩近似出发，定义并推导出与温度无关的ALPHA差值谱，并进一步提出消除维思近似影响的修正项．以此为基础，在不考虑大气下行辐射影响的条件下，借鉴ALPHA导出发射率法和ASTERTES算法的优点，提出一个新的发射率温度分离算法．与现有发射率温度分离算法相比，该算法的优点是原理清楚，流程简单，求解速度快，结果精度高，并且适用的温度和下垫面范围宽．     

A temperature and emissivity separation algorithm for AdvancedSpaceborne Thermal Emission and Reflection Radiometer (ASTER)images

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scanner on NASA's Earth Observing System (EOS)-AM1 satellite (launch scheduled for 1998) will collect five bands of thermal infrared (TIR) data with a noise equivalent temperature difference (NEΔT) of ⩽0.3 K to estimate surface temperatures and emissivity spectra, especially over land, where emissivities are not known in advance. Temperature/emissivity separation (TES) is difficult because there are five measurements but six unknowns. Various approaches have been used to constrain the extra degree of freedom. ASTER's TES algorithm hybridizes three established algorithms, first estimating the normalized emissivities and then calculating emissivity band ratios. An empirical relationship predicts the minimum emissivity from the spectral contrast of the ratioed values, permitting recovery of the emissivity spectrum. TES uses an iterative approach to remove reflected sky irradiance. Based on numerical simulation, TES should be able to recover temperatures within about ±1.5 K and emissivities within about ±0.015. Validation using airborne simulator images taken over playas and ponds in central Nevada demonstrates that, with proper atmospheric compensation, it is possible to meet the theoretical expectations. The main sources of uncertainty in the output temperature and emissivity images are the empirical relationship between emissivity values and spectral contrast, compensation for reflected sky irradiance, and ASTER's precision, calibration, and atmospheric compensation     

Spectral mixture analysis of simulated thermal infraredspectrometry data: An initial temperature estimate bounded TESSMA searchapproach

At sensor thermal infrared (TIR) radiation varies depending on the temperature and emissivity of surface materials and the modifying impact of atmospheric absorption and emission. TIR imaging spectrometry often involves extracting temperature, emissivity, and/or surface composition, which are useful in diverse studies ranging from climatology to land use analyses. A two-stage application of temperature emissivity separation (TES) using spectral mixture analysis (SMA) or TESSMA, was employed to characterize isothermal mixtures on a subpixel basis. This two-stage approach first uses the relationship between a virtual cold endmember fraction and surface temperature to extract initial image temperature estimates. Second, an isothermal SMA application searches the region within the maximum temperature error range of the initial estimate, selecting the best subpixel spectral mixture fit. Work presented includes characterizations of synthetically generated temperature and constituent mixture gradient test images, and a discussion of errors associated with selecting temperature search ranges 25% and 75% smaller than the initial temperature calculation error range. Results using this two-stage approach indicate improved overall temperature estimates, constituent estimates, and constituent fraction estimates using simulated TIR data     

基于场景的热红外高光谱数据光谱定标

传感器每个波段的中心波长和半高全宽（Full Width at Half Maximum，FWHM）随成像环境变化会发生较大的系统性漂移。这种漂移最终会影响发射率和温度的反演精度，尤其是在大气吸收波段附近的发射率反演精度。选择水汽在11.73 m处的吸收通道作为参考波段，提出了适用于热红外高光谱数据的光谱定标技术流程。模拟实验表明:光谱分辨率为50 nm，中心波长偏移在-50~50 nm、FWHM变化在-25~25 nm时，大气水汽含量对光谱定标误差的影响最大。同时，对误差分布曲面进行拟合得到描述误差分布模型，用于误差的估计。当大气水汽含量足够大时，光谱中心波长偏移估算误差可达到1 nm以内。最后，将所提方法应用于机载热红外高光谱数据光谱定标。结果显示，热红外高光谱成像仪中心波长偏移为28.4 nm，FWHM变化为-18.5 nm。     

基于标准黑体的物体表面发射率计算方法研究

红外测温仪器的精度和被测物体表面的发射率对测量物体红外辐射特性的准确性影响很大。为了提高物体表面发射率的计算精度,先通过标准黑体对红外热像仪进行标定。然后,利用标定好的红外热像仪测量温度,计算出被测物体表面的发射率。将基于神经网络的红外热像仪标定方法应用到目标发射率的求解方法中,有效地消除了热像仪的系统误差。测试装置简单,测试结果准确。同时,温度和发射率的精确测量为红外隐身材料的研制奠定了基础。     

Accurate atmospheric correction of ASTER thermal infrared imagery using the WVS method

The water vapor scaling (WVS) method involves an atmospheric correction algorithm for thermal infrared (TIR) multispectral data, designed mainly for the five TIR spectral bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on the Terra satellite. First, this method is improved for better applicability to ASTER/TIR imagery. The major improvement is the determination of a water vapor scaling factor on a band-by-band basis, which can reduce most of the errors induced by various factors such as algorithm assumptions. Next, the WVS method is validated by assessing the surface temperature and emissivity retrieved for a global-based simulation model (416 448 conditions), 183 ASTER scenes selected globally, and ASTER scenes from two test sites, Hawaii Island and Tokyo Bay. In situ lake surface temperatures measured in 13 vicarious calibration experiments, Moderate Resolution Imaging Spectroradiometer sea surface temperature products, and a climatic lake temperature are also used in validation. All the results indicate that although the ASTER/TIR standard atmospheric correction algorithm performs less well in humid conditions, the WVS method will provide more accurate retrieval of surface temperature and emissivity in most conditions including notably humid conditions. The expected root mean square error is about 0.6 K in temperature. Since the WVS method will be degraded by errors in gray pixel selection and cloud detection, these processing steps should be applied accurately.     

A physics-based algorithm for retrieving land-surface emissivityand temperature from EOS/MODIS data

The authors have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical recession method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of hand-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NEΔT) and calibration accuracy specifications of the MODIS Instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 μm IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K     

基于傅里叶变换红外光谱仪的光谱发射率估计

基于傅里叶变换红外(Fourier Transform Infrared, FTIR)光谱仪等先进测试 手段,建立了一种估计目标光谱发射率的方法框架。首先,通过双温度测量标定获得FTIR光谱仪关于波 长的背景辐射亮度函数和响应度函数,提高了测量的准确性;其次,基于大气窗口的辐射亮度数据进行高阶多 项式拟合,进一步抑制了杂散辐射的影响;然后通过对大气吸收波长的辐射特性进行估计,获得了所测波段的 红外亮度曲线;最后估计了目标的光谱发射率,其相对误差均在1%以内。测试结果表明,本文方法行之有效。     

An efficient two-scale model for the computation of thermal emission and atmospheric reflection from the sea surface

An efficient implementation of the two-scale model of sea surface thermal emission and atmospheric reflection is described. The model is applied in a study of the reflection of downwelling atmospheric radiation. Results show that reflected downwelling radiation can increase azimuthal variations of total observed brightnesses.