Improvements in the split-window technique for land surfacetemperature determination

Land surface temperature (LST) retrievals obtained from NOAA Advanced Very High Resolution Radiometer (AVHRR) are of considerable importance for climatic research. However, the accurate evaluation of LST from space has been severely limited because of the difficulty in separating atmospheric from surface effects as the surface cannot be modeled as a black-body radiator. With this goal in mind, a novel extension of the split-window technique is presented in which the atmospheric contribution to the radiance measured by the satellite is investigated by the ratioing of covariance and variance of the brightness temperatures measured in channels 4 and 5 of AVHRR/2. Furthermore, the contribution of emissivity is evaluated from coefficients that depend on the spectral emissivities in both thermal channels. Using a wide range of simulations from an atmospheric radiative transfer model it is shown that the proposed algorithm provides an estimate of LST, to within 0.4 K if the spectral surface emissivity is known, which is better than that given by the currently used split-window algorithms for LST determination. Also the limitations on algorithm accuracy are discussed considering different values of noise equivalent temperature. Finally the authors present the preliminary results obtained using the proposed method from AVHRR data over a semi-arid region-of Northwestern Victoria in Australia provided by CSIRO, and a mountainous region of Northeast of France acquired in the frame of Regio Klimat Projekt     

Atmospheric corrections in the thermal infrared: global and watervapor dependent split-window algorithms-applications to ATSR and AVHRRdata

The split-window method is an appropriate way to perform atmospheric corrections of satellite brightness temperatures in order to retrieve the surface temperature. A climatological data set of 1761 different radio soundings, the TIGR database, has been used to develop two different split-window methods. A global quadratic (QUAD) method, with global coefficients to be applied on a worldwide scale, and a water vapor dependent (WVD) algorithm. The first method includes a quadratic term in the split-window equation that roughly accounts for the water vapor amount. The other method explicitly includes the water vapor amount in each split-window coefficient. When applied to the 1761 radio soundings, the latter method gives better results than the global one, especially when the surface emissivity is far from unity (0.95 or less) and when the water vapor reaches great values. Both algorithms have been tested on ATSR/ERSI and AVHRR/NOAA data over sea pixels. The QUAD algorithm gives correct results for simulations (the standard error is 0.2 K) and experimental data (the bias ranges from -0.1 to 0.4 K). The WVD algorithm appears to be more accurate for both simulations (the standard error is less than 0.1 K) and AVHRR experimental data when climatological water vapor contents are used (the bias ranges from -0.2 to 0.1 K)     

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     

Impact of the atmospheric transmittance and total water vaporcontent in the algorithms for estimating satellite sea surfacetemperatures

Sea surface temperature (SST) algorithms for NOAA AVHRR data can determine SST with rms values of 0.7 K on a global basis. However, this figure is not compatible with the high accuracy of 0.3 K required by climate studies. Biases in the SST product, arising when the factors that increase the optical path-length (absorbents concentration in the atmosphere or viewing angles) are large, cause problems in the use of the split-window formulation for climate monitoring. The reason is that the split-window coefficients currently used are not adequate to cover for all the atmospheric variability. To show this, simulations of channels 4 and 5 of AVHRR/2 of NOAA-11 using a radiative transfer model have been made. The range of atmospheric conditions and surface temperatures introduced in the simulation covers the variability of these parameters on a worldwide scale. From these data, the authors present new split-window coefficients that take into account the atmospheric variability through the ratio of the channel transmittances, or else through the total water vapor content along the path. They also show, using simulated and actual data, that the proposed split-window algorithm has a real global character and represents an improvement over the conventional algorithms     

用HJ-1B卫星数据反演地表温度的修正单通道算法

目前用于地表温度反演的单通道算法主要针对窄视场传感器建立.HJ-1B卫星红外相机为宽视场传感器,其热红外通道(IRS4)观测天顶角可达±33°以上,在地表温度反演时必须剔除传感器观测角度的影响.以大气辐射传输模拟为基础,建立了基于传感器观测天顶角-大气函数系数的修正单通道算法.针对HJ-1B卫星与Terra卫星过境时间...     

Land-surface temperature measurement from space: physicalprinciples and inverse modeling

To apply the multiple-wavelength (split-window) method used for satellite measurement of sea-surface temperature from thermal-infrared data to land-surface temperatures, the authors statistically analyze simulations using an atmospheric radiative transfer model. The range of atmospheric conditions and surface temperatures simulated is wide enough to cover variations in clear atmospheric properties and surface temperatures, both of which are larger over land than over sea. Surface elevation is also included as the most important topographic effect. Land covers characterized by measured or modeled spectral emissivities include snow, clay, sands, and tree leaf samples. The empirical inverse model can estimate the surface temperature with a standard deviation less than 0.3 K and a maximum error less than 1 K. A band in the region from 10.2 to 11.0 μm will usually give the most reliable single-band estimate of surface temperature. A band in either the 3.5-4.0-μm region or in the 11.5-12.6-μm region must be included for accurate atmospheric correction     

An optimization algorithm for separating land surface temperatureand emissivity from multispectral thermal infrared imagery

Land surface temperature (LST) and emissivity are important components of land surface modeling and applications. The only practical means of obtaining LST at spatial and temporal resolutions appropriate for most modeling applications is through remote sensing. While the popular split-window method has been widely used to estimate LST, it requires known emissivity values. Multispectral thermal infrared imagery provides us with an excellent opportunity to estimate both LST and emissivity simultaneously, but the difficulty is that a single multispectral thermal measurement with N bands presents N equations in N+1 unknowns (N spectral emissivities and LST). In this study, we developed a general algorithm that can separate land surface emissivity and LST from any multispectral thermal imagery, such as moderate-resolution imaging spectroradiometer (MODIS) and advanced spaceborne thermal emission and reflection radiometer (ASTER) data. The central idea was to establish empirical constraints, and regularization methods were used to estimate both emissivity and LST through an optimization algorithm. It allows us to incorporate any prior knowledge in a formal way, The numerical experiments showed that this algorithm is very effective (more than 43.4% inversion results differed from the actual LST within 0.5°, 70.2% within 1° and 84% within 1.5°), although improvements are still needed     

单通道物理法反演海表温度的参数敏感性分析及验证

定量分析了反演海表温度的单通道物理法对海水比辐射率、海面风速、海水盐度、大气透过率、大气上下行辐射等参数的敏感性,发现海水比辐射率、大气透过率对算法精度影响较大,是单通道物理法反演海表温度的主要误差来源.在不同的波段,单通道物理法对参数敏感性也有较大差别,中红外波段的敏感性要小于热红外波段.为了验证单通道物理法的可行性、精度及参数敏感性分析的结果,选择墨西哥湾海域2009年全年夜间MODIS实测数据进行实验.结果表明,中红外波段的单通道物理法反演海表温度的精度高于热红外波段,达到MODIS劈窗算法海表温度标准产品同等精度,这与参数敏感性分析的结果一致.由于中红外波段单通道物理法精度较高,一方面,可以满足常规的业务观测需求,为海表温度反演提供新的技术手段;另一方面,可用来标定劈窗算法系数,弥补海洋现场观测站位空间分布不足的问题.     

基于遗传算法综合Terra/Aqua MODIS热红外数据反演地表组分温度

混合像元组分温度相对来说更有应用价值,而多角度热红外遥感的发展推动了混合像元组分温度反演基础和方法的发展.根据前期数值模拟得到Terra和Aqua卫星上的MODIS测量可以认为是同一卫星在两个不同观测时间和观测角度上的测量,综合利用Terra和Aqua卫星上的MODIS数据反演混合像元内土壤和植被组分温度.根据混合像元热红外辐射模型,利用遗传算法,分别模拟Terra卫星MODIS的32和33通道,以及Terra和Aqua卫星上MODIS的32通道辐射反演了河北怀来试验区范围内植被覆盖率、土壤组分温度和比辐射率、植被组分温度和比辐射率等表面参数.通过与实测数据进行比较,综合利用上午Terra和下午Aqua卫星32通道数据反演的上午植被组分温度与地面同步测量温度偏差在1℃内,而利用上午Terra卫星32和33通道数据反演的上午植被组分温度与地面同步测量值偏差在1.4℃内.尽管利用双星数据反演的组分温度精度相对较高,但针对同一个像元,两个方案反演的结果有一定偏差.     

基于MODIS数据的地表温度反演

利用MODIS影像数据,采用劈窗算法来反演安徽地区的地表温度。结合Sobrine、覃志豪等人提出的NDVITEM方法和地物监督分类方法,对地表比辐射率进行了估算,将反演结果与NASA的地表温度产品进行比较,平均误差在1 K左右。同时利用卫星过境当天从安徽省高密度自动监测站获取的实时数据对反演结果进行验证,发现反演温度与地面实测数据的曲线走势具有高度的一致性且有较高的相关性,能直观地反映安徽地区地表温度的空间分布。     

The RADTRAN microwave surface emission models

The AFGL RADTRAN microwave atmospheric transmission/brightness temperature computer code has been enhanced by a surface emissivity modeling subpackage. This enhancement will provide realistic calculations of frequency-dependent polarized surface emissivity to support simulations of Earth-viewing microwave sensing systems. These models are appropriate for the frequency range 1-40 GHz. Two distinct modeling approaches have been applied: one based on wave theory for random discrete scatterers, and one based on radiative transfer theory for continuous random media. The former approach is used to model the ocean surface, various forms of sea ice, and snow over land, whereas the latter is used to treat soils and vegetation. Surface emissivity values obtained from these models as functions of polarization, frequency, and look angle are illustrated     

参数弱固定法反演地表温度

提出了弱固定敏感参数、控制信息流向目标参数的地表温度反演方法.从热红外辐射传输机理出发,以MODIS为数据源,构建辐射传输方程,同时反演包括地表温度、大气平均温度、中红外(3～5μm)、远红外(8-14.5 μm)6个波段的大气透过率和发射率共计14个参数.以MODTRAN模拟数据和重庆地区MODIS遥感影像为实验数据...     

BRDF models to predict spectral reflectance and emissivity in thethermal infrared

This paper presents modifications to the linear kernel bidirectional reflectance distribution function (BRDF) models from Roujean et al. and from Wanner et al. that extend the spectral range into the thermal infrared (TIR). The present authors application is to synthesize the TIR optical properties of a scene pixel from laboratory component measurements. The angular reflectance and emissivity are needed to convert the radiance of a pixel as measured from space to land-surface temperature. The kernel models will be applied to develop a look-up table for the MODIS land-surface temperature algorithm to estimate the spectral, angular scene emissivity from land cover classification. A shrub scene and a dense canopy scene illustrate qualitative differences in angular emissivity that would not be evident without the kernel model modifications. They conclude that the modified models provide a simple and efficient way to estimate scene optical properties over a wide spectral range     

Thermal Land Surface Emissivity Retrieved From SEVIRI/Meteosat

The methodologies used by the Satellite Application Facility on Land Surface Analysis (Land SAF) for retrieving emissivity are presented here. In the first approach, i.e., the vegetation cover method (VCM), the land surface emissivity (EM) is computed for Spinning Enhanced Visible and Infrared Imager (SEVIRI) infrared channels and for the 3- to 14- range using information on the pixel fraction of vegetation cover (FVC). The VCM uses a lookup table, which takes into account the channel's spectral response function, and laboratory reflectance spectra for different materials. The accuracy of the VCM depends on the reliability of FVC and the land cover classification. The EM for SEVIRI split-window channels is primarily used as an internal product by Land SAF for land surface temperature (LST) estimations. However, sensitivity studies show that LST often fails to meet the required accuracy of 2 K over desert and semiarid regions, where the VCM is unable to model the EM spatial variability, which is mostly associated with soil composition. Moreover, it is also over such areas where the atmosphere is generally dry that the impact of EM uncertainties on LST is largest. A second approach to determine the EM for SEVIRI split-window channels is currently being tested. This methodology allows the simultaneous retrieval of LST and channel EMs with the assumption that the latter remain constant. The channel EMs are then averaged over a 22-day period to filter out the noise in the retrievals. A first analysis of the maps obtained for an area within Northern Africa shows spatial patterns with features also present in the surface albedo.     

A semiempirical model for interpreting microwave emission fromsemiarid land surfaces as seen from space

A radiative transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The approach used is described, and the sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7     

利用MODIS水汽数据进行ASAR干涉测量大气改正研究

对流层水汽引起的大气相位延迟是制约重复轨道InSAR 高精度测量的重要因素之一。为有效解决InSAR 中大气相位延迟的问题,对InSAR 中大气延迟误差进行了分析,研究了利用MODIS 水汽数据对ASAR 干涉图大气改正的方法及其关键技术,并以太原地区的ASAR 干涉图为例,对其进行大气改正。实验结果表明,MODIS/ASAR 大气改正方法可以显著地提高干涉图的质量,同时形变反演的精度也得到了明显的改善,验证了MODIS 与ASAR 数据融合获取地表形变信息的必要性和可靠性。     

A Practical Method for Retrieving Land Surface Temperature From AMSR-E Over the Amazon Forest

Remote sensing of land surface temperature (LST) using infrared (IR) sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is only capable of retrieval under clear-sky conditions. Such LST observations over tropical forests are very limited due to clouds and rainfall, particularly during the wet season and high atmospheric water-vapor content. In comparison, low-frequency microwave radiances are minimally influenced by meteorological conditions. Exploring this advantage, we have developed an algorithm to retrieve LST over the Amazonian forest. The algorithm uses multifrequency polarized microwave brightness temperatures from the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System (AMSR-E). Relationships between polarization ratio and surface emissivity are established for forested and nonforested areas, such that LST can solely be calculated from microwave radiance. Results are presented over three time scales: at each orbit, daily, and monthly. Results are evaluated by comparing with available air-temperature records on daily and monthly intervals. Our findings indicate that the AMSR-E-derived LST agrees well with in situ measurements. Results during the wet season over the tropical forest suggest that the AMSR-E LST is robust under all-weather conditions and shows higher correlation to meteorological data (r = 0.70) than the IR-based LST approaches (r = 0.42).     

基于MODIS红外通道的辐射传输计算

通过建立地气系统的红外辐射传输方程,基于MODIS红外通道进行辐射传输计算.利用快速精确的透过率模型PFAAST计算大气透过率,在红外辐射传输计算中考虑了地面反射大气辐射亮度的影响,指出地面反射大气辐射亮度在整个方程所占比重随着地表发射率变小而增加,其中MODIS第33通道对发射率的改变最为敏感,美国标准大气下,当发射率ε=0.65时,比重达到7.12%,因此,忽略地面反射大气辐射亮度,直接影响红外辐射传输计算的准确性.模拟了MODIS各红外通道辐射亮度,并与MODTRAN4.0模拟结果比较,相对误差不超过0.12%,模拟了大气倾斜路径对卫星红外通道观测亮温的影响.     

Satellite-Observed Location of Stratocumulus Cloud-Top Heights in the Presence of Strong Inversions

Infrared channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to infer cloud-top pressure (CTP), temperature, and effective cloud amount or emissivity. For low clouds, those with tops at pressures greater than 700 hPa, the infrared window 11-mum channel brightness temperature is used to determine the CTP and the corresponding cloud-top temperature by comparison with the temperature profile obtained from the NCEP Global Data Assimilation System meteorological analysis. In the presence of strong inversions which are common for marine stratus and stratocumulus, this leads to the identification of an erroneously high cloud-top height (CTH). This discrepancy is illustrated by comparing MODIS CTHs with those inferred from the geometric method used by the Multiangle Imaging SpectroRadiometer on the same satellite platform, and field observations. The error in CTH is typically about 2 km and depends on the shape of the actual temperature profile. It is shown that column water vapor above cloud retrieved from the MODIS solar infrared channels in the vicinity of the 0.94-mum water vapor absorption band can be used to flag the error and that the location of the true CTH could possibly be obtained using lapse rate formulations for cloud-topped boundary layers.     

沙尘气溶胶对热红外分裂窗通道亮温和地表反演温度的影响研究

沙尘气溶胶通过改变地-气系统的热红外辐射传输可引起地表温度遥感探测结果发生变化.较系统地研究了冬季和夏季沙尘气溶胶光学厚度(AOD)变化对热红外分裂窗通道亮温(BT)和地表反演温度(LST)的影响,以及反演结果受大气水汽和地表因素的作用.红外辐射传输模拟计算表明:1)沙尘气溶胶影响下,热红外分裂窗通道亮温差小于零;2)随AOD增大,BT和LST都减小,其中LST减小的速度大于BT;3)不同水汽含量下LST变化不明显;4)当AOD较大时,LST主要反映沙尘层的温度信息.模拟结果与中国北方典型沙尘实例分析结果有较好的一致性.