【作者】 孙静；

【导师】 赵萍；

【作者基本信息】 安徽师范大学 ， 地图学与地理信息系统， 2012， 硕士

【摘要】 地表温度是区域和全球尺度上陆地表面物理过程的一个关键参数，综合了地气间相互作用的结果，是地球表面能量平衡和温室效应的良好指示计，在气候、水文、生态、军事和生物地球化学等研究领域有着广泛的应用。利用遥感反演地表温度在过去已取得了很大的进展，前人发展了大量的温度反演算法，但这些算法都把大量存在的非同温混合像元视为同温同质体，使得反演得到的只是物理意义模糊不清的该混合像元的平均温度。而事实上在大量的地表温度实际应用中，需要的是物理意义明确的地表组分温度。植被和土壤的组分温度在全球变化研究、地表过程模拟以及农作物估产、干旱监测等方面都有重要的应用价值。由于多角度数据相比多波段数据更有利于组分温度的反演，因此学者们致力于地表非同温混合像元热辐射方向性建模研究并提出了多种热辐射方向性模型，且在此基础上进行了一系列的组分温度分解算法的研究。但到目前为止，限于卫星技术的发展，人们可以有效利用的星载多角度数据较少。鉴于地表组分温度反演的必要性和符合要求的星载多角度遥感数据的不易获得性，研究一种基于多波段遥感数据的地表组分温度反演方法，具有非常重要的理论和现实意义。与TM、ETM+、AVHRR及MODIS等传感器的热红外数据相比，ASTER的热红外数据同时具有较高光谱分辨率和较高空间分辨率，这是使用ASTER数据反演地表组分温度的优势所在。因此，本文利用ASTER数据，以光照植被、阴影植被、光照土壤和阴影土壤四种混合像元为研究对象，对地表组分温度的反演方法进行了研究，主要内容和成果如下：(1)用MonteCarlo方法模拟植被和土壤有效比辐射率，以及光照植被、阴影植被、光照土壤和阴影土壤四种组分面积比，进而计算得到光照植被有效比辐射率、阴影植被有效比辐射率、光照土壤有效比辐射率和阴影土壤有效比辐射率。(2)建立地表组分有效比辐射率方向性模型，通过引入波长变量λ，并视观测角度θ为常量，建立了一种以多波段热红外数据为数据源，用以组分温度反演的地表热辐射波长变化模型。(3)提出了一种利用ASTER5个热红外波段建立温度反演方程，从而对地表热辐射波长变化模型进行求解的方法。(4)以安徽阜阳小麦种植区为研究区，以ASTER数据为数据源，使用本文提出的模型和方法获得了地表组分温度的初步解。在同一像元中光照土壤温度最高，光照植被和阴影植被次之，阴影土壤温度最低。更多还原

【Abstract】 The land surface temperature (LST) is an important parameter for the landsurface physical processes on both regional and global scale, integrating the results ofinteraction between the land and the atmosphere, the good indicator of energy balanceand greenhouse effect of the earth, and has been extensively used in climatology,hydrology, biology, military affairs and bio-geochemistry, etc..During the past long period, much progress has been realized on the study of theretrieval of LST based on remote sensing, and many algorithms for the LST retrievalhave been developed. However, in these algorithms non-isothermal mixed-pixels areall treated as an isothermal and homogeneous surface, which caused directly theresults that the LST obtained by these algorithms is only an average temperature ofmixed-pixel. In fact,, it is desirable to obtain surface component temperature withclear physical meanings in many LST application fields.The vegetation-soil component temperatures play important roles in manydisciplines like climate change research, surface process simulation, crop yieldestimation and draught monitoring.Because of considering that multi-angular data set is more beneficial to surfacecomponent temperature retrieval than multi-channel data set，people have devotedthemselves to study the radiant directionality model of surface non-isothermalmixed-pixels and have put forward several models,on which a serial of studies oncomponent temperature retrieval algorithm have been carried out.However, valid spaceborne multi-angular data set is infrequent．With a viewofthe necessity of surface component temperature retrieval and exiguity of validspaceborne multi-angular data set, it is undoubtedly of great practical significance tostudy surface component temperature retrieval algorithm based on multi-channel dataset.Compared with thermal infrared data set from Landsat/ETM+, NOAA/AVHRRand MODIS, thermal infrared data set from ASTER are much better in both spatialand spectral resolution, which has made ASTER advantages to retrieve componenttemperature on land surface. For this reason, this dissertation carried out the following study on component temperature based on ASTER thermal infrared data set, takingthe mixed pixel with light vegetation, shadows vegetation, light soil and shadow soilas the research object:(1) Using the MonteCarlo method to simulate vegetation and soil effectiveemissivity, and area ratio of light vegetation, shadows vegetation, light soil andshadow soil, then calculate effective emissivity of light vegetation, shadowsvegetation, light soil and shadow soil;(2) By taking the directionality model of surface component effective emissivity,adding wavelength variable λ, and treating observing angle θ constant, the surfaceradiant wavelength variety model that use multi-band thermal infrared data as datasources is defined;(3) A method is proposed to solve the surface radiant wavelength variety modelby using ASTER5TIR bands establish temperature inversion equation;(4) Taking wheat growing areas in FuYang, AnHui as the study area, surfacecomponent temperature is obtained by the above-mentioned method based on ASTERdata. In the same pixel, light soil temperature is the highest, light vegetationtemperature and shadow vegetation temperature take second and third place, Shadowsoil temperature is the lowest.更多还原