用辐射传输方程从MODIS数据中反演地表温度的方法

介绍了辐射传输方程反演地表温度理论和传统参数的获取.针对MODIS波段设置特点,从MODIS的某些波段来反演大气参数,从而突破传统参数获取的局限性,提高了辐射传输方法在地表温度反演中的实用性.最后用环渤海地区的MODIS影像对该地区的地表温度进行了反演,并对MODIS的第31,32波段反演结果做了对比分析.     

AMSR-E被动微波土壤水分与降雨率时空相关性分析研究

地表土壤水分和降水具有高度相关性,是2个密切相关的地-气相互作用参量.采用同时反演获取的土壤水分和大气降水数据来研究土壤水分的变化情况,定量理解降水和土壤水分之间的物理联系,进而可以获得对反演算法改进有用的信息.采用被动微波辐射计AMSR-E反演获得的全球地表土壤水分和降雨率数据作为研究对象,一共收集了2005年10月1日至2006年10月31日之间共395 d的AMSR-E全球日土壤水分产品和升、降轨道瞬时降雨率数据.把降雨率轨道产品经过等积割圆柱投影并重采样到同日土壤水分产品相当的25 km分辨率EASE-Grid格点上.针对土壤水分和投影后得到的日降雨率数据进行每2,8,16 d的时间维平均,在空间维进行3×3、5×5、7×7格点的重采样,经时间序列对比,分析了降水对土壤水分反演的影响及其时空相关特性,并对反演参数间弱相关性出现的原因进行了探讨,这对于发现微波土壤水分和大气降雨算法的不足,提供其改进方向具有重要的指导意义.     

The study of estimation method of broadband emissivity from EOS/MODIS data

The broadband emissivity is an important parameter for estimating the energy balance of the Earth.This study focuses on estimating the window(8-12 |xm) emissivity from the MODIS(moderate-resolution imaging spectroradiometer) data,and two methods are built.The regression method obtains the broadband emissivity from MOD11B1 5KM product,whose coefficient is developed by using 128 spectra,and the standard deviation of error is about 0.0118 and the mean error is about0.0084.Although the estimation accuracy is very high while the broadband emissivity is estimated from the emissivity of bands 29,31 and 32 obtained from MOD11B1 5KM product,the standard deviations of errors of single emissivity in bands 29,31,32 are about 0.009 for MOD11B1_5KM product,so the total error is about 0.02 and resolution is about 5km×5km.A combined radiative transfer model with dynamic learning neural network method is used to estimate the broadband emissivity from MODIS 1B data.The standard deviation of error is about 0.016,the mean error is about0.01,and the resolution is about 1km ×1km.The validation and application analysis indicates that the regression is simpler and more practical,and estimation accuracy of the dynamic learning neural network method is higher.Considering the needs for accuracy and practicalities in application,one of them can be chosen to estimate the broadband emissivity from MODIS data.