NPP-VIIRS热红外数据地表温度反演方法研究

摘要/Abstract

摘要： 地表温度作为监测陆地表面与大气变化的重要参数，对于研究地表能量平衡和全球气候变化具有重要作用。可见光红外成像辐射仪套件（Visible Infrared Imaging Radiometer Suite，VIIRS）是搭载在新一代对地观测卫星NPP上的一个重要传感器。与其他传感器相比，VIIRS拥有更高的空间分辨率。分裂窗算法是反演地表温度最常用的方法，主要是利用两个热红外通道来反演地表温度，经过多年的研究和改进，发展了多种形式的分裂窗算法。由于过去很少有人利用VIIRS数据对多种分裂窗算法进行对比分析，因此利用VIIRS传感器上M15和M16两个热红外通道数据计算辐亮度和星上亮温，采用多种形式的分裂窗算法反演获得多组地表温度数据，再利用海拉尔野外观测站点的实测数据对结果进行验证，对比各算法精度，得到反演精度较高的算法。结果显示PR84算法的反演误差最大达到1.8 K，其余各算法反演地表温度的RMSE都在1.5 K以内，算法中加入二次项和水汽项可以提高算法精度，其中BL95的算法精度最高达到了1.23 K。研究结果表明，BL95算法更适用于VIIRS热红外数据地表温度反演。

关键词: 地表温度, 分裂窗算法, VIIRS

Abstract: As an important parameter forthe balance of water and energy in land surface and the atmosphere,the land surface temperature (LST)plays an important role in the study of global climate change. Visible Infrared Imaging Radiometer Suite (VIIRS)is a significant instrument equipped on the new generation earth observation satellite south-NPP. Compared to other sensors,VIIRS has a higher spatial and temporal resolution. It is fullydeveloped and can be used to retrieve the land surface temperature in a variety of methods. The split window algorithm, which takes the advantage oftwo thermal infrared channels,is the most commonly method used for retrieving LST. After years of researching and improving,a variety of split-window algorithmsare developed. The split window algorithms are derived from radiative transfer equation in thermal infrared region. The coefficients of the split window algorithms are determined in terms of the simulation data from MODTRAN5.2,the atmospheric radiation transfer software. The surface emissivity in the split window channels isestimated by using the NDVI-based threshold method. The channels M15 and M16 of VIIRS are used to calculatethe radiance and the brightness temperature of the atmosphere,and then the visible channel I1 and I2 are used to calculate NDVI for estimating land surface emissivity. Multiple forms of split window algorithms are used to acquire LST and then verified with thefield data of observation stations in Hailar field site. Those algorithms are compared and the one with the highest precision will be selected to improve LST retrieval accuracy for VIIRS. The error of the split window algorithm for retrieving land surface temperature is mainly caused by the instrument noise,surface emissivity and atmospheric properties,those uncertainty input factors will affect the accuracy of the LST retrieval. Through sensitivity analysis,the influence of these factors on the accuracy of the algorithm is determined. The total error of each algorithm is almost 0.75-1.5 K,the largest error is 1.42 K from the PR84 algorithm,and the minimum error of SR00 algorithm is 0.75 K. The land surface emissivity has a greater impact on the split window algorithm. The land surface temperature retrieves by different algorithms,and through the analysis and the verification of each algorithm, it can be seen that the algorithm containing two items has more accurate,and the algorithm accuracy can be improved if the algorithm contains the item of water vapor.The final result shows that the maximum error ofthe algorithm PR84 reaches to1.84 K,the maximum RMSE of the Surface temperatureretrieved by other algorithms is below 1.5 K. the algorithm BL95 has the highest accuracy about 1.23 K,which is more suitable for retrieving land surface temperature with the VIIRS thermal infrared data.

Key words: land surface temperature, split window algorithm, VIIRS

中图分类号:

TP79

王晨光, 段四波, 张霄羽, 冷佩, 高懋芳, 李召良. NPP-VIIRS热红外数据地表温度反演方法研究[J]. 干旱区地理, 2017, 40(6): 1264-1273.

WANG Chen-guang, DUAN Si-bo, ZHANG Xiao-yu, LENG Pei, GAO Mao-fang, LI Zhao-liang. Method for retrieval of land surface temperature from NPP-VIIRS thermal infrared data[J]. , 2017, 40(6): 1264-1273.

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