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基于MODIS数据地表温度反演劈窗算法的比较研究
引用本文:乔小,孙龙,冯锐,纪瑞鹏,于文颖,张淑杰,武晋雯. 基于MODIS数据地表温度反演劈窗算法的比较研究[J]. 气象与环境学报, 2014, 30(6): 158-162
作者姓名:乔小  孙龙  冯锐  纪瑞鹏  于文颖  张淑杰  武晋雯
作者单位:1. 沈阳中心气象台,辽宁 沈阳 110166;2.南京信息工程大学,江苏 南京 210044;3.沈阳市气象局,辽宁 沈阳 110168;4.中国气象局沈阳大气环境研究所,辽宁 沈阳 110166
基金项目:辽宁省科技厅“农业气象灾害精细化预报及风险评估研究”,公益性行业(气象)专项,国家自然科学基金,江苏省2013年度普通高校研究生科研创新计划项目(CX-LX13_481)共同资助。
摘    要:选取QIN和SOB两种代表性劈窗算法对辽宁地区地表温度进行反演,并分析二者的精度和误差分布。结果表明:QIN和SOB算法反演的地表温度(TS)与地面气象台站准同步观测的气温和地温的线性拟合显著,SOB算法线性拟合更好;从误差分布直方图上看,两种算法的反演结果与地温更接近,SOB算法与同步气温和地温在±2 ℃之间的误差比例略高于QIN算法;在野外开展与卫星遥感空间尺度一致的地表温度观测试验,QIN和SOB算法与实测值的平均绝对误差均为1.5 ℃;与NASA官网发布的地表温度产品对比发现,QIN和SOB算法的平均绝对误差分别为1.75 ℃、1.70 ℃;因此QIN、SOB算法在辽宁地区均适用,SOB算法误差更小。

关 键 词:劈窗算法  相关性  误差分析  

Comparative study on land surface temperature retrieval using split-window methods based on MODIS data
QIAO Xiao-shi,SUN Long-yu,FENG Rui,JI Rui-peing,YU Wen-ying,ZHANG Shu-jie,WU Jin-wen. Comparative study on land surface temperature retrieval using split-window methods based on MODIS data[J]. Journal of Meteorology and Environment, 2014, 30(6): 158-162
Authors:QIAO Xiao-shi  SUN Long-yu  FENG Rui  JI Rui-peing  YU Wen-ying  ZHANG Shu-jie  WU Jin-wen
Affiliation:1. Shenyang Central Meteorological Observatory, Shenyang 110166, China; 2. Nanjing University of Information Science & Technology, Nanjing 210044, China; 3.Shenyang Meteorological Service, Shenyang 110168, China; 4. Institute of Atmospheric Environment, Chine Meteorological Administration, Shenyang 110016, China
Abstract:Using QIN and SOB representative algorithms for retrieving land surface temperature (LST) based on the MODIS in Liaoning province, both precision and error were analyzed. The results show that LST retrieved by QIN and SOB algorithms has a good linear fitting with the observed air temperature and surface temperature, especially for a SOB algorithm. According to the error histograms, retrieved LST by two methods is close to the observed surface temperature. Errors of the air and surface temperature between ±2 ℃ calculated by two methods are compared, and error ratio of the SOB algorithm is slightly higher than that of the QIN algorithm. Field experiment, being a same resolution with remote sensing data, suggests that mean absolute errors between two the retrieved and observed temperature both are 1.5 ℃. Compared with the LST from NASA website, mean absolute error of the QIN and SOB algorithms are 1.75 ℃ and 1.70 ℃, respectively. Thus, the two algorithms both are suitable in Liaoning province, and the SOB algorithm has less error.
Keywords:Split-window method  Correlation  Error analysis
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