Himawari 8 AHI数据地表温度反演的实用劈窗算法  

Practical split-window algorithm for retrieving land surface temperature from Himawari 8 AHI data

作　　者：刘超[1,2] 历华 杜永明 曹彪 柳钦火 孟翔晨 胡友健 LIU Chao LI Hua DU Yongming CAO Biao LIU Qinhuo MENG Xiangchen HU Youjian(College of Information Engineering, China University of Geosciences, Wuhan 430074, China State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences Beijing 100101, China Joint Center for Global Change Studies （JCGCS）, Beijing 100875, China State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China)

机构地区：[1]中国地质大学(武汉)信息工程学院,武汉430074 [2]中国科学院遥感与数字地球研究所遥感科学国家重点实验室,北京100101 [3]全球变化与中国绿色发展协同创新中心,北京100875 [4]北京师范大学地理学与遥感科学学院遥感科学国家重点实验室,北京100875

出　　处：《遥感学报》2017年第5期702-714,共13页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:41571357;41571359;41501366);高分四号卫星应用共性关键技术项目(编号:30-Y20A02-9003-15/16);国家高技术研究发展计划(863计划)(编号:2013AA12A304)~~

摘　　要：地表温度是水文、气象、气候和环境等研究领域中的关键参数,利用热红外遥感可快速获取区域和全球高精度的地表温度数据。Himawari 8号是日本发射的新一代地球静止轨道气象卫星,星上搭载AHI(Advanced Himawari Imager)成像仪,具有更高的时空分辨率。利用AHI第14(11.2μm)和15(12.35μm)通道星上亮温数据,提出反演地表温度的实用劈窗算法,其中输入的发射率数据利用ASTER GED(Global Emissivity Dataset)v4计算得到。劈窗算法的系数由观测角度和大气水汽含量分区决定,其中大气水汽含量由两个劈窗通道直接估算得到。利用黑河流域生态—水文过程综合遥感观测联合试验(Hi WATER)4个站点的实测数据和中国7个湖泊中心点的MODIS地表温度产品对反演结果进行验证,结果表明,算法的均方根误差(RMSE)在3 K以内,达到目前常用遥感地表温度产品的精度。同时与利用MOD11C3 C6产品估算的发射率和温度反演结果进行对比分析,发现ASTER GED反演的结果具有更高的精度,适合用来生产高精度的地表温度产品。Land Surface Temperature （LST） is a key parameter for hydrological, meteorological, climatological, and environmental re- search fields. Accurate regional and global LST products can be obtained from thermal infrared remote sensing data. Himawari-8 is the next- generation of Japan geostationary meteorological satellite, which carries a new optical sensor called Advanced Himawari Imager （AHI）, with significantly higher temporal and spatial resolutions. AHI has 16 observation bands, with spatial resolutions of 0.5 or 1 km for visible andnear-infrared bands and 2 km for infrared bands. AHI can provide full disk images every 10 minutes, and can provide high temporal and spa- tial resolution LST information for many studies. The bands 14 and 15 of AHI can be used for LST retrieval by using the Split-Window （SW） algorithm. Thus, the objective of this paper is to propose a practical SW algorithm to retrieve LST from AHI data. Land Surface Emissivity （LSE） is one of the essential parameters for SW algorithm. SW algorithm is extremely sensitive to emissivity errors, and the sens- itivity is significantly higher for direr atmospheres. A 0.005 error in emissivity will result in a LST error of 1 K or more under drier condi- tions. The ASTER Global Emissivity Dataset （GED） version 4 was adopted to calculate the LSE in this paper to improve the accuracy of emissivity in barren surfaces. The refined Generalized Split-Window （GSW） algorithm developed for MODIS was adopted to retrieve LST from the brightness tem- perature of AHl bands 14 and 15. MODTRAN 5.2, TIGR 3 atmospheric profile database, and ASTER spectral library data were used to cre- ate a simulation database to obtain the coefficients of the GSW algorithm. The coefficients were determined based on view zenith angle and atmospheric Water Vapor （WV） sub-ranges to improve the accuracy, and the WV was directly calculated using a simple method based on the brightness temperature of AHI bands 14 and 15. Two kinds of emissivity products were used

关 键 词：地表温度 劈窗算法 AHI ASTER GED 大气水汽含量 

分 类 号：P407[天文地球—大气科学及气象学]