杨亮彦,孔金玲,王雅婷,李健锋,张文博

• 1:长安大学地球科学与资源学院
• 2:长安大学地质工程与测绘学院

摘要(Abstract)：

针对旱区大气水汽含量难以获取,且精度不高的问题,该文利用Landsat8两个热红外波段,基于SWCVR算法构建旱区大气水汽含量反演模型。与气象站实测数据进行验证,其均方根误差为0.31 g/cm~2,绝对误差为0.25 g/cm~2;与MOD05水汽产品对比发现,两者水汽的平均值分别为2.63和2.37 g/cm~2,且空间分布基本一致,但空间分辨率和成像时间的不同,导致存在一定差异性。结果表明,针对Landsat8热红外遥感数据,30×30的窗口大小最优,既保留了中高空间分辨率的优点,又获得了具有实用价值的精度;基于SWCVR算法的大气水汽含量反演方法在风沙滩地区具有较好的应用。

关键词(KeyWords)： 大气水汽含量;Landsat8;SWCVR;旱区

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41272246)

作者(Author): 杨亮彦,孔金玲,王雅婷,李健锋,张文博

DOI: 10.16251/j.cnki.1009-2307.2020.05.014

参考文献(References)：

• [1] MIERUCH S,NOEL S,BOVENSMANN H,et al.Analysis of global water vapor trends from satellite measurements in the visible spectral range[J].Atmos.Chem.Phys,2008,8(3):491-504.
• [2] LI Z L,JIA L,Su Z B.A new approach for retrieving precipitable water from ATSR2 split-window channel data over land area[J].lnternational Journal of Remote Sensing,2003,24(24):5095-5117.
• [3] 姜立鹏,覃志豪,谢雯.针对MODIS近红外数据反演大气水汽含量研究[J].国土资源遥感,2006(3):5-9,88.(JIANG Lipeng,QIN Zhihao,XIE Wen.Retrieving atmospheric water vapor from MODIS near infrared data[J].Remote Sensing for Land & Resources,2006(3):5-9,88.)
• [4] 雷忠腾,江涛,崔相辉,等.TERRA/MODIS热红外通道陆地晴空大气可降水分裂窗反演[J].测绘与空间地理信息,2018,41(2):98-101.(LEI Zhongteng,JIANG Tao,CUI Xianghui,et al.Retrieval atmospheric water over land using TERRA/MODIS thermal split-window algorithm in clear sky[J].Geomatics & Spatial Informational Technology,2018,41(2):98-101.)
• [5] ALBERT P,BENNARTZ R,PREUSKER R.Remote sensing of atmospheric water vapor using the Moderate Resolution Imaging Spectroradiometer[J].Atmos.Oceanic Technol,2005,22:309-314.
• [6] SOBRINO J A,LI Z L,STOLL M P.Improvements in the split-window technique for land surface temperature determination[J].IEEE Transactions on Geoscience and Remote Sensing,1994,32:243-253.
• [7] SOBRINO J A,RAISSOUNI N,SIMARRO J.Atmospheric water vapor content over land surfaces derived from the AVHRR data:application to the Iberian Peninsula[J].IEEE Transactions on Geoscience and Remote Sensing,1999,37 (3):1425-1434.
• [8] PADMANABHAN S,REIDING S C,VIVEKANANDAN J.Retrieval of atmospheric water vapor density with fine spatial resolution using three-dimensional tomographic inversion of microwave brightness temperatures measured by a network of scanning compact radiometers[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(11):3708-3721.
• [9] BARDUCCI A,GUZZI D,MARCOIONNI P.Algorithm for the retrieval of columnar water vapor from hyperspectral remotely sensed data[J].Appl.Opt.,2004,43(29):5552-5563.
• [10] 王永前,施建成,曾巧林,等.TRMM/VIRS热红外通道陆地大气可降水汽总量分裂窗反演[J].遥感学报,2016,20(1):94-102.(WANG Yongqian,SHI Jiancheng,ZENG Qiaolin,et al.Retrieval of precipitable water vapor over land using TRMM/VIRS thermal split window measurements [J].Journal of Remote Sensing,2015,20(1):94-102.)
• [11] DALU G.Satellite remote sensing of atmospheric water vapor[J].International Journal of Remote Sensing,1986,7(9):1089-1097.
• [12] KLEESPIES T J,MCMILLIN L M.Retrieval of precipitable water from observations in the split-window over varying surface temperatures[J].Journal of Applied Meteorology,1990,29(9):851-862.
• [13] REN H,DU C,LIU R.Atmospheric water vapor retrieval from Landsat 8 thermal infrared images[J].Journal of Geophysical Research:Atmospheres,2015,120:1723-1738.
• [14] 王猛猛,何国金,张兆明,等.基于Landsat 8 TIRS数据的大气水汽含量反演劈窗算法[J].遥感技术与应用,2017,32(1):166-172.(WANG Mengmeng,HE Guojin,ZHANG Zhaoming,et al.Atmospheric water vapor retrieval from Landsat-8 TIRS data using split-window algorithm[J].Remote Sensing Technology and Application,2017,32(1):166-172.)
• [15] 徐涵秋,唐菲.新一代Landsat系列卫星:Landsat 8遥感影像新增特征及其生态环境意义[J].生态学报,2013,33(11):3249-3257.(XU Hanqiu,TANG Fei.Analysis of new characteristics of the first Landsat 8 image and their ecoenvironmental significance[J].Acta Ecologica Sinica,2013,33(11):3249-3257.)
• [16] 覃志豪,LI Wenjuan,ZHANG Minghua,等.单窗算法的大气参数估计方法[J].国土资源遥感,2003(2):37-43.(QIN Zhihao,LI Wenjuan,ZHANG Minghua,et al.Estimating of the essential atmospheric parameters of mono-window algorithm for land surface temperature retrieval from Landsat TM6[J].Remote Sensing for Land & Resources,2003 (2):37-43.)
• [17] 宋彩英.基于Landsat8的地表温度像元分解算法研究[D].南京:南京大学,2015:21-22.(SONG Caiying.An effective pixel decomposition approach for land surface temperature of Landsat8[D].Nanjing:Nanjing University,2015:21-22.)