历华等:Evaluation of the VIIRS and MODIS LST products in an arid area of Northwest China
被阅读 2142 次
2013-12-30

Evaluation of the VIIRS and MODIS LST products in an arid area of Northwest China

Author(s): Hua Li , Donglian Sun , Yunyue Yu , Hongyan Wang , Yuling Liu , Qinhuo Liu , Yongming Du , Heshun Wang, BiaoCao

REMOTE SENSING OF ENVIRONMENT
卷: 142  页: 111-121
DOI: 10.1016/j.rse.2013.11.014
出版年: FEB 25 2014
 
摘要
In this study, the Visible Infrared Imager Radiometer Suite (VIIRS) land surface temperature (LST) environmental data record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) L2 swath LST products (collection 5) from both the Terra and Aqua satellites were evaluated against ground observations in an arid area of northwest China during the Heihe Watershed Allied Telemetry Experimental Research (Hi WATER) experiment. Four barren surface sites were chosen for the evaluation, which took place from June 2012 to April 2013. The results show that the current VIIRS LST products demonstrate a reasonable accuracy, with an average bias of 036 K and -0.58 K and an average root mean square error (RMSE) of 2.74 K and 1.48 K for the four sites during daytime and nighttime, respectively. The accuracy of the nighttime LST is much better than that of daytime. Furthermore, it was also found that the VIIRS split-window (SW) algorithm provides better performance than the VIIRS dual split-window (DSW) algorithm during both daytime and nighttime. For MODIS LST products, the results show that both Terra and Aqua MODIS C5 LST products underestimate the LST for the four barren surface sites at daytime, and the biases and RMSEs are much larger for Aqua, with biases varies from -0.91 K to -3.13 K for Terra and from -131 K to -3.76 K for Aqua. (C) 2013 The Authors. Published by Elsevier Inc All rights reserved.
 
作者信息
通讯作者地址: Liu, QH (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] George Mason Univ, Dept Geog & Geoinformat Sci, Fairfax, VA 22030 USA
[ 3 ] NOAA NESDIS Ctr Satellite Applicat & Res, College Pk, MD 20742 USA
[ 4 ] Ocean Univ China, Coll Informat Sci & Engn, Dept Marine Technol, Qingdao 266100, Peoples R China
[ 5 ] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20740 USA