Validation of Landsat land surface temperature product in the conterminous United States using in situ measurements from SURFRAD, ARM, and NDBC sites  

作　　者：Si-Bo Duan Zhao-Liang Li Wei Zhao Penghai Wu Cheng Huang Xiao-Jing Han Maofang Gao Pei Leng Guofei Shang 

机构地区：[1]Key Laboratory of Agricultural Remote Sensing,Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing,People’s Republic of China [2]School of Land Science and Space Planning,Hebei GEO University Hebei,People’s Republic of China [3]Institute of Mountain Hazards and Environment,Chinese Academy of Sciences,Chengdu,People’s Republic of China [4]Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration,Anhui University,Hefei,People’s Republic of China

出　　处：《International Journal of Digital Earth》2021年第5期640-660,共21页国际数字地球学报（英文）

基　　金：supported by the National Natural Science Foundation of China[grant numbers 41871275 and 41921001];by the Fundamental Research Funds for Central Non-profit Scientific Institution[grant number 1610132020044].

摘　　要：Since 1982,Landsat series of satellite sensors continuously acquired thermal infrared images of the Earth’s land surface.In this study,Landsat 5,7,and 8 land surface temperature(LST)products in the conterminous United States from 2009 to 2019 were validated using in situ measurements collected at 6 SURFRAD(Surface Radiation Budget Network)sites,6 ARM(Atmospheric Radiation Measurement)sites,and 9 NDBC(National Data Buoy Center)sites.The results indicate that a relatively consistent performance among Landsat 5,7,and 8 LST products is obtained for most sites due to the consistent LST retrieval algorithm in conjunction with the same atmospheric compensation and land surface emissivity(LSE)correction methods for Landsat 5,7,and 8 sensors.Large bias and root mean square error(RMSE)of Landsat LST product are obtained at some vegetated sites due to incorrect LSE estimation where LSE is invariant with the increasing of normalized difference vegetation index(NDVI).Except for the sites with incorrect LSE estimation,a mean bias(RMSE)of the differences between Landsat LST and in situ LST is 1.0 K(2.1 K)over snow-free land surfaces,−1.1 K(1.6 K)over snow surfaces,and−0.3 K(1.1 K)over water surfaces.

关 键 词：Land surface temperature land surface emissivity VALIDATION LANDSAT 

分 类 号：TP7[自动化与计算机技术—检测技术与自动化装置]