程洁等:A disaggregation approach for estimating high spatial resolution broadband emissivity for bare soils from Landsat surface reflectance
被阅读 458 次
2018-06-25
A disaggregation approach for estimating high spatial resolution broadband emissivity for bare soils from Landsat surface reflectance
作者:Cheng, J (Cheng, Jie)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 1,2 ] ; Liu, H (Liu, Hao)[ 1 ] ; Nie, AX (Nie, Aixiu)[ 3 ] ; Liu, Q (Liu, Qiang)[ 3 ]
INTERNATIONAL JOURNAL OF DIGITAL EARTH
卷: 11  期: 7  页: 691-702
DOI: 10.1080/17538947.2017.1341559
出版年: 2018
文献类型:Article
 
摘要
High spatial resolution land surface broadband emissivity (BBE) is not only useful for surface energy balance studies at local scales, but also can bridge the gap between existing coarser resolution BBE products and point-based field measurements. This study proposes a disaggregation approach that utilizes the established BBE-reflectance relationship for estimating high spatial resolution BBE for bare soils from Landsat surface reflectance data. The disaggregated BBE is compared to the BBE calculated from spatial-temporal matched Advanced Spaceborne Thermal Emission and Reflectance Radiometer emissivity product. Comparison results show that better agreement is achieved over relative homogeneous areas, but deteriorated over heterogeneous and cloud-contaminated areas. In addition, field-measured emissivity data over large homogeneous desert were also used to validate the disaggregated BBE, and the bias is 0.005. The comparison and validation results indicated that the disaggregation approach can obtain high spatial resolution BBE with better accuracy for homogeneous area.
 
通讯作者地址: Cheng, J (通讯作者)
Beijing Normal Univ, Fac Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Fac Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[ 3 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing, Peoples R China