Title
An improved physical method with linear spectral emissivity constraint to retrieve land surface temperature, emissivity and atmospheric profiles from satellite-based hyperspectral thermal infrared data
Abstract
In this paper, an improved method is proposed to simultaneously retrieve land surface temperature (LST), emissivity (LSE) and atmospheric profiles. This method employed the linear spectral emissivity constraint to efficiently reduce the number of retrieved variables. The proposed method was validated with some simulations. The initial guesses were derived from a neural network model. This method could greatly improve the accuracies of LST, LSE and atmospheric profiles. The RMSE of LST was decreased from 5.12 K (the initial guesses) to 1.59 K (the physical retrieved). The retrieved emissivity spectrum was in good agreement with the actual spectrum. An improvement of 1K in the tropospheric temperature was also been found. Those results showed that the proposed method is capable of improving the retrieval accuracies of land surface and atmospheric parameters with the remotely sensed thermal infrared data.
Year
DOI
Venue
2012
10.1109/IGARSS.2012.6350991
IGARSS
Keywords
Field
DocType
troposphere,neural network model,remotely sensed thermal infrared data,remote sensing,hyperspectral,atmospheric techniques,atmospheric profiles,emissivity,satellite-based hyperspectral thermal infrared data,atmospheric profile,thermal infrared,retrieved emissivity spectrum,land surface temperature,linear spectral emissivity constraint,land surface emissivity,improved physical method,tropospheric temperature,atmospheric radiation,accuracy,atmospheric modeling
Meteorology,Land surface temperature,Satellite,Thermal infrared,Computer science,Remote sensing,Troposphere,Mean squared error,Hyperspectral imaging,Atmospheric model,Emissivity
Conference
Volume
Issue
ISSN
null
null
2153-6996 E-ISBN : 978-1-4673-1158-8
ISBN
Citations 
PageRank 
978-1-4673-1158-8
1
0.48
References 
Authors
0
8
Name
Order
Citations
PageRank
Ning Wang123087.46
Hua Wu2164.89
Lingling Ma34114.54
Xinhong Wang432.69
Yonggang Qian51710.45
Zhao-Liang Li6416127.21
Chuanrong Li74618.79
Lingli Tang8610.96