Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data
K. Arai. International Journal of Advanced Computer Science and Applications(IJACSA), (2012)
Zusammenfassung
In order to evaluate the skin surface temperature (SSST) estimation accuracy with MODIS data, 84 of MODIS scenes together with the match-up data of NCEP/GDAS are used. Through regressive analysis, it is found that 0.305 to 0.417 K of RMSE can be achieved. Furthermore, it also is found that band 29 is effective for atmospheric correction (30.6 to 38.8\% of estimation accuracy improvement). If single coefficient set for the regressive equation is used for all the cases, SSST estimation accuracy is around 1.969 K so that the specific coefficient set for the five different cases have to be set.
%0 Journal Article
%1 IJACSA.2012.031108
%A Arai, Kohei
%D 2012
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K AQUA/MODIS MODTRAN; NCEP/GDAS; Regressive Skin Split Terra Thermal analysis; and infrared method; radiometer; sea surface temperature; window
%N 11
%T Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data
%U http://ijacsa.thesai.org/
%V 3
%X In order to evaluate the skin surface temperature (SSST) estimation accuracy with MODIS data, 84 of MODIS scenes together with the match-up data of NCEP/GDAS are used. Through regressive analysis, it is found that 0.305 to 0.417 K of RMSE can be achieved. Furthermore, it also is found that band 29 is effective for atmospheric correction (30.6 to 38.8\% of estimation accuracy improvement). If single coefficient set for the regressive equation is used for all the cases, SSST estimation accuracy is around 1.969 K so that the specific coefficient set for the five different cases have to be set.
@article{IJACSA.2012.031108,
abstract = {In order to evaluate the skin surface temperature (SSST) estimation accuracy with MODIS data, 84 of MODIS scenes together with the match-up data of NCEP/GDAS are used. Through regressive analysis, it is found that 0.305 to 0.417 K of RMSE can be achieved. Furthermore, it also is found that band 29 is effective for atmospheric correction (30.6 to 38.8\% of estimation accuracy improvement). If single coefficient set for the regressive equation is used for all the cases, SSST estimation accuracy is around 1.969 K so that the specific coefficient set for the five different cases have to be set.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {Arai, Kohei},
biburl = {https://www.bibsonomy.org/bibtex/2bdeaf02553d5937eaa57764ece5ed6e3/thesaiorg},
interhash = {25119e1c6551416af1e498a2a1881b55},
intrahash = {bdeaf02553d5937eaa57764ece5ed6e3},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {AQUA/MODIS MODTRAN; NCEP/GDAS; Regressive Skin Split Terra Thermal analysis; and infrared method; radiometer; sea surface temperature; window},
number = 11,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Evaluation of Regressive Analysis Based Sea Surface Temperature Estimation Accuracy with NCEP/GDAS Data}},
url = {http://ijacsa.thesai.org/},
volume = 3,
year = 2012
}