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http://dx.doi.org/10.5467/JKESS.2017.38.4.269

Calculation of Surface Broadband Emissivity by Multiple Linear Regression Model  

Jo, Eun-Su (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Lee, Kyu-Tae (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Jung, Hyun-Seok (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Kim, Bu-Yo (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Zo, Il-Sung (Research Institute for Radiation-Satellite, Gangneung-Wonju National University)
Publication Information
Journal of the Korean earth science society / v.38, no.4, 2017 , pp. 269-282 More about this Journal
Abstract
In this study, the surface broadband emissivity ($3.0-14.0{\mu}m$) was calculated using the multiple linear regression model with narrow bands (channels 29, 30, and 31) emissivity data of the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System Terra satellite. The 307 types of spectral emissivity data (123 soil types, 32 vegetation types, 19 types of water bodies, 43 manmade materials, and 90 rock) with MODIS University of California Santa Barbara emissivity library and Advanced Spaceborne Thermal Emission & Reflection Radiometer spectral library were used as the spectral emissivity data for the derivation and verification of the multiple linear regression model. The derived determination coefficient ($R^2$) of multiple linear regression model had a high value of 0.95 (p<0.001) and the root mean square error between these model calculated and theoretical broadband emissivities was 0.0070. The surface broadband emissivity from our multiple linear regression model was comparable with that by Wang et al. (2005). The root mean square error between surface broadband emissivities calculated by models in this study and by Wang et al. (2005) during January was 0.0054 in Asia, Africa, and Oceania regions. The minimum and maximum differences of surface broadband emissivities between two model results were 0.0027 and 0.0067 respectively. The similar statistical results were also derived for August. The surface broadband emissivities by our multiple linear regression model could thus be acceptable. However, the various regression models according to different land covers need be applied for the more accurate calculation of the surface broadband emissivities.
Keywords
surface broadband emissivity; narrowband emissivity; multiple linear regression model; spectral emissivity;
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Times Cited By KSCI : 3  (Citation Analysis)
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