TY - JOUR
T1 - Clear-Sky Longwave Downward Radiation Estimation by Integrating MODIS Data and Ground-Based Measurements
AU - Zhou, Wang
AU - Shi, Jiancheng
AU - Wang, Tianxing
AU - Peng, Bin
AU - Zhao, Rui
AU - Yu, Yuechi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - Surface energy budget has great influence on earth surface biogeophysical and biogeochemical processes. As one of the components of surface energy budget, the longwave downward radiation (LWDR) is essential to many land applications. In this research, a new LWDR estimation scheme under clear sky by integrating MODIS thermal bands radiance and in situ measurements through the multivariate adaptive regression splines (MARS) has been proposed. The MODIS products and corresponding multinetwork in situ LWDR observations under clear skies in 2004 were extracted for model training and cross-validation. The in situ LWDR observations from seven SURFRAD sites in 2008 were used to test the new method. In training phase, the cross-validation RMSE, bias, and R-square of the new method are, respectively, 24.66 W/m 2 , -0.446 W/m 2 , and 0.88 in the daytime and 23.16 W/m 2 , -0.272 W/m 2 , and 0.92 in the nighttime. The test results at the seven SURFRAD sites show that the proposed method has good performance, with RMSE, bias, and R-square of 17.15 W/m 2 , 0.028 W/m 2 , and 0.91 in the daytime and 14.08 W/m 2 , -3.609 W/m 2 , and 0.94 in the nighttime, respectively. More importantly, the error analysis reveals that the predicted residual errors of the proposed method have a weak correlation with related meteorological parameters at global scale, which reflects the stability and robustness of the new method.
AB - Surface energy budget has great influence on earth surface biogeophysical and biogeochemical processes. As one of the components of surface energy budget, the longwave downward radiation (LWDR) is essential to many land applications. In this research, a new LWDR estimation scheme under clear sky by integrating MODIS thermal bands radiance and in situ measurements through the multivariate adaptive regression splines (MARS) has been proposed. The MODIS products and corresponding multinetwork in situ LWDR observations under clear skies in 2004 were extracted for model training and cross-validation. The in situ LWDR observations from seven SURFRAD sites in 2008 were used to test the new method. In training phase, the cross-validation RMSE, bias, and R-square of the new method are, respectively, 24.66 W/m 2 , -0.446 W/m 2 , and 0.88 in the daytime and 23.16 W/m 2 , -0.272 W/m 2 , and 0.92 in the nighttime. The test results at the seven SURFRAD sites show that the proposed method has good performance, with RMSE, bias, and R-square of 17.15 W/m 2 , 0.028 W/m 2 , and 0.91 in the daytime and 14.08 W/m 2 , -3.609 W/m 2 , and 0.94 in the nighttime, respectively. More importantly, the error analysis reveals that the predicted residual errors of the proposed method have a weak correlation with related meteorological parameters at global scale, which reflects the stability and robustness of the new method.
KW - Longwave downward radiation (LWDR)
KW - MODIS
KW - multivariate adaptive regression splines (MARS) method
KW - remote sensing
UR - http://www.scopus.com/inward/record.url?scp=85056725103&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056725103&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2018.2878229
DO - 10.1109/JSTARS.2018.2878229
M3 - Article
AN - SCOPUS:85056725103
SN - 1939-1404
VL - 12
SP - 450
EP - 459
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 2
M1 - 8537963
ER -