共 22 条
REMOTELY SENSED CLEAR-SKY SURFACE LONGWAVE DOWNWARD RADIATION BY USING MULTIVARIATE ADAPTIVE REGRESSION SPLINES METHOD
被引:0
作者:
Zhou, Wang
[1
,4
]
Wang, Tianxing
[1
]
Shi, Jiancheng
[1
]
Peng, Bin
[2
,3
]
Zhao, Rui
[1
,5
]
Yu, Yuechi
[1
,4
]
机构:
[1] Inst Remote Sensing & Digital Earth Chinese Acad, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[2] Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA
[3] Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL 61801 USA
[4] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[5] Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130000, Jilin, Peoples R China
来源:
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
|
2018年
关键词:
longwave downward radiation;
MODIS;
multivariate adaptive regression splines;
remote sensing;
NETWORK;
CLOUD;
MODEL;
D O I:
暂无
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
Surface radiation balance plays a vital role in the earth surface system and affects many biogeophysical processes. As one of components of surface energy balance, longwave downward radiation (LWDR) is considered as the most poorly estimated radiation component, and its uncertainty is regarded as substantially larger than other terms of surface energy budget. In this paper, we applied the multivariate adaptive regression splines (MARS) method to derive LWDR based on MODIS thermal infrared bands top of atmosphere radiances and ground-based LWDR measurements. In model fitting process, the RMSE, bias and R-square value are 25.49 W/m(2), -0.000 W/m(2) and 0.88, respectively; and in model validation stage, the RMSE, bias and R-square value are 25.63 W/m(2), 0.481 W/m(2) and 0.87, respectively. The newly proposed model demonstrates comparable accuracy with other LWDR estimating methods and proves that MARS method is very useful in remote sensing based LWDR estimation.
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页码:5571 / 5574
页数:4
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