Arid
DOI10.1002/joc.3441
Comparative study of statistical and artificial neural network’s methodologies for deriving global solar radiation from NOAA satellite images
Rahimikhoob, A.; Behbahani, S. M. R.; Banihabib, M. E.
通讯作者Rahimikhoob, A.
来源期刊INTERNATIONAL JOURNAL OF CLIMATOLOGY
ISSN0899-8418
EISSN1097-0088
出版年2013
卷号33期号:2页码:480-486
英文摘要

The use of satellite data to estimate global solar radiation (G) at ground level has become an effective way for a large area with high spatial and temporal resolution. The statistical approach is a widely applied procedure for this task. The first objective of this study was to examine the potential of this approach for deriving instantaneous G from NOAAAVHRR satellite data for the atmosphere of semi-arid environment of Iran. The second objective was to apply artificial neural network (ANN) to the estimation of G from advanced very high resolution radiometer (AVHRR) images. A Comparison between these two methods was the last objective of this study. A total of 661 images of NOAAAVHRR level 1b, covering the area of this study were collected from the Satellite Active Archive of NOAA. The results demonstrated that the use of ANN model gave better estimates than the statistical technique. Root mean square error and R2 for the comparison between observed and estimated G for the tested data using the proposed ANN model are 56.95 W m-2 and 0.90, respectively. For the statistical approach method these values are 68.33 W m-2 and 0.86. Copyright (C) 2012 Royal Meteorological Society


英文关键词global solar radiation artificial neural network statistical approach AVHRR data Iran
类型Article
语种英语
国家Iran
收录类别SCI-E
WOS记录号WOS:000313753900017
WOS关键词FEEDFORWARD NETWORKS ; TEMPERATURE ; MODEL ; IRRADIANCE ; VALIDATION ; ALGORITHM
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/177694
作者单位Univ Tehran, Dept Irrigat & Drainage Engn, Tehran, Iran
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Rahimikhoob, A.,Behbahani, S. M. R.,Banihabib, M. E.. Comparative study of statistical and artificial neural network’s methodologies for deriving global solar radiation from NOAA satellite images[J],2013,33(2):480-486.
APA Rahimikhoob, A.,Behbahani, S. M. R.,&Banihabib, M. E..(2013).Comparative study of statistical and artificial neural network’s methodologies for deriving global solar radiation from NOAA satellite images.INTERNATIONAL JOURNAL OF CLIMATOLOGY,33(2),480-486.
MLA Rahimikhoob, A.,et al."Comparative study of statistical and artificial neural network’s methodologies for deriving global solar radiation from NOAA satellite images".INTERNATIONAL JOURNAL OF CLIMATOLOGY 33.2(2013):480-486.
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