Comparison of ANN and MLR models for estimating solar radiation in Turkey using NOAA/AVHRR data

Sahin M., Kaya Y., Uyar M.

ADVANCES IN SPACE RESEARCH, vol.51, no.5, pp.891-904, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51 Issue: 5
  • Publication Date: 2013
  • Doi Number: 10.1016/j.asr.2012.10.010
  • Page Numbers: pp.891-904
  • Keywords: Solar radiation, Mapping, Land surface temperature, Artificial neural network, Multiple linear regression, NOAA/AVHRR, LAND-SURFACE-TEMPERATURE, ARTIFICIAL NEURAL-NETWORKS, DIFFERENCE VEGETATION INDEX, EMISSIVITY, PARAMETERS, INSOLATION, AREAS


In this paper, the estimation capacities of MLR and ANN are investigated to estimate monthly-average daily SR over Turkey. The satellite data are used for 73 different locations over Turkey. Land surface temperature, altitude, latitude, longitude and month are offered as the input variables for modeling ANN and MLR to get SR. Estimations of SR are evaluated with the meteorological values by using the statistical bases. The obtained results indicated that the ANN model could achieve a satisfactory performance when compared to the MLR model. Moreover, it is understood that more accurate results in estimation of SR are obtained in the use of satellite data, rather than the use of meteorological station data. Finally, the built ANN model is used to estimate the yearly average of daily SR over Turkey. As a result, satellite-based SR map for Turkey is generated. (C) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.