Estimation of Solar Radiation Using Land Surface Temperature MODIS Sensor Data and Neural Network Model

Document Type : Research Article

Authors

• S. Emamifar
• A. Alizadeh

Ferdowsi University of Mashhad

https://doi.org/10.22067/jsw.v0i0.39508

Abstract

Estimation the amount of radiation reaching the Earth's surface (Rs) is an important factor in the energy balance models simulation of plant growth and evapotranspiration estimation. Most Estimation models to radiation reaching the Earth's surface use satellite data and they are based on land surface temperatures. In this study, the Accuracy of solar radiation estimation is investigated Using four different models of neural networks (with the names of ANN1,ANN2, ANN3, ANN4) with the inputs Including products land surface temperature MODIS sensor (models 1 and 2 , and models 3 and 4 are based on MOD11A1 MYD11A1 products, respectively), extraterrestrial radiation (Ra) and relative sunshine (n / N). The results show that four neural network models are able to estimate the amount of radiation reaching the Earth's surface with good correlation (R2>. 85). However, models based on MOD11A1 products have a higher accuracy than models based on MYD11A1 products. Neural network model of ANN1 (based on MOD11A1 products, relative sunshine and extraterrestrial radiation (Ra)) with the coefficient of determination (R2) equal to .9332 and the root mean square error (RMSE) equal to 1.4448 MJ per square meter per day is more accurate on the estimation of solar radiation than other models. The results also showed that the Neural network model ANN2, comparing with Hargreaves and Samani models based on air temperature and extraterrestrial radiation, is More accurate in estimating of solar radiation.

Keywords

• Solar radiation
• MODIS sensors
• Land surface temperature
• Neural network model

20.1001.1.20084757.1393.28.3.17.7

References

1- رحیمی خوب ع.، صابری پ.، بهبهانی س.م.ر. و نظری فر م.ه. 1389. برآورد تابش خورشید رسیده به سطح زمین با استفاده از تصاویر ماهواره نوا و روابط آماری در جنوب شرق تهران. مجله علوم وفنون کشاورزی و منابع طبیعی، علوم آب وخاک. سال پانزدهم. شماره پنجاه و ششم

2- منهاج م.ب. 1379.هوش محاسباتی (مبانی شبکه های عصبی). جلد اول، انتشارات دانشگاه پلی تکنیک. 715ص

3- Allen R.G., Pereira L.S., Raes D. and Smith M. 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. Irrigation and Drainage Paper No.56. FAO, Rome.

4- Almorox J. and Hontoria C. 2004. Global solar radiation estimation using sunshine duration in Spain. Energy Convers. Manag.45: 1529-1535.

5- Angstrom A.K. 1924. Solar and terrestrial radiation. Quarterly Journal of Royal Meteorological Society,50:121-125.

6- Belcher B.N. and DeGaetano A.T. 2007. A revised empirical model to estimate solar radiation using automated.

7- Coll C., Caselles V., Sobrino J.A. and Valor E. 1994. On the atmospheric dependence of the split-window equation for land surface temperature. International Journal of Remote Sensing; 15: 102-105.

8- Emamifar S., Rahimikhoob A. and Noroozi A.A. 2013. Daily mean air temperature estimation from MODIS landsurface temperature products based on M5 model tree. International Journal of Climatology.

9- Hargreaves, G.H. 1994. Simplified coefficients for estimating monthly solar radiation in North America and Europe. Departmental Paper, Dept. of Biol. and Irrig. Eng., Utah State Univ., Logan, Utah.

10- Hargreaves, G. H. and Z. A. Samani. 1998. Estimating potential evapotranspiration. J. Irrig. D. Eng. 108: 230-225.

11- Iziomon, M.G. and Mayer H. 2002. Assessment of some global solar radiatio parameterizations. 64(2): 1631-1643.

12- Ozan S¸ enkal.2010. Modeling of solar radiation using remote sensing and arti ficial neural network in Turkey. Energy. 35: 4795-4801.

13- Peter E.T. and Steven W.R. 1999. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity and precipitation. Agric. Forest Meteorol. 3: 211-228.

14- Qin J., Chen Z., Yang K., Liang S. and Tang W. 2011. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products. Appl. Energy 88, 2480-2489.

15- Rahimikhoob A. 2010. Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment. Renew. Energy. 35, 2131-2135.

16- Samani Z. 2000. Estimation solar radiation and evapotranspiration using minimum climatological data. J. Irrig. Drain. Eng. 126(4): 265-267.

17- Shengpan L., Nathan J., Moore Joseph P. Messina Mark H., DeVisser Jiaping W. 2012. Evaluation of estimating daily maximum and minimum air temperature with MODIS data in east Africa. International Journal of Applied Earth Observation and Geoinformation 18: 128–140.

18- Vancutsem C., Ceccato P., Dinku T., Connor S.J. 2010. Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sens. Environ. 114 (2), 449–465.

19- Wan Z. 1999. MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD), Version 3.3, NASA contract NAS 3137-5 (Institute for Computational Earth System Science)

20- Wan Z.M., Zhang Y.L., Zhang Q.C., and Li Z.L. 2002. Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectro-radiometer data. Remote Sensing of Environment, 83 (1-2), 163-180.

21- Yan H., Zhang J.H., Hou Y.Y. and He Y.B. 2009. Estimation of air temperature from MODIS data in east China. Int. J. Remote Sens. 30 (23), 6261–6275.