Modeling MODIS LAI time series using stochastic approach

Document Type : Research Article


Assistant Professor, Faculty of Agriculture, Azarbaijan Shahid Madani University, Tabriz, Iran


Leaf area index is one of the most important variables characterizing energy flux, atmosphere- land surface exchange and vegetation structure. In this research, Leaf area index time series of wheat, alfalfa, apple and potato have been investigated using the modeling based on Box-Jenkins method, and  the result of mathematical relationships between leaf area index and NDVI were compared. The trend of MODIS time series in the period of 2012 to 2015 with seasonal length of 46 using seasonal Man –Kendall test was negative. The simulation of time series using ARIMA (p,0,q)×(P,1,Q)46indicated the decease in  error and correlation and NASH coefficient; for example, the correlation coefficients of wheat, alfalfa, apple and potato were 0.9, 0.94,0.93 and 0.89, respectively. The criteria comparison demonstrated the better performance of SARIMA model especially for alfalfa and apple time series with high values of leaf area index. Stochastic modeling has minimum error relative to the mathematical relationships. According to the high performance of SARIMA model, preparation of leaf area index time series with high precision is more important.


Main Subjects

[1].        Zarate-Valdez JL, Whiting ML, Lampinen BD, Metcalf S, Ustin SL, Brown PH. Prediction of leaf area index in almonds by vegetation indexes. Comput Electron Agric. 2012; 85:24–32.
[2].        Shen L, Li Z, Guo X. Remote Sensing of Leaf Area Index (LAI) and a Spatiotemporally Parameterized Model for Mixed Grasslands. Int J App Sci Technol. 2014; 4(1):46-61.
[3].        Fang s, Le Y, Liang Q, Liu X. Leaf Area Index Estimation Using Time-Series MODIS Data in Different Types of Vegetation. J Indian Soc Remote Sens. 2014; 42(4):733–743.
[4].        Jonckheere I, Fleck S, Nackaerts K, Muys B, Coppin P, Weiss M, Baret F. Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agr Forest Meteorol. 2004; 121:19–35.
[5].        Jiang B, Liang S, Wang J, Xiao Z. Modeling MODIS LAI time series using three statistical methods. Remote Sens Environ. 2010; 114(7):1432-1444.
[6].        Xiao Z, Liang S,  WangJ, Jiang B, LiX. Real-time retrieval of Leaf Area Index from MODIS time series data. Remote Sens Environ. 2011; 115(1):97-106.
[7].         Fernandez-manso A, Fernández-Manso O. Forecast of NDVI in coniferous areas using temporal ARIMA analysis and climatic data at a regional scale.Int J Remote Sens . 2011; 32(6):1595-1617.
[8].        Movahedian M, Hosseini SE, Ghorbanzadeh M. Estimation of Leaf Area Index using neural network. 3rd International Conference on Information and Knowledge Technology, Ferdowsi University of Mashhad. 2007.
[9].        Parviz L. Investigation and modification land surface hydrological model for stream flow forecasting (in short term scale). MSc. Thesis in Water Resource Management, Tehran University. 2011.
[10].    Trombettaa A, Iacobellis V, Tarantinob E, Gentile F. Calibration of the AquaCrop model for winter wheat using MODIS LAI images. Agric Water Manage. 2016; 164(2):304-316.
[11].    Karamouz M, Araghinejad S, Advanced hydrology. 2nd ed. Amirkabir University of Technology. 2006. P. 464.
[12].    Malmir M. Low streamflow time series forecasting. MSc. Thesis in Water Resource Management, Tehran University. 2006.
[13].    Bahmani R, Radmanesh F, Eslamian SS, Parham G. Reservoir evaporation trend analysis and its prediction using time series. J Irrigation SciEngin. 2014; 36(2):67-80.
[14].    Bakhshandeh E, Soltani A, Ghadiryan R. Leaf area measurement by AccuPAR instrument in wheat. J Plant Prod. 2010; 18(4):97-101.
[15].    Su F, Hong Y, Lettenmaier DP. Evaluation of TRMMMultisatellite Precipitation Analysis (TMPA) and Its Utility in Hydrologic Prediction in the La Plata Basin. J Hydrometeorol. 2007; 9:622- 640.
[16].    Yang G, Bowling LC, CherkauerK.A, Pijanowski BC, Niyogi D. Hydroclimatic response of watersheds to urban intensity: An observational and modeling-based analysis for the White River Basin, Indiana. J Hydrometeorol. 2009; 11:122-138.
[17].    Xu X, Du H, Zhou G, Li P. Method for improvement of MODIS leaf area index products based on pixel-to-pixel correlations. European J Remote Sens. 2016; 49:57-72.