Aliabadi K., Entezari A. R. and Eskandari N. (2014). Estimation of physical parameters (biomass) of vegetation using remote sensing data. J. Arid. Region. Geographic Studies., 4(15), 23-33 [In Persian].
Anonymous. (2019). Agricultural Statistics (Volume I – Crops). Ministry of Agriculture-Jahad. Available on:
https://www.maj.ir. [In Persian].
Asadi Kapourchal S., Homaee M. and Pazira E. (2013). Modeling leaching requirement for desalinization of saline soils. J. Water Soil Resour. Conserv., 2(2), 65-83 [In Persian].
Bao Y., Gao, W. and Gao Z. (2009). Estimation of winter wheat biomass based on remote sensing data at various spatial and spectral resolution. Front Earth Sci., 3(1), 118-128.
Chen R. K. and Yang C. M. (2005). Determining the optimal timing for using LAI and NDVI to predict rice yield. J. Photogramm. Remot. Sens., 10(3), 239-254.
Ebrahimi Rad H., Babazadeh H., Amiri E. and Sedghi H. (2018). Effect of irrigation management and planting density on yield and water productivity of rice (Hashemi Cultivar). J wat. Res. Agr., 31(4), 625-636 [In Persian].
Gee G. W. and Bauder J. W. (1986). Particle size analysis. In: Klute A (Ed.), Methods of soil analysis. Part 1. Physical and mineralogical methods, Agron, 2nd (ed.), Madison, WI, pp 404–408.
Grossman R. and Reinsch B. T. G. (2002). Bulk Density. In: Dane J. H. and Topp G. C., Methods of soil analysis. physical methods, soil science society of America, Inc, Madison, Wisconsin, USA, Part 4.
Kunnath-Poovakka A., Ryu D., Renzullo L. J. and George B. (2016). The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction. J. Hydrol., 535, 509-524.
Ma Y., Feng S., Huo Z. and Song X. (2011). Application of the SWAP model to simulate the field water cycle under deficit irrigation in Beijing, China. Math. Comput. Model., 54(3-4), 1044-1052.
Machado S. E. D., Bynum J., Archer T. L., Lascano R. J., Wilson L. T. Bordovsky J., Segarra E., Bronson K., Nesmith D. M. and Xu W. (2002). Spatial and temporal variability of corn growth and grain yield: Implication for sitespecific farming. J. Crop Sci., 42, 1564-1576.
Mohanty B. P. (2013). Soil hydraulic property estimation using remote sensing: a review. Vadose Zone J., 12 (4), 1-9.
Nuarsa I. W., Nishio F. and Hongo C. (2012). Rice yield estimation using Landsat ETM+ data and field observation. J. Agr. Sci., 4(3), 45-56.
Page A. L., Miller R. H. and Keeney D. R. (1982): Methods of soil analysis; 2. Chemical and microbiological properties, 2. Aufl. 1184 S., Am. Soc. Agronomy (Publ.), Madison, Wisconsin, USA.
Pettorelli N., Vik O., Mysterud A., Gaillard J. M., Tucker C. J. and Stenseth N. C. (2005). Using the satellite derived NDVI to assess ecological responses to environmental change. Trend. Ecol Evol., 20(9), 503-510.
Raeini-Sarjaz M. and Rostami A. (2016). Remotely sensed measurements of apple orchard actual evapotranspiration and plant coefficient using MODIS images and SEBAL algorithm (Case study: Ahar plain, Iran). Scientific J. Agr. Meteorol., 4(1), 32-43 [In Persian].
Rezaei M., Raeini Sarjaz ., Shahnazari A. and Vazifedoust M. (2014). Estimation of paddy field rice yield in the Sephidrud system using Landsat images (case study : Some Sara). Iranian J. Irrig. Drain., 8(3), 591-601[In Persian].
Rezaei M. (2015). The effects of different irrigation applied water on water productivity at large scale using satellite data and DSSAT model assimilation. PhD dissertation, Sari Agricultural Sciences and Natural Resources University, Sari, Iran. 168 pp. [In Persian].
Rezaei M., Shahnazari A., Raeini sarjaz M. and Vazifedoust M. (2016). Improving agricultural management in a large-scale paddy field by using remotely sensing data in the CERES-Rice model. Irrig. Drain., 65, 224-228.
Sadooghi L., Homaee M., Noroozi A. A. and Asadi Kapourchal S. (2016). Estimating rice yield using VSM model and satellite images in Guilan province. Cereal Res., 6(3), 397- 410 [In Persian].
Sarker R. L. and Nichol J. E. (2011). Improved Forest estimates using ALOSAVNIR- 2 Texture indices. Remote Sens. Environ.,115(4), 968-977.
Serrano L., Filella I. and Penuelas J. (2000). Remote Sensing of Biomass and Yield of Winter Wheat under Different Nitrogen Supplies. Crop Sci., 40(3), 723-731.
Siyal A. A., Dempewolf J. and Becker-Reshef I. (2015). Rice yield estimation using Landsat ETM+ Data. J. Appl. Remot. Sens., 9, 1-16.
Son N.T., Chen C.F., Chen C.R., Minh V.Q. and Trung N.H. (2014). A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation. Agri. Forest Meteorol., 197, 52-64.
Thenkabail P., Smith R. B. and Pauw E. D. (2002). Evaluation of narrow band and broad band vegetation indices for determining optimal hyperspectral wave bands for agricultural crop characterization. Photogramm. Eng. Rem. S., 68(6), 607–621.
Van Lier Q. J., Wendroth O. and van Dam J. C. (2015). Prediction of winter wheat yield with the SWAP model using pedotransfer functions: An evaluation of sensitivity, parameterization and prediction accuracy. Agr. Wat. Manag., 154, 29-42.
Walkly A. and Black J. A. (1934). An examination of digestion method for determiningsoil organic matter and proposed modification of the chromic acid titration. Soil Sci., 37, 29-38.
Wei-guo L., Hua L. and Li-hua Z. (2011). Estimating Rice Yield by HJ-1A Satellite Images. Rice Sci., 18(2), 142-147.
Xie X. and Zhang D. (2010). Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter. Adv. Water Resour., 33, 678–690.
Yaghouti H., Pazira E., Amiri E. and Masihabadi M. H. (2018). Application of satellite imagery and remote sensing technology to estimate rice yield. J. Water Soil Resour. Conserv., 7(3), 55-69 [In Persian].
Zare Abyaneh H., Farokhi E., Vazifeh Doost M. and Azhdari K. (2011). Evaluation of the SWAP model to estimate the distribution pattern of soil moisture under drip irrigation management. J. Water and Soil. 24(6), 1197-1209 [In Persian].
Zhou Y., Zhang Y., Vaze J., Lane P. and Xu S. (2013). Improving runoff estimates using remote sensing vegetation data for bushfire impacted catchments. Agr. Forest Meteorol., 182–183, 332–341.