Abi Saab, M.T., El Alam, R., Jomaa, I., Skaf, S., Fahed, S., Albrizio, R. & Todorovic, M., 2021,
Coupling Remote Sensing Data and AquaCrop Model for Simulation of Winter Wheat Growth under Rainfed and Irrigated Conditions in a Mediterranean Environment, Agronomy, 11(11), P. 2265, DOI:
10.3390/agronomy11112265.
Ahmadi, S.H., Mosallaeepour, E., Kamgar-Haghighi, A.A. & Sepaskhah, A.R., 2015, Modeling Maize Yield and Soil Water Content with AquaCrop under Full and Deficit Irrigation Managements, Water Resources Management, 29(8), PP. 2837-2853, DOI: 10.1007/s11269-015-0973-3.
Akbari, E., 2020, Remotely Sensed Data Assimilation into Crop Simulation Model for Crop Yield Estimation, PhD. thesis. Tehran university. (in persian).
Akbari, E., 2023, A Review of Remotely Sensed Data Assimilation into Crop Simulation Models, Iranian Journal of Soil and Water Research, 54(5), PP. 753-770, DOI: 10.22059/ ijswr.2023.357472.669478. (in persian).
Akbari, E., Darvishi Boloorani, A., Neysani Samany, N., Hamzeh, S., Soufizadeh, S. & Pignatti, S., 2020a,
Estimating the Spatial-Temporal Distribution of Leaf Area Index Using Sentinel-2 Satellite Images (Case Study: Silage Maize Farms of South of Tehran), Iranian Journal of Irrigation & Drainage, 14(3), PP. 967-980, DOI:
20.1001. 1.20087942.1399.14.3.20.7. (in persian).
Akbari, E., Darvishi Boloorani, A., Neysani Samany, N., Hamzeh, S., Soufizadeh, S. & Pignatti, S., 2020b, Deriving the Leaf Area Index of Silage Maize Using Digital Hemispherical Photography Method (Case Study: Qaleh-Now Farms, South of Tehran), Iranian Journal of Soil and Water Research, 51(6), PP. 1331-1340, DOI: 10.22059/ ijswr.2020.296569.668483. (in persian).
Akbari, E., Boloorani, A.D., Verrelst, J., Pignatti, S., Neysani Samany, N., Soufizadeh, S. & Hamzeh, S., 2023,
Biophysical Variable Retrieval of Silage Maize with Gaussian Process Regression and Hyperparameter Optimization Algorithms, Remote Sensing, 15(14), P. 3690,
https://doi.org/10.3390/ rs15143690.
Akbari, E., Darvishi Boloorani, A., Verrelst, J., Pignatti, S., Neysani Samany, N., Soufizadeh, S. & Hamzeh, S., 2024, How Global Sensitive is the AquaCrop Model to Input Parameters? A Case Study of Silage Maize Yield on a Regional Scale, Frontiers of. Agronomy, 6, P. 1304611, DOI: 10.3389/ fagro.2024.1304611.
Alexandratos, N. & Bruinsma, J., 2012, World Agriculture Towards 2030 /2050: The 2012 Revision.
Badiehneshin, A., Noory, H. & Vazifedoust, M., 2014, Improving Crop Yield Estimation through SWAP Model Using Satellite Data, Iranian Journal of Soil and Water Research, 45(4), PP. 379-388, DOI: 10.22059/ ijswr.2014.52590. (in persian).
Baret, F., Weiss, M., Allard, D., Garrigues, S., Leroy, M., Jeanjean, H., Fernandes, R., Myneni, R., Privette, J., Morisette, J. & Bohbot, H., 2005, VALERI: A Network of Sites and a Methodology for the Validation of Medium Spatial Resolution Land Satellite Products, Remote Sensing of Environment, 76(3), PP. 36-39, https://hal.inrae.fr/hal-03221068.
Busetto, L., Casteleyn, S., Granell, C., Pepe, M., Barbieri, M., Campos-Taberner, M., Casa, R., Collivignarelli, F., Confalonieri, R., Crema, A., García-Haro, F.J., Gatti, L., Gitas, I. Z., Gonz´alez-P´erez, A., Grau-Muedra, G., Guarneri, T., Holecz, F., Katsantonis, D., Minakou, C., Miralles, I., Movedi, E., Nutini, F., Pagani, V., Palombo, A., Di Paola, F., Pascucci, S., Pignatti, S., Stroppiana, D., Rampini, A., Ranghetti, L., Ricciardelli, E., Romano, F., Stavrakoudis, D.G., Viggiano M. & Boschetti, M., 2017,
Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(12), PP. 5423-5441, DOI:
10.1109/ JSTARS.2017.2679159.
Claverie, M., Demarez, V., Duchemin, B., Hagolle, O., Ducrot, D., Marais-Sicre, C., Dejoux, J.F., Huc, M., Keravec, P., Béziat, P. & Fieuzal, R., 2012,
Maize and Sunflower Biomass Estimation in Southwest France Using High Spatial and Temporal Resolution Remote Sensing Data, Remote Sensing of Environment, 124, PP. 844-857, DOI:
10.1016/j.rse.2012.04.005.
Clevers, J., Vonder, O.W., Jongschaap, R. E.E., Desprats, J. F., King, C., Prevot, L. & Bruguier, N., 2002, Using SPOT Data for Calibrating a Wheat Growth Model under Mediterranean Conditions, Agronomie, 22(6), PP. 687-694, DOI: 10.1051/agro:2002038.
Curnel, Y., de Wit, A.J., Duveiller, G. & Defourny, P., 2011,
Potential Performances of Remotely Sensed LAI Assimilation in WOFOST Model Based on an OSS Experiment, Agricultural and Forest Meteorology, 151(12), PP. 1843-1855, DOI:
10.1016/ j.agrformet. 2011.08.002.
Dorigo, W.A., Zurita-Milla, R., de Wit, A.J., Brazile, J., Singh, R. & Schaepman, M.E., 2007,
A Review on Reflective Remote Sensing and Data Assimilation Techniques for Enhanced Agroecosystem Modeling, International Journal of Applied Earth Observation and Geoinformation, 9(2), PP. 165-193, DOI:
10.1016/j.jag.2006.05.003.
ESA, 2005, SPARC 2004, Contract No. 18307/04/NL/FF, SPARC Data Acquisition Report.
Gao, Y., Duan, A., Qiu, X., Sun, J., Zhang, J., Liu, H. & Wang, H., 2010,
Distribution and Use Efficiency of Photosynthetically Active Radiation in Strip Intercropping of Maize and Soybean, Agronomy Journal, 102(4), PP. 1149-1157, DOI:
10.2134/agronj2009.0409.
Hadria, R., Duchemin, B.I., Lahrouni, A., Khabba, S., Er Raki, S., Dedieu, G., Chehbouni,
A. & Olioso, A., 2006,
Monitoring of Irrigated Wheat in a Semi-Arid Climate Using Crop Modelling and Remote Sensing Data: Impact of Satellite Revisit Time Frequency, International Journal of Remote Sensing, 27(6), PP. 1093-1117, DOI:
10.1080/ 01431160500382980.
Hassanli, M., Ebrahimian, H., Mohammadi, E., Rahimi, A. & Shokouhi, A., 2016,
Simulating Maize Yields When Irrigating with Saline Water, Using the AquaCrop, SALTMED, and SWAP Models, Agricultural Water Management, 176, PP. 91-99, Doi:
10.1016/j.agwat.2016.05.003.
Hoefsloot, P., Ines, A.V., van Dam, J., Duveiller, G., Kayitakire, F. & Hansen, J., 2012, Combining Crop Models and Remote Sensing for Yield Prediction: Concepts, Applications and Challenges for Heterogeneous Smallholder Environments, Publications Office of the European Union, 2012, Luxembourg. DOI:10.2788/72447.
Hsiao, T.C., Heng, L., Steduto, P., Rojas-Lara, B., Raes, D. & Fereres, E., 2009,
AquaCrop—the FAO Crop Model to Simulate Yield Response to Water: III. Parameterization and Testing for Maize, Agronomy Journal, 101(3), PP. 448-459, DOI:
10.2134/agronj2008.0218s.
IRIMO [WWW Document], 2019, URL www.irimo.ir (accessed 9.30.21).
Jafari Sayadi, F., 2021, Estimation of Rice Yield Using Satellite Image Integration Algorithms and AquaCrop Model, Thesis of PhD. Sari University of Agricultural Sciences and Natural Resources (in persian).
Jin, X., Kumar, L., Li, Z., Xu, X., Yang, G. & Wang, J., 2016, Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data, Remote Sensing, 8(12), P. 972, 1-15, DOI:10.3390/rs8120972.
Jin, X., Li, Z., Yang, G., Yang, H., Feng, H., Xu, X., Wang, J., Li, X. & Luo, J., 2017,
Winter Wheat Yield Estimation Based on Multi-Source Medium Resolution Optical and Radar Imaging Data and the AquaCrop Model Using the Particle Swarm Optimization Algorithm, ISPRS Journal of Photogrammetry and Remote Sensing, 126, PP. 24-37, DOI:
10.1016/j.isprsjprs.2017. 02.001.
Jin, X., Kumar, L., Li, Z., Feng, H., Xu, X., Yang, G. & Wang, J., 2018,
A Review of Data Assimilation of Remote Sensing and Crop Models, European Journal of Agronomy, 92, PP. 141-152, DOI:
10.1016/ j.eja.2017.11.002.
Launay, M. & Guerif, M., 2005, Assimilating Remote Sensing Data into a Crop Model to Improve Predictive Performance for Spatial Applications, Agriculture, Ecosystems & Environment, 111(1-4), PP. 321-339, DOI: http://dx.doi.org/10.1016/ j.agee.2005.06.005.
Liang, S., Li, X. & Xie, X., 2013, Land Surface Observation, Modeling and Data Assimilation World Scientific, World Scientific Publishing Company, 1st edition.
Liu, J., Pattey, E. & Admiral, S., 2013,
Assessment of in Situ Crop LAI Measurement Using Unidirectional View Digital Photography, Agricultural and Forest Meteorology, 169, PP. 25-34, DOI:
10.1016/j.agrformet.2012.10.009.
Ma, B., Wang, Q., Xue, B., Hou, Z., Jiang, Y. & Cai, W., 2022,
Application of UAV Remote Sensing in Monitoring Water Use Efficiency and Biomass of Cotton Plants Adjacent to Shelterbelt, Frontiers in Plant Science, 13, DOI:
10.3389/fpls.2022.894172.
Morel, J., Martiné, J.-F., Bégué, A., Todoroff, P. & Petit, M., 2012,
A Comparison of Two
Coupling Methods for Improving a Sugarcane Model Yield Estimation with a NDVI Derived Variable, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 8531, PP. 93-102, DOI:
10.1117/ 12.975688.
Morel, J., Bégué, A., Todoroff, P., Martiné, J.F., Lebourgeois, V. & Petit, M., 2014,
Coupling a Sugarcane Crop Model with the Remotely Sensed Time Series of fIPAR to Optimise the Yield Estimation, European Journal of Agronomy, 61, PP. 60-68, DOI:
10.1016/j.eja.2014.08.004.
Munz, S., Feike, T., Chen, Q., Claupein, W. & Graeff-Hönninger, S., 2014,
Understanding Interactions between Cropping Pattern, Maize Cultivar and the Local Environment in Strip-Intercropping Systems, Agricultural and Forest Meteorology, 195, PP. 152-164, DOI:
10.1016/j.agrformet.2014.05.009.
Prescott, J.A., 1940, Evaporation from Water Surface in Relation to Solar Radiation, Transactions of The Royal Society of South Australia, 40, PP. 114-118.
Quaife, T., Lewis, P., De Kauwe, M., Williams, M., Law, B.E., Disney, M. & Bowyer, P., 2008,
Assimilating Canopy Reflectance into an Ecosystem Model with an Ensemble Kalman Filter, Remote Sensing Environment, 112, PP. 1347-1364, DOI:
10.1016/j.rse.2007.05.020.
Raes, D., 2017, AquaCrop Training Handbook I. Understanding AquaCrop, Food and Agriculture Organization of the United Nations, Rome, Italy.
Raes, D., Steduto, P., Hsiao, T.C. & Fereres, E., 2016, AquaCrop Version 5.0 Reference Manual, Annex I. Food and Agriculture Organization of the United Nations, Rome, Italy, http://www.fao.org/land-water/ databases- and-software/AquaCrop/en/.
Raes, D., Steduto, P., Hsiao, T.C. & Fereres, E., 2017, AquaCrop. FAO Crop – Water Productivity Model to Simulate Yield Response to Water, Reference Manual, Ver. 6, FAO, Land and Water Division, Rome, Italy.
Razzaghi, F., Zhou, Z., Andersen, M.N. & Plauborg, F., 2017,
Simulation of Potato Yield in Temperate Condition by the AquaCrop Model, Agricultural Water Management, 191, PP. 113-123, DOI:
10.1016/j.agwat.2017. 06.008.
Richter, K., Atzberger, C., Hank, T.B. & Mauser, W., 2012,
Derivation of Biophysical Variables from Earth Observation Data: Validation and Statistical Measures, Journal of Applied Remote Sensing, 6(1), PP. 063557-063557, DOI:
10.1117/1.JRS.6.063557.
Sadooghi, L., Homaee, M., Noroozi, A. & Asadi Kapourchal, S., 2017,
Estimating Rice Yield Using VSM Model and Satellite Images in Guilan Province, Cereal Research, 6(3), PP. 397-410, DOI:
20.1001.1.22520163.1395.6.3. 10.2. (in persian).
Silvestro, P.C., Pignatti, S., Pascucci, S., Yang, H., Li, Zh., Yang, G., Huang, W. & Casa, R., 2017,
Estimating Wheat Yield in China at the Field and District Scale from the Assimilation of Satellite Data into the Aquacrop and Simple Algorithm for Yield (SAFY) Models, Remote Sensing, 9(5), P. 509, DOI:
10.3390/rs9050509.
Steduto, P., Hsiao, T.C., Raes, D. & Fereres, E., 2009,
AquaCrop—The FAO Crop Model to Simulate Yield Response to Water: I. Concepts and Underlying Principles, Agronomy Journal, 101(3), PP. 426-437, DOI:
10.2134/agronj2008.0139s.
Thorp, K.R., Hunsaker, D.J. & French, A.N., 2010,
Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model, Transactions of the ASABE, 53(1), PP. 251–262, DOI:
10.13031/2013.29490.
Tripathy, R., Chaudhari, K.N., Mukherjee, J., Ray, S.S., Patel, N., Panigrahy, S. & Parihar,
J.S., 2013,
Forecasting Wheat Yield in Punjab State of India by Combining Crop Simulation Model WOFOST and Remotely Sensed Inputs, Remote Sensing Letters, 4(1), PP. 19-28, DOI:
10.1080/ 2150704X.2012.683117.
Vanuytrecht, E., Raes, D. & Willems, P., 2014,
Global Sensitivity Analysis of Yield Output from the Water Productivity Model, Environmental Modelling & Software, 51, PP. 323-332, DOI:
10.1016/j.envsoft.2013. 10.017.
Vazifedoust, M., Van Dam, J.C., Bastiaanssen, W.G.M. & Feddes, R.A., 2009,
Assimilation of Satellite Data into Agrohydrological Models to Improve Crop Yield Forecasts, International Journal of Remote Sensing, 30(10), PP. 2523-2545, DOI:
10.1080/ 01431160802552769. (in persian).
Wösten, J.H.M. , Pachepsky, Y.A. & Rawls, W.J., 2001,
Pedotransfer Functions: Bridging the Gap between Available Basic Soil Data and Missing Soil Hydraulic Characteristics, Journal of Hydrology, 251(3-4), PP. 123-150. DOI :
10.1016/S0022-1694(01)00464-4.
Xia, T., Miao, Y., Wu, D., Shao, H., Khosla, R. & Mi, G., 2016,
Active Optical Sensing of Spring Maize for in-Season Diagnosis of Nitrogen Status Based on Nitrogen Nutrition Index, Remote Sensing, 8(7), P. 605, DOI:
10.3390/rs8070605.
Yao, F., Tang, Y., Wang, P. & Zhang, J., 2015,
Estimation of Maize Yield by Using a Process Based Model and Remote Sensing Data in the Northeast China Plain, Physics Chemistry Earth Parts A/B/C, 87, PP. 142-152, DOI:
10.1016/j.pce.2015.08.010
)