[1]. Alizamir, M., Kisi, O., Ahmed, A., Mert, C., Fai, C., Kim, S., & El-Shafie, A. (2020). Advanced machine learning model for better prediction accuracy of soil temperature at different depths. Plos One, 15(4), e0231055.
[2]. Amir Moradi, K., & Bahmani, O. (2014). Prediction of Daily Soil Temperatures with Artificial Neural Network. Soil Research, 28(3), 543-556. (in Farsi)
[3]. Amini, F. Z., Ghorbani, M. A., & Darbandi, S. (2014). Evaluation of Genetic Programming in Estimation of Soil Temperature, Geographic Space, 4(47), 19-38. (in Farsi)
[4]. Araghi, A., Mousavi‐Baygi, M. Adamowski, J. Martinez, C. & VanderPloeg, M. (2017). Forecasting soil temperature based on surface air temperature using a wavelet artificial neural network. Meteorological Applications, 24(4), 603-611.
[5]. Asakereh, H., & Sayadi, F. (2017). Analysis and Forecasting Drought Days Using Artificial Neural Networks Model (Case Study: Station Tehran). Geography and Planning, 21(60), 161-167. (in Farsi)
[6]. Baaghideh, M., Entezari, A., & Kordi, A. (2019). Investigation of the Relationship between Soil Temperature and Climate Parameters in the Northwest of Iran (1992-2015). Geography and Regional Development, 16(1), 307-279.
[7]. Becker, F., & Li, Z. (1990). Towards a local split window method over land surfaces. Remote Sensing. 11, 369–393.
[8]. Behyar, M., & Kamali, G. (2001). Projection of minimum soil temperature and frost and frost control methods in Chaharmahal Bakhtiari province, Meteorological and Baroque Research Institute 3(23), 81-102. (in Farsi)
[9]. Carlson, T., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index, Remote Sensing of Environment, 62, 241-252.
[10].Chander, G., Markham, B., & Helder, D. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM +, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5), 893-903
[11].Chedin, A., Scott, N., & Berroir, A. (1982). A single-channel, double-viewing angle method for sea surface temperature determination from coincident Meteosat and TIROS-N radiometric measurements‚ Applied Meteorology, 4(21) ‚ 613-618.
[12].Dymond, J., Stephens, P., & Newsome, P (1992). Percentage vegetation cover of a degrading rangeland from SPOT. Remote Sensing. 13, 1999–2007.
[13].Ebrahimi Heravi, B., Rangzan, K., Riahi Bakhtiari, H., & Taghizadeh, A. (2015). Determination of urban surface temperature using LandSat images (Case study: Karaj). RS and GIS for Natural Resources, 6(2), 19-32. (in Farsi)
[14].Fangueiro, D., Kidd, P.S., Alvarenga, P., Beesley, L., & Varennes, A. (2018). Chapter 10 Strategies for Soil Protection and Remediation, in: “Soil Pollution: From Monitoring to Remediation”, Edited by: Duarte, A.C., Cachada, A. and Rocha-Santos, T.A.P. Elsevier. 251–281.
[15].Feng, Y., Cui, N., Hao, W., Gao, L., & Gong, D. (2019). Estimation of soil temperature from meteorological data using different machine learning models. Geoderma, 338, 67-77
[16].Gao, Z., Bian, L., Hu, Y., Wang, L., & Fan, J. (2007). Determination of soil temperature in an arid region, Arid Environments. 71, 157-168.
[17].García-Santos, V., Cuxart, J., Martínez-Villagrasa, D., Jiménez, M.A., & Simó, G, (2018). Comparison of Three Methods for Estimating Land Surface Temperature from Landsat 8-TIRS Sensor Data. Remote Sensing. 10, 1450.
[18].Ghuman, B.S., & Lal, R. (1982). temperature regime of a tropical soil in relation to surface condition and air temperature and its Fourier analysis, Soil Science, 134, 133-140.
[19].Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J.S., Hook, S., & Kahle, A.B. (1998). A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images‚ IEEE transactions on geoscience and remote sensing, 4(36)‚ 1113- 1126.
[20].Hagan, MT., & Menhaj, MB. (1994). Training feedforward network with the Marquardt algorithm. IEEE Trans on Neural Networks. 5, 989-993
[21].Harrison-murray, R., & Lal, R. (1979). High soil temperatures and response of maize to mulching in the lowland humid tropics. In: Greenland, D.J., Lal, R. (Eds), Soil Conservation and Management in the Humid Tropics. Wiley, New York.
[22].Hook, S., Gabell, A., Green, A., & Kealy, P. (1992). A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies‚ Remote sensing of Environment, 2(42)‚ 123-135.
[23]. https://earthexplorer.usgs.gov/.
[24].Huang, R., Huang, J. X., Zhang, C., Wen, Z., Chen, Y., Zhu, D., & Mansaray, L. (2020). Soil temperature estimation at different depths, using remotely-sensed data. Integrative Agriculture, 19(1), 277-290.
[25].Jiménez-Muñoz, J., & Sobrino, J. (2010). Split-Window Coefficients for Land Surface Temperature retrieval from Low-Resolution Thermal Infrared Sensors, IEEE Geoscience and Remote Sensing Letters, 5, 806–809.
[26].Jiménez-Muñoz, J., Sobrino, J., Jiménez, D., Mattar, C., & Cristóbal, J. (2014). Land Surface Temperature Retrieval Methods from Landsat-8 Thermal Infrared Sensor Data. IEEE Geoscience and Remote Sensing Letters, 11, 1840–1843.
[27].Jouybari, Y., Moghaddam, M., Akhoondzadeh, M., & Saradjian, R. (2015). A Split-Window Algorithm for Estimating LST from Landsat-8 Satellite Images. Geomatics Science and Technology. 5(1), 215-226. (in Farsi)
[28].Khoshhal dastjerdi, J., & Hosseini, S. (2010). Application of Artificial Neural Network in Climatic Elements Simulation and Drought Cycle Predication (Case Study: Isfahan Province). Geography and Environmental Planning, 21(3), 107-120. (in Farsi)
[29].Kisi, O., Tombul, M., & Kermani, M. (2015). Modeling soil temperatures at different depths by using three different neural computing techniques. Theoretical and applied climatology, 121(1-2), 377-387.
[30].Kuenzer, C., & Dech, S. (2013). Thermal Infrared Remote Sensing, Sensord, Methods, Applications, 17. Springer, 546.
[31].Li, Q., Hao, H., Zhao, Y., Geng, Q., Liu, G., Zhang, Y., & Yu, F. (2020). GANs-LSTM model for soil temperature estimation from meteorological: A new approach. IEEE Access.
[32].Li, Z.-L., Tang, B.-H., Wu, H., Ren, H., Yan, G., Wan, Z., Sobrino, J. A. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing of Environment, 131, 14-37.
[33].Ma, X.L., Wan, Z., Moeller, C., Menzel, W.P., & Gumley, L.E. (2002). Simultaneous retrieval of atmospheric profiles, land- surface temperature and surface emissivity from moderate-resolution imaging spectroradiometer thermal infrared data: Extension of a two-step physical algorithm‚ Applied Optics, 5(41) ‚ 909-924.
[34]. Mamdani, E.H., & Assilian, S., (1975). An experiment in linguistic synthesis with a fuzzy logic controller. Man-Machine Studies, 7(1), 1-13.
[35].Masiello, G., Serio, C., De Feis, I., Amoroso, M., Venafra, S., Trigo, I., & Watts, P. (2013). Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances‚ Atmospheric Measurement Techniques, 12(6), 3613-3634.
[36].Mazidi, A., & Falahzade, F. (2010). Annual soil temperature trend at Yazd station, geography and development, 24, 39-50. (in Farsi)
[37].McMillin, L. M. (1975). Estimation of sea surface temperatures from two infrared window measurements with different absorption. Geophysical Research, 80(36), 5113-5117.
[38].Nafaji mod, M., Alizade, A., Mohamadian, A., & Mosavi, j. (2009). Investigation of relationship between air and soil temperature at different depths and estimation of the freezing depth (Case study: Khorasan Razavi). Water and Soil, 22(2), 456-466. (in Farsi)
[39].Nayak, P.C., Sudheer, K.P., Rangan, D.M., & Ramasatri, K.S. (2004). A neuro-fuzzy computing technique for modeling hydrological time series. Hydrology, 291, 52-66.
[40].Neinavaz, E., Skidmore, A. K., & Darvishzadeh, R. (2020). Effects of prediction accuracy of the proportion of vegetation cover on land surface emissivity and temperature using the NDVI threshold method. Applied Earth Observation and Geoinformation, 85, 1-13.
[41].Neteler, M. (2010). Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data. Remote Sensing, 2(1), 333-351.
[42].Parsafar, N., & Marofi, S. (2011). Estimation of Soil Temperature from Air Temperature Using Regression Models, Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System (Case Study: Kermanshah Region). Water and Soil Science, 21(3), 139-152. (in Farsi)
[43].Sabziparvar, A., Zare-Abyaneh, H., & Bayat-Varkeshi, M. (2010). A model Comparison between Predicted Soil Temperatures Using ANFIS Model and Regression Methods in Three Different Climates. Water and Soil, 24(2), 274-285. (in Farsi)
[44].Salih, M., Jasim, O., Hassoon, K., & Abdalkadhum, A. (2018). Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera. International Engineering & Technology, 7(4.20), 608-612.
[45].Shati, F., Prakash, S., Norouzi, H., & Blake, R. (2018). Assessment of differences between near-surface air and soil temperatures for reliable detection of high-latitude freeze and thaw states. Cold Regions Science and Technology, 145, 86-92.
[46].Singh, V.K., Singh, B.P., Kisi, O., & Kushwaha, D.P. (2018). Spatial and multi-depth temporal soil temperature assessment by assimilating satellite imagery, artificial intelligence and regression-based models in arid area. Computers and Electronics in Agriculture, 150, 205-219.
[47].Sobrino, J., Li, Z., Stoll, M., & Becker, F. (1996). Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data. Remote Sensing, 17(11), 2089-2114.
[48].Sun, D., & Pinker, R. (2007). Retrieval of surface temperature from the MSG‐ SEVIRI observations: Part I. Methodology‚ Remote Sensing, 23(28)‚ 5255- 5272.
[49].Talaee, P. H. (2014). Daily soil temperature modeling using neuro-fuzzy approach. Theoretical and applied climatology, 118(3), 481-489.
[50].Tiba, C. H., & Raquel, G. (2006), Numerical Procedure for Estimating Temperature in Solarized Soils, Pesquisa Agropecuária Brasileira, 3, 533 – 537.
[51].Van Wambeke, A., (1992). Soils of the Tropics, Properties and Appraisal. Donnelley and Sons, Mexico.
[52].Veysi, S., Naseri, A., Hamzeh, S., & Moradi, P. (2016). Estimation of sugarcane field temperature using Split Window Algorithm and OLI LandSat 8 satellite images. RS and GIS for Natural Resources, 7(1), 27-40. (in Farsi)
[53].Vlassova, L., Perez-Cabello, F., Nieto, H., Martín, P., Riaño, D., & Riva, J. (2014). Assessment of methods for land surface temperature retrieval from Landsat-5 TM images applicable to multiscale tree-grass ecosystem modeling. Remote Sensing, 6(5), 4345-4368.
[54].Wan‚ Z., & Li, Z.L., (1997). A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data‚ IEEE transactions on geoscience and remote sensing, 35(4), 980-996.
[55].Yang, C. C., Parsher, S. O., Mehuys, G. R., & Panti, N. K. (1997). Application of artificial neural networks for simulation of soil temperature. Agricultural Engineering. 40(3), 649-656.
[56].Zadmehr, H., & Farrokhian Firouzi, A. (2020). Estimation of Soil Temperature from Metrological Data Using Extreme Learning Machine, Artificial Neural Network, and Multiple Linear Regression Models. Soil and Water Research. (in Farsi)
)