- Alavi, M., Albaji, M., Golabi, M., Naseri, A. A., & Homayouni, S. (2024). Estimation of sugarcane evapotranspiration from remote sensing and limited meteorological variables using machine learning models. Journal of Hydrology, 629, 130605.
- Alavi, M., Albaji, M., Golabi, M., Naseri, A. A., & Homayouni, S. (2023). Evaluating remote sensing technique and machine learning algorithms in estimating sugarcane evapotranspiration. Water and Irrigation Management, 13(4), 965-982. (In Persian)
- Babaeian, E., Sidike, P., Newcomb, M. S., Maimaitijiang, M., White, S. A., Demieville, J., Ward, R. W., Sadeghi, M., LeBauer, D. S., & Jones, S. B. (2019). A new optical remote sensing technique for high-resolution mapping of soil moisture. Frontiers in big Data, 2, 37.
- Baghdadi, N., El Hajj, M., Zribi, M., & Bousbih, S. (2017). Calibration of the water cloud model at C-band for winter crop fields and grasslands. Remote Sensing, 9(9), 969.
- Blake, G. (1965). Bulk density. Methods of Soil Analysis: Part 1 Physical and Mineralogical Properties, Including Statistics of Measurement and Sampling, 9, 374-390.
- Burdun, I., Bechtold, M., Aurela, M., De Lannoy, G., Desai, A. R., Humphreys, E., Kareksela, S., Komisarenko, V., Liimatainen, M., & Marttila, H. (2023). Hidden becomes clear: Optical remote sensing of vegetation reveals water table dynamics in northern peatlands. Remote sensing of environment, 296, 113736.
- Carlson, T. N., Gillies, R. R., & Perry, E. M. (1994). A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote sensing reviews, 9(1-2), 161-173.
- Day, P. R. (1965). Particle fractionation and particle‐size analysis. Methods of Soil Analysis: Part 1 Physical and Mineralogical Properties, Including Statistics of Measurement and Sampling, 9, 545-567.
- Goward, S. N., & Hope, A. (1989). Evapotranspiration from combined reflected solar and emitted terrestrial radiation: Preliminary FIFE results from AVHRR data. Advances in Space Research, 9(7), 239-249.
- Huete, A., Justice, C., & Liu, H. (1994). Development of vegetation and soil indices for MODIS-EOS. Remote sensing of environment, 49(3), 224-234.
- Jiang, L., & Islam, S. (1999). A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations. Geophysical research letters, 26(17), 2773-2776.
- Jimenez-Munoz, J. C., Sobrino, J. A., Skoković, D., Mattar, C., & Cristobal, J. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geoscience and remote sensing letters, 11(10), 1840-1843.
- Krishnan, S., & Indu, J. (2023). Assessing the potential of temperature/vegetation index space to infer soil moisture over Ganga Basin. Journal of Hydrology, 621, 129611.
- Mohammadi Moalezade, J., Hamzeh, S., & Naseri, A. (2022). Estimating Soil Surface Moisture Content and Investigating Irrigation Schedule of Sugarcane Fields Using Thermal Trapezoidal Model. Iranian Journal of Soil and Water Research, 53(10), 2209-2223.(In Persian)
- Moran, M., Clarke, T., Inoue, Y., & Vidal, A. (1994). Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote sensing of environment, 49(3), 246-263.
- Nouraki, A., Golabi, M., Albaji, M., Naseri, A., & Homayouni, S. (2023). Spatial-temporal modeling of soil moisture using optical and thermal remote sensing data and machine learning algorithms. Iranian Journal of Soil and Water Research, 54(4), 637-653. (In Persian)
- Nouraki, A., Akhavan, S., Rezaei, Y., & Fuentes, S. (2021). Assessment of sunflower water stress using infrared thermometry and computer vision analysis. Water Supply, 21(3), 1228-1242.
- Quintana-Molina, J. R., Sánchez-Cohen, I., Jiménez-Jiménez, S. I., Marcial-Pablo, M. d. J., Trejo-Calzada, R., & Quintana-Molina, E. (2023). Calibration of volumetric soil moisture using Landsat-8 and Sentinel-2 satellite imagery by Google Earth Engine. Revista de Teledetección(62), 21-38.
- Rahimzadeh-Bajgiran, P., Berg, A. A., Champagne, C., & Omasa, K. (2013). Estimation of soil moisture using optical/thermal infrared remote sensing in the Canadian Prairies. ISPRS journal of photogrammetry and remote sensing, 83, 94-103.
- Sadeghi, M., Babaeian, E., Tuller, M., & Jones, S. B. (2017). The optical trapezoid model: A novel approach to remote sensing of soil moisture applied to Sentinel-2 and Landsat-8 observations. Remote sensing of environment, 198, 52-68.
- Sandholt, I., Rasmussen, K., & Andersen, J. (2002). A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote sensing of environment, 79(2-3), 213-224.
- Taddeo, S., Dronova, I., & Depsky, N. (2019). Spectral vegetation indices of wetland greenness: Responses to vegetation structure, composition, and spatial distribution. Remote sensing of environment, 234, 111467.
- Tuller, M., Babaeian, E., Jones, S., Montzka, C., Vereecken, H., & Sadeghi, M. (2019). The paramount societal impact of soil moisture. Eos, 100.
- Wang, W., Huang, D., Wang, X.-G., Liu, Y.-R., & Zhou, F. (2011). Estimation of soil moisture using trapezoidal relationship between remotely sensed land surface temperature and vegetation index. Hydrology and Earth System Sciences, 15(5), 1699-1712.
|