Kaydani, M., Hooshmand, A., Hamzeh, S. (2024). Valuating the Accuracy of Models Based on Thermal and Optical Satellite Data to Estimate Soil Moisture with Different Textures in Haft-Tapeh Sugarcane Agro- Industry. , 38(3), 239-255. doi: 10.22092/jwra.2024.367149.1056
Mehdi Kaydani; Abdorahim Hooshmand; Saeid Hamzeh. "Valuating the Accuracy of Models Based on Thermal and Optical Satellite Data to Estimate Soil Moisture with Different Textures in Haft-Tapeh Sugarcane Agro- Industry". , 38, 3, 2024, 239-255. doi: 10.22092/jwra.2024.367149.1056
Kaydani, M., Hooshmand, A., Hamzeh, S. (2024). 'Valuating the Accuracy of Models Based on Thermal and Optical Satellite Data to Estimate Soil Moisture with Different Textures in Haft-Tapeh Sugarcane Agro- Industry', , 38(3), pp. 239-255. doi: 10.22092/jwra.2024.367149.1056
Kaydani, M., Hooshmand, A., Hamzeh, S. Valuating the Accuracy of Models Based on Thermal and Optical Satellite Data to Estimate Soil Moisture with Different Textures in Haft-Tapeh Sugarcane Agro- Industry. , 2024; 38(3): 239-255. doi: 10.22092/jwra.2024.367149.1056

Valuating the Accuracy of Models Based on Thermal and Optical Satellite Data to Estimate Soil Moisture with Different Textures in Haft-Tapeh Sugarcane Agro- Industry

پژوهش آب در کشاورزی
Article 5, Volume 38, Issue 3, December 2024, Pages 239-255    PDF (1.82 M)
Document Type: Research Paper
DOI: 10.22092/jwra.2024.367149.1056
Authors
Mehdi Kaydani* 1; Abdorahim Hooshmand2; Saeid Hamzeh3
1PhD student of Water Science and Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
2Professor, Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
3Associate Prof., Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Abstract
Soil moisture is one of the key parameters in the management of water, soil and plant resources. Due to problems such as discontinuity in taking samples, lack of access to sufficient information about the characteristics of the regions, as well as spending a lot of time and money to estimate the amount of available soil moisture and its spatial changes, the use of satellite images is proposed as a cost-effective and efficient method. The thermal-visible trapezoidal model is based on the interpretation of pixel distribution in LST-V1 space, which is used to estimate soil surface moisture or real evapotranspiration. The aim of this study was to estimate soil moisture during the season of 2021-22 for three different soil textures in Haft-Tapeh Sugarcane Agro-industry Company. This was done by Landsat 8 and 9 satellite images and using thermal and optical trapezoidal methods. The results indicated similar accuracy of both models in estimating soil moisture in all three soil textures. Based on the fitted regression relationship between both models and the percentage of volumetric soil moisture in the measured points, the highest coefficient of explanation obtained between was 0.96 for the thermal trapezoidal model and 97.00 for the optical trapezoidal model, in loamy soil texture. This indicated the exact fit and distribution of data in LST-V1 and STR-VI space by the desired models. Also, for the efficiency of the obtained maps, the lowest value of RMSE percentage was calculated for the two models in loamy soil texture as 3.74 and 3.77, respectively. In general, it can be concluded that optical and thermal trapezoidal models predict soil moisture with a small difference and with high accuracy for all the three loamy soil textures.
Keywords
Optical Trapezoidal Model; Thermal Trapezoidal Model; Landsat 8 and 9 satellite images
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