Iranian Journal of Irrigation & Drainage

Iranian Journal of Irrigation & Drainage

Estimation of Sugarcane Yield Using Landsat and Sentinel Satellite Images (Case Study: Haft-Tappeh Sugarcane Cultivation and Industry)

Document Type : Original Article

Authors
mehdi kaydani 1
abdorahim hooshmand 2
saeid hamzeh 3
1 Doctoral student of water science and engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Shahid Chamran University of Ahvaz
3 University of Tehran
Abstract
Estimating the amount of sugarcane crop has a key role for a wide range of applications such as sugarcane production management. In this research, the prediction of sugarcane crop yield with the methods of Normalized Differential Greenness Index (NDVI), Enhanced Greenness Index (EVI) and Soil Amended Vegetation Spectral Index (SAVI) extracted from satellite images is examined. was placed for this, Landsat 8 and 9 and Sentinel 2 satellite images from March 1401 to February 1402 were used. First, three fields with different soil texture were selected, then satellite images were taken in three stages for each field according to the simultaneous passage of two satellites from the study area, and at specific points the values of NDVI, EVI and SAVI indices after correction and processing It was extracted from satellite images and their correlation with observed vield data was obtained. The results showed that SAVI of Sentinel 2 satellite in loamy soil texture and EVI of Sentinel 2 satellite in loamy-clay-silty and clayey soil texture were more related with explanation coefficient of 0.76. Then, based on the superior index, the fitted linear regression relationship between the index and yield was obtained for each farm with different soil texture. The results of the relationship analysis showed a strong correlation between the observed and calculated values with the linear regression relationship of sugarcane yield in all three fields. The highest explanatory coefficient and predictive correlation of the regression relationship with observed values of 0.83 and 0.91 were obtained in the field with loamy soil texture. In general, the results of this research showed that the more the heavy texture of the soil is reduced, the more reliable the results of the fitted regression relationship can be.
Keywords
Sugarcane
Landsat
Sentinel
Crop Yield
Vegetation Index
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Iranian Journal of Irrigation & Drainage
Volume 18, Issue 6 - Serial Number 109
January and February 2025
Pages 1023-1033