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Estimation of soil moisture using WCM model and Sentinel satellite imagery for irrigation scheduling of sugarcane fields
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Reyhaneh Leghayat   , Saeid Hamzeh * , Nahmeh Neysani Samani , Jamal MOhammadi Moalehzadeh , Abed Ali Naseri |
| University of Tehran |
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Abstract: (1694 Views) |
Estimating of soil moisture is very important for water resources studies and irrigation scheduling, and for this purpose the use of satellite imagery is very helpful. The present research was conducted to evaluate the capability of WCM model based on the use of radar and optical data of Sentinel 1 and 2 to estimate soil moisture and irrigation scheduling in sugarcane cultivation lands located in the southwest of Iran. For this purpose, the soil moisture was measured from May 18 to September 27, 2020, simultaneously with 7 passes of Sentinel 1 and 2 satellites at 337 ground control points located in 18 sugarcane fields using a TDR350 moisture meter. After performing the necessary processing, the soil moisture was estimated using the WCM model using different polarizations of radar images as well as different plant indices and the results were evaluated using field observations. The obtained results show that the WCM model using LAI index and VV polarization is more accurate in estimating soil moisture. Also, the accuracy of the results for the case where the desired model is calculated for each image separately is higher than when a general model is developed for the entire sugarcane growth period. The RMSE of this model for a single image using the LAI index is in the range of [1-13 %] and its correlation coefficient is [0.98-0.34]. If a model is developed for the entire period, the RMSE is between [17 -22 %] and its correlation coefficient is [0/1-0/2].
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| Keywords: Remote Sensing, Radar and Optical Imagery, WCM model, Soil Moisture, Irrigation |
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Full-Text [PDF 2228 kb]
(531 Downloads)
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Type of Study: Research |
Subject:
RS
Received: 2022/09/7 | Accepted: 2023/05/21 | ePublished ahead of print: 2023/05/21 | Published: 2023/05/21
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