Relationship Between Field Measurement of Soil Moisture in the Effective Depth of Sugarcane Root Zone and Extracted Indi
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RESEARCH ARTICLE
Relationship Between Field Measurement of Soil Moisture in the Effective Depth of Sugarcane Root Zone and Extracted Indices from Spectral Reflectance of Optical/Thermal Bands of Multispectral Satellite Images Shadman Veysi1
•
Abd Ali Naseri2 • Saeid Hamzeh3
Received: 31 May 2020 / Accepted: 28 July 2020 Ó Indian Society of Remote Sensing 2020
Abstract Estimation of soil moisture variables is very important in agriculture studies such as precision irrigation and its management, so knowledge of the variation would be highly beneficial. Effective irrigation is possible with regular monitoring of soil and plant water conditions and with the forecasting of future crop water requirement. This study explored the capability of indices for estimating soil moisture as an indicator of detection irrigation time in sugarcane farms located in the southwest of Iran. For this goal, Landsat 8 satellite images were got from May until September 2015. Concurrent with the satellite pass times, field measurements include soil moisture (SM) and canopy temperature was done at the predefined points in sugarcane farms. These farms were selected with different age and irrigation days. Various indices were calculated using the combination of optical and thermal infrared wavelengths, and their relationship to the amount of SM was studied. According to the results of this research, vegetation indices based on optical bands do not show a good coefficient of determination (R2). Results showed that soil moisture computed by crop water stress index (CWSI) and temperature vegetation dryness index (TVDI) have a similar trend, which showed that both indices can be used for irrigation scheduling, although they had some differences for computed soil moisture, TVDI had better correlation than to CWSI. TVDI indicated a good correlation with SM measurement data which R2 values range from 0.35 to 0.66, as well as inharmonious with the spatial distribution of (SM). It showed (RMSE) less than 0.2. Comparing recorded irrigation and (SM) in the farms shows that (SM) can be classified into three classes: low soil moisture (0.1 \ SM B 0.15), medium soil moisture (0.15 \ SM B 0.2) and high soil moisture (0.2 \ SM B 0.25). This classification can be utilized for precision irrigation scheduling in soils with heavy and semi-heavy texture (silty clay and silty clay loam). All of the results demonstrated that the TVDI can be utilized for assessment SM and determine irrigation time in agriculture lands, without each other in situ measurement of data. Keywords Irrigation scheduling Soil moisture (SM) Sugarcane Remote sensing
Introduction & Shadman Veysi [email protected] 1
Research Department of Cropland Horticultural Science, Kurdistan Agricultural and Natural Resources Research and Education Center, ARREO, Sanandaj, Iran
2
Department of Irrigation and Drainage, Faculty of Water Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran
3
Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, P.O. Box 14155-6
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