Comparison of remote sensing methods for estimating actual daily evapotranspiration using Landsat 8 multispectral images

Document Type : علمی - پژوهشی

Authors

1 MSc Student in Remote Sensing. k.n.toosi university of technology

2 Professor in Department of photogrammetry and remote sensing, College of geodesy and geomatics, K.N.Toosi University

3 Ph.D. student of photogrammetry in Department of photogrammetry and remote sensing, College of geodesy and geomatics, K.N.Toosi University

Abstract

Agriculture consumes approximately 70% of freshwater resources worldwide. The world population is expected to reach 9.8 billion people by 2050. The increase in population leads to a rise in the demand for food. But limited resources make food security a severe threat. As a result, it is necessary to manage and increase irrigation efficiency. Actual crop evapotranspiration (ETa) is essential for estimating irrigation water requirements. According to the conducted studies and the wide application of ET estimation models, it is necessary to increase the focus on accurate and fast methods of determining this parameter. Therefore, this study aims to compare more user-friendly ETa. remote sensing estimation methods, including the EEFLUX system, METRICTOOL, and the automatic hot and cold pixel selection method of SEBAL and METRIC models. For this purpose, 6 Landsat 8 satellite images were used during the winter wheat crop planting period of Tehran University farms in Mohammad Shahr Karaj. Evaluation of the mentioned methods was done using alfalfa reference evapotranspiration (ETr) of the FAO-Penman-Monteith method as reference data. RMSE of EEFLUX system, METRICTOOL, SEBAL, and automatic METRIC were obtained as 2.45, 0.33, 0.39, and 2.76, respectively. According to the numerical results, the automatic approach can be accurate as the METRICTOOL. In this way, the automatic process increases the model's efficiency in terms of time and efficiency and can reduce human error in ET estimation for new or inexperienced users, making these models available to the public. Also, EEFLUX data can be helpful for management measures in large-scale studies.

Keywords

Iranian Journal of Remote Sensing & GIS

Articles in Press, Accepted Manuscript
Available Online from 08 May 2024

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