Assistant Professor, National Salinity Research Center, Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran

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Khaleghi Rana; BEHMANESH JAVAD; Azad Nasrin

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Journal: APPLIED SOIL RESEARCH Year:2019 | Volume:7 | Issue:1 Page(s): 108-121

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Information Journal Paper

Title

Assistant Professor, National Salinity Research Center, Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran

Author(s)

Khaleghi Rana | BEHMANESH JAVAD | Azad Nasrin | Issue Writer Certificate

Keywords

Soil electrical conductivityQ1

Remote sensingQ2

Satellite dataQ1

Statistical parametersQ1

Topographic parametersQ2

Abstract

Managing and monitoring of salinity is one of the most important affair in agriculture, especially in arid and semi-arid area. For this purpose, the use of new technologies like Remote sensing and GIS is inevitable. The investigation of relationships between different soil parameters using Satellite data is an effective step in predicting the electrical conductivity of soil saturation extract. In this research, using multivariable regression method based on relationship between topographical properties and obtained indices from Landsat 8 satellite, the prediction of the electrical conductivity of soil saturation extract was studied in Urmia plain. For this purpose, firstly 40 samples were taken from 0-30 cm soil depth and their electrical conductivity of soil saturation extract (ECe) were measured. After performing the necessary processing on satellite images and determining the ground surface points, pixel values in the different bands were extracted. In the present research, the data was divided into two series including training (80% of data) and validation data (20% of data). The relationship between Satellite data and the obtained results from the region soil tests was extracted using the multivariable linear regression methods and the accuracy of the model was evaluated by factors such as R-squared, standard error of the mean, adjusted R-squared and Durbin Watson statistic. The results showed that for the obtained model, the error indices including the correlation coefficient, standard error of the mean, adjusted R-squared and Durbin Watson statistic were calculated 70. 3%, 10. 03%, 61. 8% and 1. 709 respectively. Finally, the model was run using test data and for its evaluation the indices including Geometric Mean Error Ratio (GMER), R-squared (R2) and Root Mean Square Error (RMSE) were employed so that the mentioned indices were measured 0. 867, 0. 638 and 0. 354 respectively. These results show good efficiency and accuracy of the model

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APA: Copy

Khaleghi, Rana, BEHMANESH, JAVAD, & Azad, Nasrin. (2019). Assistant Professor, National Salinity Research Center, Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran. APPLIED SOIL RESEARCH, 7(1 ), 108-121. SID. https://sid.ir/paper/261905/en

Vancouver: Copy

Khaleghi Rana, BEHMANESH JAVAD, Azad Nasrin. Assistant Professor, National Salinity Research Center, Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran. APPLIED SOIL RESEARCH[Internet]. 2019;7(1 ):108-121. Available from: https://sid.ir/paper/261905/en

IEEE: Copy

Rana Khaleghi, JAVAD BEHMANESH, and Nasrin Azad, “Assistant Professor, National Salinity Research Center, Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran,” APPLIED SOIL RESEARCH, vol. 7, no. 1 , pp. 108–121, 2019, [Online]. Available: https://sid.ir/paper/261905/en

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