Estimating Soil Organic Matter in Semirom Area by Using Satellite Images

Document Type : Research Paper

Authors

1 MSc., Environmental Sciences, Department of Environmental Sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

2 Assistant Professor of Environmental Sciences, Department of Environmental Sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran; Waste and Wastewater Research Center, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

3 Assistant Professor of Soil Sciences, Department of Environmental Sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

Abstract

Soil organic matter is one of the most important physical properties of soil, and is affected by such factors as vegetation, soil properties, and the climate of the region. In order to determine the amount of soil organic matter, after studying satellite images and resource assessment and land capability maps, a part of Semirom region was selected for conducting field studies, and Landsat 8 OLI image was cut in accordance with the border of the study area. Sampling points were chosen through identification of the region and using maps, official statistics, and false-color composite images of the area. Accordingly, 50 soil samples were taken from the surface soil (0-20 cm) and the amount of organic matter, electrical conductivity and pH were measured. To investigate the efficiency of satellite images in determining the amount of soil organic matter, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were estimated using satellite images and Terrest and ArcGIS 10.5 softwares, and the corresponding maps were developed. The relationship between the organic matter and vegetation indexes was examined using linear regression analysis and correlation coefficient. The results indicated significant correlation higher than 70 % between the organic matter and the vegetation indices. It could be concluded that remote sensing and satellite images can serve as tools for overcoming the limitations of traditional methods and are appropriate for monitoring the quality of soil. Remote sensing allows for displaying the results in terms of temporal and spatial scales, and is especially appropriate for extensive areas.

Keywords


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