Assessment of soil organic matter status using regression kriging technique and Landsat images

Soil organic matter (SOM) is an important soil quality factor that affects physical, chemical and biological properties of the soil. Accurate estimation of SOM spatial variabilities provides critical information especially in precision agriculture. The objective of this study was to estimate SOM spatial variabilities and to assess its status using regression kriging (RK) in Ghorveh plain in Kurdistan province (Iran). Therefore, 150 soil samples from a depth of 0-15 cm were taken systematically in a grid spaced 2 Km × 2 Km. Particle size distribution and SOM content of the soil samples were measured in the laboratory. Stepwise multiple linear regressions (MLR) was used to estimate SOM variabilities based on the soil texture data (percentages of sand, silt and clay) and vegetation indices obtained from Landsat Enhanced Thematic Mapper (ETM) imagery. The MLR model was used to provide an initial map of SOM content. Furthermore, the residuals of MLR model were interpolated using ordinary kriging (OK) and they were combined with the initial map of SOM to produce the final map of RK SOM. The SOM status map was derived from overlaying of soil texture and SOM maps in four different levels (very low, low, medium and high). The results of MLR indicated that both clay content and soil adjusted vegetation index (SAVI) variables have a significant effect on SOM content (p <0.05). The cross-validation results indicated that the RK method was able to explain about 84% of the spatial variabilities of SOM. The SOM status map indicated that more than 96% of the soil in the proposed region is in a low condition in terms of organic matter.