The accuracy, speed, and feasibility of studying soil properties depend largely on the techniques used and their efficiency to correlate soil attributes. This study aimed to investigate the capability of the diffuse reflectance spectroscopy (DRS) and magnetic susceptibility (MS) methods in predicting and mapping soil physicochemical properties and monitoring their spatial distribution in an arid and semi-arid region, southern Iran. A total of 100 surface soil samples were collected from the depth of 0-20 cm and analyzed for OC, CCE, gypsum, clay, EC, Fed, chi lf, and VIS-NIR-SWIR (350-2500 nm) spectroscopy using standard laboratory methods. The DRS and MS techniques were then used to estimate soil properties using the partial least squares regression (PLSR) and the linear regression methods, respectively. Results showed an accurate estimation of gypsum (RPD = 2.3 and R2 = 0.81), and reliable estimations for clay, Fed, OC, CCE, and EC by the PLSR method. However, the MS method presented reliable results only for the Fed (RPD = 1.5, R2 = 0.55). The DRS- and MS-derived predictive maps showed different spatial distribution patterns from the interpolated maps which were derived based on the observed data. The Fed parameter showed the most similarity with its observed data in both DRS- and MS-derived maps; whereas in the case of other soil properties, the DRS method presented a better prediction performance compared to the MS one. The findings of the present study highlighted the significant capability of the DRS technique as an efficient predictor for soil properties in the studied area.