Kriging interpolation and conditional simulation are two common methods of spatial variation approaching, whether or not they can describe multi-scale structure of data relates to the correctness of corresponding conclusions. In this paper, we took the soil organic matters in the newly reclaimed area in Yili as an example and focused on multi-scale structure of ordinary kriging interpolation(OK) and sequential gaussian simulation(SGS) with scale variance analysis, semi-variance and Moran’s I. We inferred that 15 km, 35 km and 60 km might be characteristic scales of soil organic matters in the newly reclaimed area. In small scale, both of them resulted in bias on scale structure of real spatial data characteristic. In large scale, both of them could reflect the multi-scale structure of data and characterize the characteristic scales of 35 km and 60 km.