Research has been shown that the organic matter content can be predicted from light reflectance with a linear or curvilinear relationship in the visual and infrared range. The High-resolution, remotely sensed imagery of a bare surface crop field have been proven to quantitatively describe the spatial variation of the surface SOC contents in our previous study (Chen et al. 2000 and 2005). The technology and methodology were simple and accurate enough to be of practical use in agricultural production fields, and to greatly reduce the number of soil samples and the cost of soil analysis compared to grid sampling methods. However this procedure requires that the field needs to have a dry and bare soil surface at the time of obtaining the remotely sensed image of the field. As we may realize that when we want to map a field with remote sensing we cannot always obtain a remotely sensed image with a dry and bare soil surface. Therefore, the method we previously developed would not be successful applied for mapping a field if the field does not have dry and bare soil surface. Soil organic carbon is an important factor in soil formation. The accumulation of SOC has a close relationship with topographic (landscape) properties that can be derived from digital elevation model (DEM). This would give us a different way of mapping SOC content of a field by creating the relationship between SOC and the topographic properties. In this study, the relationships between SOC and various topographic properties will be examined, and soil organic carbon content will be mapped by examining the soil-landscape relationships at a field scale.