Soil survey provides information on soils, their spatial distribution and their areal extent for proper land use planning and agro-technology transfer. Remote sensing has emerged as a potential modern tool which can be utilised as a cost eiTective means of small-scale soil mapping. In the present study, different soilscape units (physiography-cum-soil association units) were identified following a supervised classification based on a maximum likelihood classifier using IRS (Indian Remote Sensing Satellite) 1A-LISS-II digital data. Six soilscape units, namely hills, valleys, moderate and severe eroded piedmonts, alluvial plain and river terraces were identified and delineated digitally. The overall classification accuracy of the digital soil map is 92 per cent. Major soils (subgroup levels) encountered in various soilscape units are-Typic/Lithic Ustorthents; Typic/Udic Ustochrepts; Typic Haplustalfs; Typic Ustipsamments and Typic Ustifluvents.