Updating a physiography-based soil map using digital soil mapping techniques

Abstract

Research work carried out in Entre-Rios province (Argentina) for mixed land use planning and management in relation to suitable soil conditions required high-resolution soil information at farm level. Basic information was provided by a 1:20,000 scale soil map made using physiographic analysis with intensive aerial photo-interpretation of soil-landscape relationships and landscape-oriented fi eld survey. Continuous productivity-index (PI) classes were predicted from a number of environmental covariates, mostly DEM derivatives, using regression and geostatistical techniques. The PI land classifi cation was used to adjust the soil-landscape/soil-series interpretation of the existing choropleth soil map by means of correlating discrete PI values obtained from a conventional mapping procedure with continuous PI values obtained by soil digital mapping procedures.