This article reviews the use of optical, microwave, Lidar and hyper spectral remote sensing data for soil mapping with emphasis on applications at local and regional level. Remote sensing is expected to offer possibilities for improving incomplete spatial and thematic coverage of current regional and global soil databases. Soil properties that have been measured using remote sensing approaches include mineralogy, texture, soil iron, soil moisture, soil organic carbon, soil salinity and carbonate content. In sparsely vegetated areas, successful use of space borne, airborne and in situ measurements using optical, passive and active microwave instruments has been reported. On the other hand, in densely vegetated areas, soil data acquisition typically relied on indirect retrievals using soil indicators, such as plant functional groups, productivity changes, and Ellenberg indicator values. Several forms of kriging, classification and regression tree analyses have been used jointly with remotely sensed data to predict soil properties at unvisited locations aiming at obtaining continuous area coverage. Yet, most studies so far have been performed on a local scale and only few on regional or smaller map scale. Although progress has been made, current methods and techniques still bear potential to further explore the full range of spectral, spatial and temporal properties of existing data sources.
soil survey, remote sensing, hyper spectral, lidar, review
