Fusion of Soil and Remote Sensing in Support of Digital Soil Modeling.

The evolution of digital soil mapping (DSM) and modeling techniques during the last decade, addressing new methods and paradigms for soil data and information needs, have the potential to overcome some of the limitations imposed by labor intensive and costly traditional soil surveys. There is still work ahead in soil science to provide a universally accepted digital soil model responding to global societal needs toward environmentally sustainable management. Digital Soil Mapping involves the use of fusion techniques for fitting quantitative relationships between soil properties or classes and their environment. The fusion of spectral data from various sensors with soil geographic data, field observations, and other ancillary data, represents a powerful merging of technologies, methods, and data sources, intended to improve the understanding and mapping of soil systems. These emerging soil models are meta-paradigmatic (i.e., based on a suite of paradigms from different disciplines), use multiple methodologies (e.g., Bayesian statistics, geostatistics, regression trees), and fuse data acquired from multiple sources (e.g., in-situ observations, proximal sensing, remote sensing). Particular interest and application are in those complex and highly variable landscapes, especially where difficulties on data collection due to remoteness and inaccessibility of sampling locations lead to sparse data sets. In these cases, data fusion or integral approaches can maximize data sampling integrating multiple data sources, including historic datasets. Differences in satellite-based, airborne and ground-based soil sensors are used to optimize the characterization of soil properties, which include spatial, temporal, and spectral resolutions, where larger distances between sensor and object introduce the possibility of more noise. For this reason, conventional laboratory methods are being complemented with proximal or ground-based soil sensors. It has been hypothesized that fusion techniques will improve the accuracy of predictions of various soil properties and permit their application over a greater range of soil physical and chemical properties.