Digital soil mapping: A brief history and some lessons

Abstract Digital soil mapping (DSM) is a successful sub discipline of soil science with an active research output. The success of digital soil mapping is a confluence of several factors in the beginning of 2000 including the increased availability of spatial data (digital elevation model, satellite imagery), the availability of computing power for processing data, the development of data-mining tools and GIS, and numerous applications beyond geostatistics. In addition, there was an increased global demand for spatial data including uncertainty assessments, and a rejuvenation of many soil survey and university centres which helped in the spreading of digital soil mapping technologies and knowledge. The theoretical framework for digital soil mapping was formalised in a 2003 paper in Geoderma. In this paper, we define what constitutes digital soil mapping, sketch a brief history of it, and discuss some lessons. Digital soil mapping requires three components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. We also illustrate the history with a number of sleeping beauty papers that seem too precocious and consequently the ideas were not taken up by contemporaries and largely forgotten. It took another 30 to 40 years before the ideas were rediscovered and then flourished. Examples include proximal soil sensing that was developed in the 1920s, soil spectroscopy in 1970s, and soil mapping based on similarity of environmental factors in 1979. In summary, the coming together of emerging topics and timeliness greatly assists in the development of paradigm. We learned that research and ideas that are too precocious are largely ignored — such work warrants (re)discovery.