We performed a systematic mapping of validation methods used in digital soil mapping (DSM), in order to gain an overview of current practices and make recommendations for future publications on DSM studies. A systematic search and screening procedure, largely following the RepOrting standards for Systematic Evidence Syntheses (ROSES) protocol, was carried out. It yielded a database of 188 peer-reviewed DSM studies from the past two decades, all written in English and all presenting a raster map of a continuous soil property. Review of the full-texts showed that most publications (97%) included some type of map validation, while just over one-third (35%) estimated map uncertainty. Most commonly, a combination of multiple (existing) soil sampe datasets was used and the resulting maps were validated by single data-splitting or cross-validation. It was common for essential information to be lacking in method descriptions. This is unfortunate, as lack of information on sampling design (missing in 25% of 188 studies) and sample support (missing in 45% of 188 studies) makes it difficult to interpret what derived validation metrics represent, compromising their usefulness. Therefore, we present a list of method details that should be provided in DSM studies. We also provide a detailed summary of the 28 validation metrics used in published DSM studies, how to interpret the values obtained and whether the metrics can be compared between datasets or soil attributes
