Heavy metal soil contamination is a severe environmental problem globally, and its mapping is vital for environmental managers and policymakers to determine its distributions and hotspots. This paper reviewed multiple proximal and remote sensing spectroscopy for convenient and inexpensive method of obtaining soil reflectance spectroscopy or environmental covariates, which can be used for mapping heavy metal soil contamination. Furthermore, spatial prediction using proximal remote-sensed data and environmental covariates was discussed. We suggested that mapping of the spatial distributions of metal species may be important due to the different bioavailabilities and toxicities of various species. The assimilation of multiple proximal/remote-sensed sensors may promote the horizontal and vertical mapping of soil heavy metals. Moreover, combining the advantages of satellite and unmanned aerial vehicle -based hyperspectral imaging systems will facilitate the development of a space–aeronautic incorporation hyperspectral observation technology that can monitor soil environment rapidly and accurately at a large scale.