Global environmental changes have resulted in modifications in ecosystem services that soils provide. It is necessary to have up to date soil information at regional and global scales to ensure that essential services continue to be provided. With the advancement in computer and sensing technologies, methods for soil data collection and spatial modeling of large-scale areas may benefit from using spectroscopy.
This research demonstrates that remote and proximal sensing (RS and PS) methods are an important and also essential source for regional-scale digital soil mapping (DSM). The main findings show that the integrated use of RS and PS with geostatistical methods improves regional-scale DSM. In every step of the soil mapping process, spectroscopy can play a key role and can deliver data in a timely and cost efficient manner. In our quest to further develop such methods, we need to combine legacy, in-situ, and observational data with (spatiotemporal) modeling to allow better prediction of soil properties. In the near future, this will enable us to deliver more accurate and comprehensive information about soil resources and associated ecosystem services at regional scale and, ultimately at global scale as well.