  We present a practical approach to inter-compare a range of candidate digital
elevation models (DEMs) based on pre-defined criteria and statistically sound
ranking approach. The presented approach integrates the randomized complete
block design (RCBD) into a novel framework for DEMs comparison. The method
presented provides a flexible, statistically sound and customizable tool for
evaluating the quality of any raster - in this case a DEM - by means of a
ranking approach, which takes into account a confidence level, and can use both
quantitative and qualitative criteria. The users can design their own criteria
for the quality evaluation in relation to their specific needs. The application
of the RCBD method to rank six 1" global DEMs, considering a wide set of study
sites, covering different morphological and landcover settings, highlights the
potentialities of the approach. We used a suite of criteria relating to the
differences in the elevation, slope, and roughness distributions compared to
reference DEMs aggregated from 1-5 m lidar-derived DEMs. Results confirmed
significant superiority of CopDEM 1" and its derivative FABDEM as the overall
best 1" global DEMs. They are slightly better than ALOS, and clearly outperform
NASADEM and SRTM, which are in turn much better than ASTER.
