Digital elevation models (DEMs) are the basic data of science and engineering technology research. SRTM and ASTER GDEM are currently widely used global DEMs, and TanDEM-X DEM, released in 2016, has attracted users’ attention due to its unprecedented accuracy. These global datasets are often used for local applications and the quality of DEMs affects the results of applications. Many researchers have assessed and compared the quality of global DEMs on a local scale. To provide some additional insights on quality assessment of 12- and 30-m resolution TanDEM-X DEMs, 30-m resolution ASTER GDEM and 30-m resolution SRTM, this study assessed differences’ performance in relation to not only geographical features but also the ways in which DEMs have been created on selected Chinese sites, taking ICESat/GLAS points with 14-cm absolute vertical accuracy but size of 70-m diameter and 12-m resolution TanDEM-X DEM with less than 10-m absolute vertical accuracy as the reference data for comprehensive quality evaluation. When comparing the three 30-m DEMs with the reference DEM, an improved Least Z-Difference (LZD) method was applied for co-registration between models, and Quantile–Quantile (Q-Q) plot was used to identify if the DEM errors follow a normal distribution to help choose proper statistical indicators accordingly. The results show that: (1) TanDEM-X DEMs have the best overall quality, followed by SRTM. ASTER GDEM has the worst quality. The 12-m TanDEM-X DEM has significant advantages in describing terrain details. (2) The quality of DEM has a strong relationship with slope, aspect and land cover. However, the relationship between aspect and vertical quality weakens after data co-registration. The quality of DEMs gets higher with the increasing number of images used in the fusion process. The quality in where slopes opposite to the radar beam is the worst for SRTM, which could provide a new perspective for quality assessment of SRTM and other DEMs whose incidence angle files are available. (3) Systematic deviations can reduce the vertical quality of DEM. The differences have non-normal distribution even after co-registration. For researchers who want to know the quality of a DEM in order to use it in further applications, they should pay more attention to the terrain factors and land cover in their study areas and the ways in which the DEM has been created.

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