Vertical change is often measured in the cryosphere via digital elevation model (DEM) differencing to assess glacier and ice-sheet mass balances. This requires the signal of change to outweigh the noise associated with the datasets. On the ice-free earth, land-level change is much smaller in magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required high-resolution data at small scales. For the first time we measure land-level changes at the scale of entire mountain belts in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010–2015), both spaceborne radar DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove ~ 1/10 pixel (~ 3 m) shifts, Fast Fourier Transform and filtering to remove SRTM-C short- and long-wavelength stripes, and blocked shifting to remove remaining complex biases. The datasets are then differenced and outlier pixels are identified as potential signal for the case of gravel-bed channels and hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to ~ 3 m in best case) in two > 100 km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5 m (up to > 10 m for large piles). These values correspond to conservative rates of 0.2 to > 0.5 m/yr for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide with a deposit volume of 16 ± 0.15 × 10 6 m 3 . Additional signals of change can be garnered from TanDEM-X auxiliary layers, however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.