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In this paper, we borrow from blind noise parameter estimation (BNPE)methodology early developed in the image processing field an original andinnovative no-reference approach to estimate Digital Elevation Model (DEM)vertical error parameters without resorting to a reference DEM. The challengesassociated with the proposed approach related to the physical nature of theerror and its multifactor structure in DEM are discussed in detail. A suitablemultivariate method is then developed for estimating the error in gridded DEM.It is built on a recently proposed vectorial BNPE method for estimatingspatially correlated noise using Noise Informative areas and Fractal BrownianMotion. The newly multivariate method is derived to estimate the effect of thestacking procedure and that of the epipolar line error on local (fine-scale)standard deviation and autocorrelation function width of photogrammetric DEMmeasurement error. Applying the new estimator to ASTER GDEM2 and ALOS World 3DDEMs, good agreement of derived estimates with results available in theliterature is evidenced. In future works, the proposed no-reference method foranalyzing DEM error can be extended to a larger number of predictors foraccounting for other factors influencing remote sensing (RS) DEM accuracy.

Estimation of Variance and Spatial Correlation Width for Fine-scale Measurement Error in Digital Elevation Model