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- W2379214480 abstract "The report on of DEM accuracy is commonly based on some global statistical measures,such as the mean and standard deviation of DEM errors.Usually,the specification of these accuracy indices is based on the assumption that the error distribution is normal and there is no outlier and systematic error.However,such an assumption is rarely an exact statement owing to the malfunction or improper calibration of instruments,mistaken readings,gross recording and calculation,and improper execution,etc,particularly when a DEM is directly derived from digital photogrammetric systems and active airborne sensors including Light Detection and Ranging(LiDAR) and InSAR.A robust estimator based on the adaptive M-estimation principle(REMP) has been developed for the DEM accuracy assessment.The iteration of REMP starts from estimations with a high breakdown point and selection of the weights of errors with the residual distribution.In terms of DEM mean and standard deviation errors,two examples including a numerical test and a real-world one were employed to comparatively analyze the results of REMP and the classical non-robust and robust estimators.Results indicate that under the non-normal distribution of DEM errors,the classical non-robust estimators are seriously influenced by the non-normality.Some robust estimators,such as 10% trimmed or Winsorized mean,normalized median absolute deviation are not very robust to resist the influence of outliers.REMP that is slightly affected by the non-normal distribution of DEM errors is more accurate than the classical estimators.The robust methodology can adapt to the DEMs,especially the ones derived from remote sensing,such as LiDAR or digital photogrammetry in the non-open terrain." @default.
- W2379214480 created "2016-06-24" @default.
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- W2379214480 date "2011-01-01" @default.
- W2379214480 modified "2023-09-23" @default.
- W2379214480 title "DEM Accuracy Assessment Based on M-Estimation" @default.
- W2379214480 hasPublicationYear "2011" @default.
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