Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is locally influenced by the landcover and the terrain slope. The quality must meet the user’s requirements, which only make sense if the nominal terrain and the relevant resolution have been explicitly specified. The aim of this article is to review the main quality assessment methods, which may be separated into two approaches, namely, with or without reference data, called external and internal quality assessment, respectively. The errors and artifacts are described. The methods to detect and quantify them are reviewed and discussed. Different product levels are considered, i.e., from point cloud to grid surface model and to derived topographic features, as well as the case of global DEMs. Finally, the issue of DEM quality is considered from the producer and user perspectives.

Digital Elevation Model (DEM) validation is often carried out by comparing the data with a set of ground control points. However, the quality of a DEM can also be considered in terms of shape realism. Beyond visual analysis, it can be verified that physical and statistical properties of the terrestrial relief are fulfilled. This approach is applied to an extract of Topodata, a DEM obtained by resampling the SRTM DEM over the Brazilian territory with a geostatistical approach. Several statistical indicators are computed, and they show that the quality of Topodata in terms of shape rendering is improved with regards to SRTM. Keywords: Digital Elevation Model; Topodata; SRTM DEM. RESUMO INTRODUCTIONDigital elevation models (DEMs) are commonly used to describe the 3D geometry of the Earth surface for a variety of applications such as landscape synthesis, hydrologic modelling or geological hazard assessment. Satellite images have been increasingly used in the past two decades to provide DEMs, mainly through photogrammetry or radar interferometry (TOUTIN and GRAY, 2000). The quality of these data has been regularly studied, both to improve the mapping methods and to evaluate their applicative potentialities. Most experiments carried out for the validation of a single DEM or a DEM production method consist in comparing the obtained data with a reference data set, generally a set of ground control points. This comparison may be based on statistical accuracy indicators such as mean difference, standard deviation or RMSE (root mean square error), and when the GCPs are numerous and well distributed the error can be interpolated and mapped. This validation approach is very relevant to evaluate the positional accuracy of the DEM. However, many applications require a good rendering of terrain shapes and a high positional accuracy does not guarantee that his requirement is fulfilled, since accurate slopes are required rather than accurate elevations. In this article, we propose several quality criteria to validate DEMs in terms of shape rendering. The characteristic of these criteria is that they are difficult to implement with ground control, and they can rather be based on reasonable hypotheses concerning geomorphological rules that all topographic surfaces are supposed to fulfil.Among the attempts to provide a world wide elevation data base, the most noticeable one is the Shuttle Radar Topography Mission (SRTM) that resulted in a homogeneous DEM with a 3 arc seconds (around 90 m) grid mesh (FARR and KOBRICK 2001).In Brazil, the Instituto Nacional de Pesquisas Espaciais has proposed another DEM called Topodata, obtained by resampling the SRTM DEM to create a 1 arc second (~30 m) grid with a geostatistical interpolation approach (VALERIANO and ROSSETTI, 2012). Since the selection of geostatistical coefficients for this interpolation considered the likelihood of DEM features relative to natural terrain shape, it was relevant to evaluate the improvement achieved with regards to the input SRTM in terms of shape realism.

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Digital elevation models (DEMs) are used for many applications, including geomorphological feature identification. This study assesses, for selected regions of Lebanon, the impact of matching parameters on the geomorphic indices extracted from photogrammetrically derived DEMs. Three parameters are shown to have a significant effect on the geomorphic indices: the template size and the correlation and curvature thresholds. The most influential parameter is the template size, an increase in which decreases the proportion of interpolated points and leads to more reliable matching, but it also tends to smooth the morphology of the DEM. A small template size tends to preserve the details of the terrain, especially for steep slopes, but it also increases noise in the DEM. For the present study, the optimal value for this parameter is about 13 9 13 pixels. High threshold values lead to more reliable matches but also increase the proportion of interpolated points, which has a significant effect on the resulting geomorphology.

ABSTRACT:Digital elevation models are considered the most useful data for dealing with geomorphology. The quality of these models is an important issue for users. This quality concerns position and shape. Vertical accuracy is the most assessed in many studies and shape quality is often neglected. However, both of them have an impact on the quality of the final results for a particular application. For instance, the elevation accuracy is required for orthorectification and the shape quality for geomorphology and hydrology. In this study, we deal with photogrammetric DEMs and show the importance of the quality assessment of both elevation and shape. For this purpose, we produce several SPOT HRV DEMs with the same dataset but with different template size, that is one of the production parameters from optical images. Then, we evaluate both elevation and shape quality. The shape quality is assessed with in situ measurements and analysis of slopes as an elementary shape and stream networks as a complex shape. We use the fractal dimension and sinuosity to evaluate the stream network shape. The results show that the elevation accuracy as well as the slope accuracy are affected by the template size. Indeed, an improvement of 1 m in the elevation accuracy and of 5 degrees in the slope accuracy has been obtained while changing this parameter. The elevation RMSE ranges from 7.6 to 8.6 m, which is smaller than the pixel size (10 m). For slope, the RMSE depends on the sampling distance. With a distance of 10 m, the minimum slope RMSE is 11.4 degrees. The stream networks extracted from these DEMs present a higher fractal dimension than the reference river. Moreover, the fractal dimension of the extracted networks has a negligible change according to the template size. Finally, the sinuosity of the stream networks is slightly affected by the change of the template size.