This is even more critical for large altimetric databases, in which a single production method must satisfy a variety of users on a variety of landscapes in terms of relief, land cover, climate, etc. Beyond this risk of over-specification, it is not easy to define an explicit and quantitative indicator to measure the degree of agreement of the data with the information sought in terms that producers could easily take into account to optimize the production. This phenomenon is encouraged by the availability of very high-resolution DEMs. In fact, users’ needs are often over-specified, which means that the requirements are disproportionate.
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However, users (scientific or operational) do not always know how to express their needs. In addition, due to our experience and our senses as humans, the relief is a familiar object and we place such high demands on its representation that any inconsistency may be unacceptable. A major difficulty of DEM quality assessment is that it is a product that serves a wide variety of users, depending on the information required from the DEM. Like any industrial product, digital elevation models must present a quality that meets both the technical constraints of production and users’ requirements. This article explores a variety of quality assessment methods, from digital elevation model to global altimetric database. The question then arises as to who should specify the quality of DEMs between the producer and the user, and how. These quality criteria correspond to different needs, and producers must therefore take into account a variety of users. When no data is available, one can look for inconsistencies in the DEM since the land relief is not a completely random object. Digital elevation model (DEM) accuracy is commonly assessed by comparing it to reference data. The diversity of relief mapping methods and the existence of large elevation databases intended for multiple users raises the issue of DEM quality.