Based on existing principles of automated drainage network extraction we have developed two methodological algorithms, the “profile scan” and “hydrological flow modeling,” and used them to extract networks from digital elevation models (DEMs). The “hydrological flow modeling” algorithm specializes in the extraction of well‐connected hierarchically arranged skeletal channel networks. On the other hand, the channels extracted by the “profile scan” algorithm lack adequate connectivity, but this algorithm is suitable for the extraction of wide valley bottoms and other flat areas. A combination of the two algorithms gives a more versatile algorithm capable of yielding networks which are not only well connected but also portray the surface character of the drainage network thus generated. The good functioning of our algorithm is not inhibited by the presence of pits in the DEM. There is therefore no preprocessing of the DEM prior to drainage extraction. Rather, at the end of extraction, isolated spots are eliminated since these are the ones most probably representing artifacts.
Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record the interface between the atmosphere and the lithosphere using a discrete two-dimensional grid, with complexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere. The treatment of DEM surfaces, affected by these intervening spheres, depends on their intended use, and the characteristics of the sensors that were used to create them. DEM is a general term, and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) record the treatment of the intermediate surfaces. Several global DEMs generated with optical (visible and near-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars and products of satellite altimetry, share the common characteristic of a georectified, gridded storage structure. Nevertheless, not all DEMs share the same vertical datum, not all use the same convention for the area on the ground represented by each pixel in the DEM, and some of them have variable data spacings depending on the latitude. This paper highlights the importance of knowing, understanding and reflecting on the sensor and DEM characteristics and consolidates terminology and definitions of key concepts to facilitate a common understanding among the growing community of DEM users, who do not necessarily share the same background.
Abstract. This paper presents an initiative recently launched under the auspices of the Committee on Earth Observation Satellites (CEOS) aiming at providing harmonised terminology and methods, as well as practical guidelines and results allowing the intercomparison of continental or global Digital Elevation Models (DEM). As the work is still ongoing the main purpose of this article is not the dissemination of the outcome but rather to inform the wider community about the initiative, communicate the chosen approach to raise awareness, and attract possible further participants. Nevertheless, some preliminary results are included and an outlook on planned next steps is provided.
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