<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data.</p></abstract>

Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data.

Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to...

Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data

Pubblicato online: 14 ago 2018

Pagine: 285 - 294

Ricevuto: 04 set 2017

Accettato: 30 nov 2017

DOI: https://doi.org/10.1515/johh-2017-0057

Parole chiave
Drainage networks, GDEMs, OpenStreetMap, Positional accuracy

© 2018 Elisabete S.V. Monteiro, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data

Pubblicato online: 14 ago 2018

Pagine: 285 - 294

Ricevuto: 04 set 2017

Accettato: 30 nov 2017

DOI: https://doi.org/10.1515/johh-2017-0057

Parole chiaveDrainage networks, GDEMs, OpenStreetMap, Positional accuracy

© 2018 Elisabete S.V. Monteiro, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
Drainage networks, GDEMs, OpenStreetMap, Positional accuracy