[HTML][HTML] Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network accuracy in Sweden

W Lidberg - Journal of Hydrology: Regional Studies, 2025 - Elsevier
Study region Sweden, a mostly forested country with many small forest roads obstructing
topographical modelling of shallow groundwater and streams. Study focus Maps have …

[HTML][HTML] Automatic Detection of Ditches and Natural Streams from Digital Elevation Models Using Deep Learning

MDST Busarello, AM Ågren, F Westphal… - Computers & …, 2025 - Elsevier
Policies focused on waterbody protection and restoration have been suggested to European
Union member countries for some time, but to adopt these policies on a large scale the …

Mapping small watercourses from DEMs with deep learning—exploring the causes of false predictions

C Koski, P Kettunen, J Poutanen, L Zhu, J Oksanen - Remote Sensing, 2023 - mdpi.com
Vector datasets of small watercourses, such as rivulets, streams, and ditches, are important
for many visualization and analysis use cases. Mapping small watercourses with traditional …

Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning

L Stanislawski, T Brockmeyer… - … Archives of the …, 2018 - isprs-archives.copernicus.org
High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and
3 meters, have increasingly become more widely available, along with lidar point cloud data …

The importance of better mapping of stream networks using high resolution digital elevation models–upscaling from watershed scale to regional and national scales

AM Ågren, W Lidberg - Hydrology and Earth System Sciences …, 2019 - hess.copernicus.org
Headwaters make up the majority of any given stream network, yet, they are poorly mapped.
A solution to this is to model the stream networks from a high resolution digital elevation …

Evaluating preprocessing methods of digital elevation models for hydrological modelling

W Lidberg, M Nilsson, T Lundmark… - Hydrological …, 2017 - Wiley Online Library
With the introduction of high‐resolution digital elevation models, it is possible to use digital
terrain analysis to extract small streams. In order to map streams correctly, it is necessary to …

Deep learning-enhanced extraction of drainage networks from digital elevation models

X Mao, JK Chow, Z Su, YH Wang, J Li, T Wu… - … Modelling & Software, 2021 - Elsevier
Drainage network extraction is essential for different research and applications. However,
traditional methods have low efficiency, low accuracy for flat regions, and difficulties in …

Classification of drainage crossings on high-resolution digital elevation models: A deep learning approach

D Wu, R Li, B Rekabdar, C Talbert… - GIScience & Remote …, 2023 - Taylor & Francis
ABSTRACT High-Resolution Digital Elevation Models (HRDEMs) have been used to
delineate fine-scale hydrographic features in landscapes with relatively level topography …

GeoAI-based drainage crossing detection for elevation-derived hydrographic mapping

M Edidem, R Li, D Wu, B Rekabdar, G Wang - Environmental Modelling & …, 2025 - Elsevier
The increasing availability of High-Resolution Digital Elevation Models (HRDEMs) allows
accurate delineation of stream and drainage flowlines at the field scale. However, the …

Mapping drainage ditches in forested landscapes using deep learning and aerial laser scanning

W Lidberg, SS Paul, F Westphal, KF Richter… - Journal of irrigation …, 2023 - ascelibrary.org
Extensive use of drainage ditches in European boreal forests and in some parts of North
America has resulted in a major change in wetland and soil hydrology and impacted the …