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 …

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 …

[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 …

Assessing the impacts of anthropogenic drainage structures on hydrologic connectivity using high‐resolution digital elevation models

S Bhadra, R Li, D Wu, G Wang… - Transactions in …, 2021 - Wiley Online Library
Delineating accurate flowlines using digital elevation models is a critical step for overland
flow modeling. However, extracting surface flowlines from high‐resolution digital elevation …

[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 …

A multi-scale mapping approach based on a deep learning CNN model for reconstructing high-resolution urban DEMs

L Jiang, Y Hu, X Xia, Q Liang, A Soltoggio, SR Kabir - Water, 2020 - mdpi.com
The scarcity of high-resolution urban digital elevation model (DEM) datasets, particularly in
certain developing countries, has posed a challenge for many water-related applications …

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 …

Assessment of digital elevation models based on the drainage morphometric parameters for the Tawi River Basin

RV Kale, PG Jose, AK Taloor, R Kumar - Advanced Modelling and …, 2022 - Springer
Digital elevation models (DEMs) datasets are the fundamental input data for the conduction
of the hydrologic, hydraulic, geomorphologic and ecohydrological modelling studies. Many …

Extensibility of U-Net neural network model for hydrographic feature extraction and implications for hydrologic modeling

LV Stanislawski, EJ Shavers, S Wang, Z Jiang… - Remote Sensing, 2021 - mdpi.com
Accurate maps of regional surface water features are integral for advancing ecologic,
atmospheric and land development studies. The only comprehensive surface water feature …

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

Q Wu, CR Lane - Hydrology and earth system sciences, 2017 - hess.copernicus.org
In traditional watershed delineation and topographic modeling, surface depressions are
generally treated as spurious features and simply removed from a digital elevation model …