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 …

[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 …

[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 …

Global mapping of river sediment bars

PE Carbonneau, S Bizzi - Earth Surface Processes and …, 2024 - Wiley Online Library
Recently, deep learning has been increasingly applied to global mapping of land‐use and
land‐cover classes. However, very few studies have addressed the problem of separating …

An attention U-Net model for detection of fine-scale hydrologic streamlines

Z Xu, S Wang, LV Stanislawski, Z Jiang… - … Modelling & Software, 2021 - Elsevier
Surface water is an irreplaceable resource for human survival and environmental
sustainability. Accurate, finely detailed cartographic representations of hydrologic …

Estimation of Small-Stream Water Surface Elevation Using UAV Photogrammetry and Deep Learning

R Szostak, M Pietroń, P Wachniew, M Zimnoch… - Remote Sensing, 2024 - mdpi.com
Unmanned aerial vehicle (UAV) photogrammetry allows the generation of orthophoto and
digital surface model (DSM) rasters of terrain. However, DSMs of water bodies mapped …

Classification and feature extraction for hydraulic structures data using advanced cnn architectures

S Talafha, D Wu, B Rekabdar, R Li… - 2021 Third International …, 2021 - ieeexplore.ieee.org
An efficient feature selection method can significantly boost results in classification
problems. Despite ongoing improvement, hand-designed methods often fail to extract …

Locating charcoal production sites in Sweden using LiDAR, hydrological algorithms, and deep learning

DS Davis, J Lundin - Remote Sensing, 2021 - mdpi.com
Over the past several centuries, the iron industry played a central role in the economy of
Sweden and much of northern Europe. A crucial component of iron manufacturing was the …

The applicability of automated marine clay gully delineation using deep learning in Norway

AJ Ganerød, M van Boeckel… - Earth Surface Processes …, 2024 - Wiley Online Library
Gullies and ravines are common landforms in raised marine fine‐grained deposits in
Norway. Gullies in marine clay are significant landforms indicative of soil erosion and natural …

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 …