Classifying Ditch and Stream Channels Mapped From High-Resolution Digital Elevation Models Using Machine Learning
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Date
2026-06-23
Journal Title
Journal ISSN
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Publisher
Swedish University of Agricultural Sciences
Abstract
Description
This data contains the digital elevation models with 0.5 m resolution and polyline shapefiles with the location of channels from the 12 study areas used in this study.
It also has the scripts to generate the datasets used to train the machine learning model to classify channels into ditches and streams, and calculate the hydrological indices. The code to train the model is also included, along with the models obtained.
For the ground truth data, the channels were mapped differently based on their type: ditches were manually digitized based on the visual analysis of some topographic indices and orthophotos obtained from the DEM. Streams were mapped by initially detecting all natural channel heads, then tracing the downstream channels, and finally manually editing them based on orthophotos.
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Keywords
Multidisciplinary Geosciences, Physical Geography, Soil Science, Imagery / Base Maps / Earth Cover, Geoscientific Information, Elevation, Location, Inland Waters, RIVERS/STREAMS, WATER CHANNELS, digital elevation model, Hydrography, ditches, machine learning, artificial intelligence, lidar