Classifying Ditch and Stream Channels Mapped From High-Resolution Digital Elevation Models Using Machine Learning
Documentation files
Documentation files
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
Research principal:
Principal's reference number:
- SLU.seksko.2024.4.4.IÄ-1
Data contains personal data:
Yes
Type of personal data:
Names of user accounts indicating who performed certain steps of the data processing.
Citation:
Language:
Method and outcome
Method and outcome
Data format/data structure:
Data collection - Computer-based observation
Data collection - Computer-based observation
Mode of collection:
Computer-based observation
Description of the mode of collection:
Professionals from the Swedish Forest Agency manually digitized the ditches within the 12 study areas spread across Sweden based on the hillshade and high-pass median filter obtained from the DEM. Historical photos and current ortophotos (resolution ranging from 0.17-0.5 m), the ditches were manually digitized. Streams were mapped by initially detecting all natural channel heads, then tracing the downstream channels, and finally manually editing them based on ortophotos.
Source of the data:
- Geographic area
Spatial resolution:
0.5 metres scale
Instrument
Instrument
Name:
GIS software
Geographic coverage
Geographic coverage
Geographic description:
The data covers 12 study areas spread across Sweden, containing information related to channel type for small water channels. More information with the precise locations can be found at the README.pdf file.
Administrative information
Administrative information
Responsible department/unit:
Department of Forest Ecology and Management
Contributor(s):
Funding
Funding
Funding agency:
- Marianne and Marcus Wallenberg Foundation
Opens a new window at ror.org.
ROR
Award title:
WASP-HS
Funding information:
This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society (WASP-HS) funded by the Marianne and Marcus Wallenberg Foundation https://wasp-hs.org/
Topic and keywords
Topic and keywords
Swedish Standard Classification of Research Subjects 2025:
INSPIRE topic categories:
Relations
Relations
Publications
Publications
Citation:
ISBN:
9789181240658
Citation:
SwePub:
Metadata
Metadata
