Extracted tree and shrub vegetation from airborne laser scanning (AHN4) in the Oostvaardersplassen wetland, the Netherlands
Woody vegetation such as willow (Salix spp.) and elder (Sambucus nigra) forms an important structural component of the reedbed ecosystem in the Oostvaardersplassen nature reserve in the Netherlands. These tree and shrub species provide essential forage for large herbivores, including red deer (Cervus elaphus), and play a key role in vegetation dynamics, grazing impacts, and ecological succession within the wetland.
Mapping woody vegetation across extensive and often inaccessible reedbed habitats is challenging using field-based approaches alone. Airborne laser scanning (ALS) provides a robust alternative by capturing detailed three-dimensional vegetation structure in the form of dense point clouds. This repository documents a LiDAR-derived dataset of extracted woody vegetation, primarily willow and elder, generated from the Dutch national airborne laser scanning dataset AHN4.
The dataset was created in the context of the Modern Approaches to the Monitoring of BiOdiversity (MAMBO) project and supports the development and testing of scalable workflows for deriving habitat condition indicators from airborne LiDAR data. It contributes to the broader objective of enabling consistent, reproducible, and spatially explicit habitat condition assessment using national and transnational airborne laser scanning datasets.<div><br></div><div>Data contents</div><div>The repository is organised into six sub-folders (see README file):</div><div>[1_Input_vegetation_points]
Vegetation-classified airborne laser scanning point clouds for the marsh area in Oostvaardersplassen, subset from the AHN4 dataset (classification ID = 1). Data are provided in standard LAS format.</div><div>[2_Extracted_trees_shrubs_points]
LiDAR point clouds containing only the extracted trees and shrubs, provided in LAS format. These files can be visualised and analysed using standard point cloud software (e.g. CloudCompare, ArcGIS Pro).</div><div>[3_Scripts]
Two Python scripts used for post-processing:
- 1_generate_tiff.py: converts extracted tree and shrub LAS files into GeoTIFF raster layers.
- 2_generate_boundary.py: converts the GeoTIFF rasters into vector boundary polygons (ESRI Shapefile format).</div><div>[4_GeoTIFFsamp;shapefiles]
Derived raster and vector products, including:
- GeoTIFF rasters of extracted trees and shrubs at 1 m spatial resolution.
- Vector boundary polygons of extracted woody vegetation derived from the GeoTIFF products (ESRI Shapefile format).</div><div>[5_Marsh_area]
Boundary polygon (ESRI Shapefile) of the marsh study area in Oostvaardersplassen</div><div>[6_OVP_area] Boundary polygon (ESRI Shapefile) of the Oostvaardersplassen nature reserve.</div><div><br></div><div>
Together, the repository provides raw vegetation-classified LiDAR inputs, extracted woody vegetation point clouds, derived raster and vector products, and the scripts required for post-processing. This structured data package enables reproducible analysis of woody vegetation distribution and structure in wetland environments and provides a methodological foundation for scaling tree and shrub extraction workflows to larger spatial extents using national and transnational airborne laser scanning datasets.<br><div><br></div></div>
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IdentificationAbout this resource
- Alternate Identifier
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53cbe922-eda1-4266-b43b-62fe4c8972f4
- Publication Date
- 2026-02-11
- Title
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Extracted tree and shrub vegetation from airborne laser scanning (AHN4) in the Oostvaardersplassen wetland, the Netherlands
- Short Name
- Abstract
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Woody vegetation such as willow (Salix spp.) and elder (Sambucus nigra) forms an important structural component of the reedbed ecosystem in the Oostvaardersplassen nature reserve in the Netherlands. These tree and shrub species provide essential forage for large herbivores, including red deer (Cervus elaphus), and play a key role in vegetation dynamics, grazing impacts, and ecological succession within the wetland.
Mapping woody vegetation across extensive and often inaccessible reedbed habitats is challenging using field-based approaches alone. Airborne laser scanning (ALS) provides a robust alternative by capturing detailed three-dimensional vegetation structure in the form of dense point clouds. This repository documents a LiDAR-derived dataset of extracted woody vegetation, primarily willow and elder, generated from the Dutch national airborne laser scanning dataset AHN4.
The dataset was created in the context of the Modern Approaches to the Monitoring of BiOdiversity (MAMBO) project and supports the development and testing of scalable workflows for deriving habitat condition indicators from airborne LiDAR data. It contributes to the broader objective of enabling consistent, reproducible, and spatially explicit habitat condition assessment using national and transnational airborne laser scanning datasets.<div><br></div><div>Data contents</div><div>The repository is organised into six sub-folders (see README file):</div><div>[1_Input_vegetation_points]
Vegetation-classified airborne laser scanning point clouds for the marsh area in Oostvaardersplassen, subset from the AHN4 dataset (classification ID = 1). Data are provided in standard LAS format.</div><div>[2_Extracted_trees_shrubs_points]
LiDAR point clouds containing only the extracted trees and shrubs, provided in LAS format. These files can be visualised and analysed using standard point cloud software (e.g. CloudCompare, ArcGIS Pro).</div><div>[3_Scripts]
Two Python scripts used for post-processing:
- 1_generate_tiff.py: converts extracted tree and shrub LAS files into GeoTIFF raster layers.
- 2_generate_boundary.py: converts the GeoTIFF rasters into vector boundary polygons (ESRI Shapefile format).</div><div>[4_GeoTIFFsamp;shapefiles]
Derived raster and vector products, including:
- GeoTIFF rasters of extracted trees and shrubs at 1 m spatial resolution.
- Vector boundary polygons of extracted woody vegetation derived from the GeoTIFF products (ESRI Shapefile format).</div><div>[5_Marsh_area]
Boundary polygon (ESRI Shapefile) of the marsh study area in Oostvaardersplassen</div><div>[6_OVP_area] Boundary polygon (ESRI Shapefile) of the Oostvaardersplassen nature reserve.</div><div><br></div><div>
Together, the repository provides raw vegetation-classified LiDAR inputs, extracted woody vegetation point clouds, derived raster and vector products, and the scripts required for post-processing. This structured data package enables reproducible analysis of woody vegetation distribution and structure in wetland environments and provides a methodological foundation for scaling tree and shrub extraction workflows to larger spatial extents using national and transnational airborne laser scanning datasets.<br><div><br></div></div>
- Dataset Language
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en
- Dataset Creator
- Dataset Creator
- Metadata Provider
- Dataset Contact
- Keywords (None)
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trees and shrubs
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LiDAR
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Airborne Laser Scanning
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point clouds
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vegetation structure
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woody vegetation
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tree and shrub extraction
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wetland ecosystems
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reedbeds
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habitat condition
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grazing impacts
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habitat monitoring
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biodiversity monitoring
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MAMBO project
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Earth Sciences
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Environmental Sciences
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Ecology
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Geoinformatics
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Temporal Coverage
Range of Dates
- Begin Date
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2020-03-01
- End Date
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2022-03-31
resourceLicensesLicense Information
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CC-BY4.0
Resource License
- License Name
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Creative Commons Attribution 4.0 International
- Acknowledgements
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Online
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DOI
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Zenodo
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Online
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1_Input_vegetation_points.zip
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Online
- A brief description of the the content of online URL.
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2_Extracted_trees_shrubs_points.zip
Distribution
Online
- A brief description of the the content of online URL.
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3_Scripts.zip
Distribution
Online
- A brief description of the the content of online URL.
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4_GeoTIFFsshapefiles.zip
Distribution
Online
- A brief description of the the content of online URL.
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5_Marsh_area.zip
Distribution
Online
- A brief description of the the content of online URL.
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6_OVP_area.zip
Distribution
Online
- A brief description of the the content of online URL.
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ReadMe.txt
Project
• Project
- Title
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MAMBO - Modern Approaches to the Monitoring of BiOdiversity
- Abstract
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Funded by European Commission (MAMBO project: 101060639).
Personnel
- Organization Name
Individual Name
- Given Name
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