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Published October 16, 2024 | Version v1

Multi-temporal high-resolution data products of ecosystem structure derived from country-wide airborne laser scanning surveys of the Netherlands

  • 1. University of Amsterdam

Description

This data repository contains a set of multi-temporal data products of ecosystem structure derived from four national ALS surveys of the Netherlands (AHN1–AHN4) (folder: 1. Data_products). Four sets of 25 LiDAR-derived vegetation metrics representing ecosystem height, cover, and structural variability are provided at 10 m spatial resolution, providing valuable data sources for a wide range of ecological research and field beyond. All 25 LiDAR metrics were calculated using Laserfarm workflow  (https://laserfarm.readthedocs.io/en/latest/) (building on the user-extendable features from the “Laserchicken” software: https://laserchicken.readthedocs.io/en/latest/#features). All metrics are calculated with the normalized point cloud. More details on metric calculation are provided on GitHub (Laserchicken: https://github.com/eEcoLiDAR/laserchicken and Laserfarm: https://github.com/eEcoLiDAR/Laserfarm), as well as on the “Laserchicken” documentation page (https://laserchicken.readthedocs.io/en/latest/). We also provided masks to minimize the influence of water surfaces, buildings and roads, as well as powerlines in the data products (folder: 2. Masks).  Since the point density of each AHN dataset has changed significantly which may have influence on generated LiDAR metrics, we also provided the four raster layers of point density (all points) for each AHN dataset (folder: 3. Point_density). Two use cases demonstrated the utility of the presented data products: (use case 1) monitoring forest structural change across time using multi-temporal ALS data and (use case 2) comparison of vegetation structural difference within Natura 2000 sites. The used data are also provided (folder: 4. Use_case). Note that all the raster layers and shapefiles provided in this repository are under the local Dutch coordinate system “RD_new” (EPSG: 28992, NAP:5709).

Three subfolders are included:

1. Data_products

·       AHN1.zip

·       AHN2.zip

·       AHN3.zip

·       AHN4.zip

·       Maps

It contains four folders with 25 LiDAR metrics at 10 m resolution generated from each AHN dataset. The file names and their corresponding LiDAR metrics can be found in Table 1. An additional folder (Maps) contains the maps (.pdf format) of all 25 metrics for each AHN dataset.

2. Masks

·       ahn3_10m_mask_building_road_water.tif

·       ahn4_10m_mask_building_road_water.tif

·       ahn4_10m_mask_powerline.tif

It contains two mask layers of water surfaces, buildings and roads for both AHN3 and AHN4 data products based on the Dutch cadaster data (TOP10NL) from 2018 (corresponding to AHN3) and 2021 (corresponding to AHN4) (https://www.kadaster.nl/zakelijk/producten/geo-informatie/topnl). In the masks, water surfaces, buildings and roads were merged into one class with pixel value assigned to 1 and the rest has the pixel value of 0. There is also a powerline mask generated from the AHN4 dataset at 10 m resolution, where pixels containing powerlines were assigned a value of 1 and the rest as NoData. We provide those masks to minimize the inaccuracies of the data products caused by human infrastructures and water surfaces.

3. Point_density

·       ahn1_10m_point_density.tif

·       ahn2_10m_point_density.tif

·       ahn3_10m_point_density.tif

·       ahn4_10m_point_density.tif

It contains four raster layers (at 10 m resolution) representing the point density of each AHN dataset.

4. Use_case

1. Multi-temporal_AHN

·       Data

·       Usecase_multi-temporal_AHN.R

It contains the input data for the use case data processing (i.e. Data folder), including the shapefile of the area (i.e. shp folder), and extracted pixel value from six selected LiDAR metrics from AHN1–AHN5 (i.e. Metrics folder), and the selected LiDAR metrics of the area (e.g. Hp95 folder), and the R code for data processing (i.e. Usecase_multi-temporal_AHN.R).

2. Natura2000

·       Data

·       Natura2000_end2021_HABITATCLASS.csv

·       Natura2000_NL_habitat_grouped.csv

·       Usecase_Natura2000.R

It contains a folder of the input data used for the use case (i.e. Data folder), including the shapefile (i.e. shp folder) of the Natura 2000 sites in the Netherlands (i.e. Nature2000_NL_RDnew.shp) and the 100 random sample plots from each habitat type (e.g. woodland_points.shp), and the LiDAR metrics from AHN4 used for demonstrating the vegetation  structure within each habitat type (i.e. AHN4_metrics folder). The table “Natura2000_end2021_HABITATCLASS.csv” is the original attribute table of Natura 2000 sites, including information related to the description of habitat classes (column “DESCRIPTION”), the code corresponding to the habitat class (column “HABITATCODE”), the code for the specific site (column “SITECODE”), and the percentage of the cover of a specific habitat class in one site (column “PERCENTAGECOVER”). The table “Natura2000_NL_habitat_grouped.csv” contains two subtabs, one (i.e. “Habitatclass”) is the copy of the original attribute table of Natura 2000 sites in the Netherlands, and the other one (i.e. “Habitat_class_summary”) is the grouped habitat type based on the dominant habitat class (i.e. class with the highest percentage cover) in each site. Different colors indicate different habitat types, corresponding to the colors in the first tab (“Habitatclass”) where the dominant habitat class was highlighted for each site.

Code availability

Jupyter Notebooks for processing AHN datasets:

https://github.com/ShiYifang/AHN

Laserfarm workflow repository:

https://github.com/eEcoLiDAR/Laserfarm

Laserchicken software repository:

https://github.com/eEcoLiDAR/laserchicken

Code for downloading AHN dataset: https://github.com/ShiYifang/AHN/tree/main/AHN_downloading

Code for generating masks for AHN datasets: https://github.com/ShiYifang/AHN/tree/main/AHN_masks

Code for demonstration of ecological use cases: https://github.com/ShiYifang/AHN/tree/main/Use_case

 

 

Files

1_Data_products.zip

Files (63.7 GB)

Name Size
md5:5de0df94f5604fab2a3f928c7e7a1b11
60.4 GB Preview Download
md5:459f7842b85a7f588e43918eb4590b1a
128.4 MB Preview Download
md5:2a19f53f2e93b6ff084d972dcb3b8e6d
3.2 GB Preview Download
md5:63e5a43905d8fb25d69e7274c5453c5e
12.5 MB Preview Download
md5:7008db6ef748897a2cd47af8b406fa84
28.7 kB Download

Additional details

Related works

References
Publication: 10.1016/j.ecoinf.2022.101836 (DOI)
Publication: 10.1016/j.dib.2022.108798 (DOI)
Publication: 10.1016/j.softx.2020.100626 (DOI)

Funding

European Commission
MAMBO - Modern Approaches to the Monitoring of BiOdiversity 101060639

Dates

Created
2024-10-16

Software

Repository URL
https://github.com/ShiYifang/AHN
Programming language
Python