Abstract
Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark's publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark's terrestrial surface. The resulting data set is comparatively small (~ 87 GB, compressed 16.4 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond.
Highlights
Over the last decades, airborne laser scanning (ALS) has become an established data source for providing fine-resolution measures of terrain and vegetation structure in ecological research (Moeslund et al, 2019; Guo et al, 2017; Zellweger et al., 2016)
The raw signal is processed by the survey provider and the resulting data is delivered to the end user in the form of a point cloud of discrete returns, where each point is associated with information on geographic location, return strength, acquisition timing etc. (Vo et al, 2016)
The amplitude attributes in the Danish elevation model (DHM)/Point-cloud point clouds are not directly comparable when points originate from different point sources, as the amplitude has not been calibrated and is sensitive to differences in sensor, sensor configuration and signal processing
Summary
Airborne laser scanning (ALS) has become an established data source for providing fine-resolution measures of terrain and vegetation structure in ecological research (Moeslund et al, 2019; Guo et al, 2017; Zellweger et al., 2016). The low uptake is likely a consequence of the considerable challenges that remain in handling these very large data sets, which require specialist expertise and software, as well as substantial amounts of data storage and processing power (Meijer et al, 2020; Vo et al, 2016; Pfeifer et al, 2014) We address this issue for Denmark by providing a compact set of ecologically relevant measures of terrain characteristics and vegetation structure derived as raster outputs from the country's national ALS data set with a grain size of 10 m x 10 m. We hope that ease of access and thorough documentation of the EcoDes-DK15 data set will encourage uptake and facilitate the development of future versions of similar data sets in Denmark and beyond
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call