EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set

Eighteen high-resolution ecological descriptors of vegetation and terrain for Denmark "EcoDes-DK15"

The data are derived from the nationwide airborne laser scanning / LiDAR campaign of Denmark from 2014-2015 provided by the Danish Agency for Data Supply and Efficiency.

Detailed documentation for the data set can be found in the accompanying manuscript and GitHub repository:

Assmann, J. J., Moeslund, J. E., Treier, U. A., and Normand, S.: EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-222, in review, 2021.

https://github.com/jakobjassmann/ecodes-dk-lidar

Files are compressed using bzip2 and tar archiving. The compressed archives can be extracted using commonly available archiving tools (for example 7z on Windows, the archiving tool on macOS and bz2 on Linux).  

A small example "teaser" subset (5 MB) of the data set, covering the Husby Klit area from Figure 6 in the manuscript, can be found here.

Abstract (from manuscript)

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. 

Acknowledgements (from manuscript)

We would like to thank Andràs Zlinszky for his contributions to earlier versions of the data set and Charles Davison for feedback regarding data use and handling. Funding for this work was provided by the Carlsberg Foundation (Distinguished Associate Professor Fellowships) and Aarhus University Research Foundation  (AUFF-E-2015-FLS-8-73) to Signe Normand (SN). This work is a contribution to SustainScapes – Center for Sustainable Landscapes under Global Change (grant NNF20OC0059595 to SN).

18项丹麦植被与地形高分辨率生态描述数据集（EcoDes-DK15）

本数据集源自丹麦数据供应与效率署提供的2014-2015年全国机载激光扫描/光探测与测距（LiDAR）作业数据。

该数据集的详细说明可参阅配套研究论文及GitHub代码仓库：

Assmann, J. J., Moeslund, J. E., Treier, U. A. 与 Normand, S.：EcoDes-DK15：基于丹麦全国机载激光扫描数据集生成的植被与地形高分辨率生态描述数据，《地球系统科学数据讨论》（Earth Syst. Sci. Data Discuss.）[预印本]，https://doi.org/10.5194/essd-2021-222，已投稿待审，2021年。

https://github.com/jakobjassmann/ecodes-dk-lidar

数据集文件采用bzip2压缩与tar归档格式，可通过通用归档工具解压（例如Windows平台的7z、macOS自带归档工具及Linux平台的bz2工具）。

数据集包含一个小型示例"预告"子集（5 MB），覆盖论文图6中的赫斯比克利特（Husby Klit）区域，可在此处获取。

【论文摘要】
生物多样性研究可从当代遥感技术（如光探测与测距（LiDAR））获取的生态系统结构三维数据中大幅获益。尽管此类区域及国家级尺度的数据可用性不断提升，但普通生态学者因对计算能力与遥感知识的要求较高，难以获取此类数据。我们处理了丹麦2014/2015年公开的全国机载激光扫描（ALS, Airborne Laser Scanning）数据集及配套高程模型，计算得到70个适用于生态学研究的栅格化描述指标。这些数据产品的栅格分辨率为10米，覆盖丹麦近全部陆地表面的逾4万平方公里区域，提供了包括植被高度、结构与密度在内的高分辨率测量数据，以及包括高程、坡向、坡度与湿度在内的地形描述指标。最终生成的数据集规模相对较小（未压缩约87 GB，压缩后为16.4 GB），且栅格数据可轻松集成至多数生态学者熟悉的软件分析流程中（地理信息系统（GIS, Geographic Information System）软件、R语言、Python）。处理流程的源代码与文档可通过代码仓库公开获取，既支持迁移至其他机载激光扫描数据集，也可用于修改或重新计算丹麦全国机载激光扫描数据集的未来版本。我们期望这套高分辨率植被与地形生态描述数据集（EcoDes-DK15）能为其他国家与地区发布同类数据集提供启发，同时希望这套栅格数据集能为丹麦及全球范围内当前与未来的生物多样性研究提供生态系统结构基线数据。

【致谢】
我们感谢安德拉斯·兹林斯基（Andràs Zlinszky）为本数据集早期版本提供的贡献，以及查尔斯·戴维森（Charles Davison）针对数据使用与处理提供的反馈。本研究的资助来自嘉士伯基金会（Distinguished Associate Professor Fellowships）与奥胡斯大学研究基金会（AUFF-E-2015-FLS-8-73），资助对象为西格妮·诺曼（Signe Normand，SN）。本研究是"全球变化下可持续景观中心（SustainScapes – Center for Sustainable Landscapes under Global Change）"的成果之一（资助编号NNF20OC0059595，资助对象为SN）。