欧洲示范点机载激光扫描植被结构度量数据检索

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi
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引用次数: 0

摘要

该数据集提供了GeoTIFF格式的光栅化光探测和测距(LiDAR)指标的标准化集合,来源于五个欧洲国家七个示范站点的全国机载激光扫描(ALS)数据:Mols Bjerge国家公园(丹麦)、自然保护区(法国)、Oostvaardersplassen(荷兰)、索尔兹伯里平原(英国)、Knepp庄园(英国)、Monks Wood(英国)和Comino岛(马耳他)。这些遗址的面积从0.08平方公里到54平方公里不等,包括森林、阔叶和针叶林、小种植园、干湿草地、沼泽、芦苇床、耕地、农田、灌丛和地中海沼泽等生境类型。共计算35个LiDAR指标,其中28个代表植被结构属性。这些指标包括植被高度(7个指标)、植被覆盖(14个指标)和植被垂直变异性(7个指标)。此外,七个度量描述了点密度(一个度量)、特征值(三个度量)和法向量(三个度量)。光栅化的激光雷达指标具有10米的空间分辨率,覆盖范围和范围由对应于每个演示站点的形状文件定义。原始的ALS点云被裁剪到站点边界,并使用“Laserfarm”工作流进行处理,这是一个标准化的计算工作流,包括用于重新平铺、规范化、特征提取和栅格化的模块化管道。Laserfarm采用开源“Laserchicken”软件的特征提取模块来计算激光雷达指标。该工作流程是使用荷兰国家信息和通信技术设施SURF的IT服务实现的。除了来自马耳他科米诺的LiDAR点云外,裁剪后的LiDAR点云可以通过公共存储库获得。包括Comino在内的所有站点的35个光栅化激光雷达指标(GeoTIFF文件,10米分辨率)以及相应的站点边界形状文件(地理空间矢量格式)都提供在Zenodo存储库中。此外,用于执行Laserfarm工作流的带有Python代码的Jupyter notebook可用于促进再现性和进一步的计算应用。用户应注意,光栅化激光雷达指标可能包含零或NA值,特别是在水面上,脉冲穿透比指标可能表明水面上的植被覆盖率过高。用户可以重新分类或屏蔽相应的零值区域。一些像素显示异常的植被高度值,可以在分析前进行过滤。某些条纹模式,可能是由于重叠的航线和增加的点密度,出现在一些指标中,尽管它们的整体影响似乎很小。该数据集支持多种应用,包括冠层高度测量、树篱、树线和森林斑块制图,以及表征植被密度、垂直分层和栖息地开放性。它支持景观尺度的栖息地分析,并有助于从ALS数据中标准化植被指标,用于特定地点的生态监测(例如,Natura 2000)。此外,该数据集展示了激光雷达数据处理工作流程的自动化执行,这对于建立跨国、多站点的生物多样性和生态系统观测网络至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data of vegetation structure metrics retrieved from airborne laser scanning surveys for European demonstration sites
This dataset provides a standardized collection of rasterized Light Detection And Ranging (LiDAR) metrics in GeoTIFF format, derived from country-wide airborne laser scanning (ALS) data across seven demonstration sites in five European countries: Mols Bjerge National Park (Denmark), Reserve Naturelle Nationale du Bagnas (France), Oostvaardersplassen (Netherlands), Salisbury Plain (United Kingdom), Knepp Estate (United Kingdom), Monks Wood (United Kingdom), and the island of Comino (Malta). The sites range in areal size from 0.08 km2 to 54 km2 and include habitat types such as forests, broadleaf and conifer woodlands, small plantations, dry and wet grasslands, marshes, reedbeds, arable fields, farmland, scrublands and mediterranean garigue. A total of 35 LiDAR metrics were calculated, of which 28 represent vegetation structural attributes. These include vegetation height (seven metrics), vegetation cover (fourteen metrics), and vegetation vertical variability (seven metrics). Additionally, seven metrics describe point density (one metric), eigenvalues (three metrics), and normal vectors (three metrics). The rasterized LiDAR metrics have a spatial resolution of 10 m, with coverage and extent defined by shapefiles corresponding to each demonstration site. The raw ALS point clouds were clipped to the site boundaries and processed with the 'Laserfarm' workflow, a standardized computational workflow that includes modular pipelines for re-tiling, normalization, feature extraction, and rasterization. Laserfarm employs the feature extraction module of the open-source ‘Laserchicken’ software to compute the LiDAR metrics. The workflow was implemented using the IT services of the Dutch national facility for information and communication technology, SURF. The clipped LiDAR point clouds are available through a public repository, except for the LiDAR point clouds from Comino, Malta, which are not publicly available. The 35 rasterized LiDAR metrics (GeoTIFF files, 10 m resolution) from all sites, including Comino, as well as the corresponding site boundary shapefiles (geospatial vector format), are provided in a Zenodo repository. Additionally, the Jupyter Notebooks with Python code for executing the Laserfarm workflow are available to facilitate reproducibility and further computational applications. Users should note that the rasterized LiDAR metrics may contain zero or NA values, particularly over water surfaces, with the pulse penetration ratio metric potentially indicating false high vegetation cover over water. Users may reclassify or mask areas with zero values accordingly. Some pixels exhibit abnormal vegetation height values, which can be filtered before analysis. Certain striping patterns, likely resulting from overlapping flight lines and increased point density, are present in some metrics, though their overall impact appears minimal. This dataset enables diverse applications, including canopy height measurements, mapping of hedgerows, treelines, and forest patches, as well as characterizing vegetation density, vertical stratification, and habitat openness. It supports landscape-scale habitat analysis and contributes to the standardization of vegetation metrics from ALS data for site-specific ecological monitoring (e.g., Natura 2000). Moreover, the dataset demonstrates the automated execution of LiDAR data processing workflows, which is crucial for establishing a transnational and multi-site biodiversity and ecosystem observation network.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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