2024/11/25 by Samantha Wittke, Mariana Campos, Lassi Ruoppa +6 · 1 voice
Environmental Science · #Remote Sensing in Agriculture #Remote Sensing and LiDAR Applications #Forest ecology and management
paper · pdf · doi:10.1038/s41597-024-04143-w
openalex publication_date 2024/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
In the present paper, we introduce a high-resolution spatiotemporal point cloud time series, acquired using a LiDAR sensor mounted 30 metres above ground on a flux observation tower monitoring a boreal forest. The dataset comprises a 18-month long (April 2020 - September 2021) time series with an average interval of 3.5 days between observations. The data acquisition, transfer, and storage systems established at Hyytiälä (Finland) are named the LiDAR Phenology station (LiPhe). The dataset consists of 103 time points of LiDAR point clouds covering a total of 458 individual trees, comprising three distinct Boreal species. Additional reference information includes the respective location, the species, and the initial height (at the first time point) of each individual tree. The processing scripts are included to outline the workflow used to generate the individual tree point clouds (LiPheKit). The presented dataset offers a comprehensive insight into inter- and intra-species variations of the individual trees regarding their growth strategies, phenological dynamics, and other functioning processes over two growth seasons.