Published December 16, 2025 | Version v1
Dataset Open

Data for: "A multi-platform LiDAR dataset for standardized forest inventory measurement at long term ecological monitoring sites"

  • 1. ROR icon Free University of Bozen-Bolzano
  • 2. Free university of Bozen/Bolzano
  • 3. ROR icon University of Trento

Description

We present a curated multi-platform LiDAR dataset from the ICOS Renon site (IT-Ren) in the Italian Alps, designed to support forest inventories and the development of standardized monitoring protocols. The dataset integrates UAV-borne laser scanning (ULS) to measure canopy coverage, terrestrial laser scanning (TLS) for detailed stem mapping, and backpack mobile laser scanning (MLS) with real-time SLAM for efficient sub-canopy acquisition. We focus on the control plot with the most complete and internally consistent registration, where TLS point clouds ($\sim$333 million points) are complemented by ULS and MLS data capturing canopy and understory strata. Marker-free, SLAM-aware protocols were used to reduce field and processing time, while manual and automated methods were combined. Final products are available in LAZ and E57 formats with UTM coordinates, together with registration reports for reproducibility. The dataset provides a benchmark for testing registration methods, evaluating scanning efficiency, and linking point clouds with segmentation, quantitative structure models, and allometric biomass estimation. By situating the acquisitions at a long-term ICOS site, it also offers opportunities to connect 3D structure with decades of ecological and flux measurements. More broadly, it illustrates how TLS, MLS, and ULS can be combined for repeated inventories and digital twins of forest ecosystems.

Files

2024-11-13-leicaBLK360-icos-CP2.zip

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Additional details

Funding

European Commission
DIGIFOREST - Digital Analytics and Robotics for Sustainable Forestry 101070405
European Commission
Monitoraggio e Automazione Robotica Forestale (FORMA) EFRE1079
European Commission
Interconnected Nord-Est Innovation Ecosystem (iNEST) ECS00000043

Dates

Collected
2024-08-01/2024-11-21
Data collection