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Dataset

 

ForestScan Project: Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS) and Terrestrial Laser Scanning (TLS) data of FBRMS-01: Paracou, French Guiana plot 6, 10th October to 15th November 2019

Latest Data Update: 2025-03-29
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2025-03-28
DOI Publication Date: 2025-03-28
Download Stats: last 12 months
Dataset Size: 7.0K Files | 224GB

Abstract

This dataset contains LiDAR scanning derived products (raw scanner data, geo-located point clouds, individual 3D tree models) collected over the north-eastern part (200 m x 200 m) of FBRMS-01: Paracou, French Guiana plot 6. The campaign took place from the 10th of October to the 15th of November 2019. Terrestrial LiDAR Scanning (TLS) was conducted on a regular grid with spacing of 10 m with a RIEGL VZ-400 scanner and retro-reflective targets for scan registration. Unpiloted Aerial Vehicle Laser Scanning (UAV-LS) was conducted with a RIEGL Ricopter with VUX-SYS VUX-1UAV system with varying flight heights and flight directions.

The TLS point clouds were collected to produce explicit 3D models of individual trees and subsequently estimate their above-ground biomass (AGB). The UAV-LS point clouds were collected to test scanner settings and inspect point clouds properties, in particular with regard to their suitability to model individual trees and their AGB.

The campaign was conducted by researchers Benjamin Brede, Harm Bartholomeus and Alvaro Lau of the Laboratory of Geo-Information Science and Remote Sensing of Wageningen University & Research (The Netherlands) with support from Nicolas Barbier of AMAP Lab (Botany and Modeling of Plant Architecture and Vegetation).

Citable as:  Brede, B.; Barbier, N.; Bartholomeus, H.; Derroire, G.; Lau, A.; Lusk, D.; Herold, M. (2025): ForestScan Project: Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS) and Terrestrial Laser Scanning (TLS) data of FBRMS-01: Paracou, French Guiana plot 6, 10th October to 15th November 2019. NERC EDS Centre for Environmental Data Analysis, 28 March 2025. doi:10.5285/325a4dde60d142049339e0c84816aac1. https://dx.doi.org/10.5285/325a4dde60d142049339e0c84816aac1

Abbreviation: Not defined
Keywords: ForestScan project, GEO-TREES, BIOMASS mission, European Space Agency (ESA), Earth Observation (EO) calibration/validation, Terrestrial LiDAR Scanning (TLS), Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS), Aerial LiDAR Scanning (ALS), Digital twins, Above Ground Biomass (AGB) estimates, Carbon estimates, Forest structure

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s):
http://creativecommons.org/licenses/by/4.0/
When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). The UCL team provided revised metadata for the catalogue record

Data Quality:
Data were validated by the Forestscan project team and provided to CEDA for archival.
File Format:
Raw and Point cloud

Process overview

This dataset was generated by a combination of instruments deployed on platforms and computations as detailed below.

Instrument/Platform pairings

Riegl Minivux and Applanix20 Deployed on: Matrice 600 Drone

Computation Element: 1

Title TLS2trees: a semi-automated processing pipeline
Abstract Plot-level point clouds were processed using TLS2trees which is a set of Python command line tools & designed to be horizontally scalable, e.g., on a High Performance Computing (HPC) facility. Pipeline steps: 1) Point cloud re-processing, 2) semantic segmentation into wood & leaf point classes, 3) instance segmentation into sets of point clouds representing individual trees, 4) Quantitative structural models (QSMs) of individual tree point clouds, & 5) Plot biophysical & AGB estimates.
Input Description None
Output Description None
Software Reference None
Output Description

None

No variables found.

Coverage
Temporal Range
Start time:
2019-10-10T00:00:00
End time:
2019-11-15T00:00:00
Geographic Extent

 
5.2804°
 
-52.9212°
 
-52.0326°
 
5.2628°