lidR: An R package for analysis of Airborne Laser Scanning (ALS) data

Roussel Jean-Romain, Auty David, Coops Nicholas C., Tompalski Piotr, Goodbody Tristan R.H., Sánchez Meador Andrew, Bourdon Jean-François, De Boissieu Florian, Achim Alexis. 2020. lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment, 251:112061, 15 p.

Quartile : Outlier, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Outlier, Sujet : IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY / Quartile : Outlier, Sujet : REMOTE SENSING

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Géographie-Aménagement-Urbanisme-Architecture

Résumé : Airborne laser scanning (ALS) is a remote sensing technology known for its applicability in natural resources management. By quantifying the three-dimensional structure of vegetation and underlying terrain using laser technology, ALS has been used extensively for enhancing geospatial knowledge in the fields of forestry and ecology. Structural descriptions of vegetation provide a means of estimating a range of ecologically pertinent attributes, such as height, volume, and above-ground biomass. The efficient processing of large, often technically complex datasets requires dedicated algorithms and software. The continued promise of ALS as a tool for improving ecological understanding is often dependent on user-created tools, methods, and approaches. Due to the proliferation of ALS among academic, governmental, and private-sector communities, paired with requirements to address a growing demand for open and accessible data, the ALS community is recognising the importance of free and open-source software (FOSS) and the importance of user-defined workflows. Herein, we describe the philosophy behind the development of the lidR package. Implemented in the R environment with a C/C++ backend, lidR is free, open-source and cross-platform software created to enable simple and creative processing workflows for forestry and ecology communities using ALS data. We review current algorithms used by the research community, and in doing so raise awareness of current successes and challenges associated with parameterisation and common implementation approaches. Through a detailed description of the package, we address the key considerations and the design philosophy that enables users to implement user-defined tools. We also discuss algorithm choices that make the package representative of the 'state-of-the-art' and we highlight some internal limitations through examples of processing time discrepancies. We conclude that the development of applications like lidR are of fundamental importance for developing transparent, flexible and open ALS tools to ensure not only reproducible workflows, but also to offer researchers the creative space required for the progress and development of the discipline.

Mots-clés Agrovoc : télédétection, gestion des ressources naturelles, aménagement forestier, écologie, modèle de simulation, traitement des données, conditionnement, analyse de données

Mots-clés libres : LiDAR, LidR, R, Airborne laser scanning (ALS), Software, Forestry

Auteurs et affiliations

• Roussel Jean-Romain, Université Laval (CAN) - auteur correspondant
• Auty David, Northern Arizona University (USA)
• Coops Nicholas C., University of British Columbia (CAN)
• Tompalski Piotr, University of British Columbia (CAN)
• Goodbody Tristan R.H., University of British Columbia (CAN)
• Sánchez Meador Andrew, Northern Arizona University (USA)
• Bourdon Jean-François, Ministère des Forêts, de la Faune et des Parcs du Québec (CAN)
• De Boissieu Florian, CIRAD-PERSYST-UMR Eco&Sols (FRA)
• Achim Alexis, Université Laval (CAN)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/605400/)

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