UAV-LIDAR and RGB imagery reveal intraspecific variability of morphometric traits in two Mediterranean pines

  1. Lombardi, Erica 1
  2. Rodríguez Puerta, Francisco 2
  3. Santini, Filippo 1
  4. Chambel, Maria Regina 3
  5. Climent, Jose 3
  6. Resco De Dios, Víctor 1
  7. Voltas, Jordi 1
  1. 1 (Universitat de Lleida. Joint Research Unit CTFC-Agrotecnio-Cerca Center)
  2. 2 (Universidad de Valladolid. EiFAB-iuFOR)
  3. 3 (Centro de Investigación Forestal (CIFOR-INIA-CSIC))
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Éditorial: Repositori de Dades de Recerca

Année de publication: 2022

Type: Dataset

DOI: 10.34810/DATA561 GOOGLE SCHOLAR lock_openAccès ouvert editor

Résumé

We evaluate the potential of LiDAR and RGB imagery obtained through unmanned aerial vehi-cles (UAVs) as high-throughput phenotyping tools for the characterization of tree growth and crown structure in two representative Mediterranean pine species (P. nigra and P. halepensis). Both UAV-based methods were then tested for their accuracy to detect genotypic differentiation among Pinus nigra and Pinus halepensis populations and their subspecies (black pine) or ecotypes (Aleppo pine). We investigated the possible relation between intraspecific variation of morphometric traits and life-history strategies of populations by correlating traits to climate factors at origin of pop-ulations. Finally, we investigated which traits distinguished better among black pine subspecies or Aleppo pine ecotypes. The data included raw values of morphometric traits derived from LiDAR and RGB-UAVs and measured in situ, populations means of statistically relevant morphometric traits and climate variables at site, and subspecies (P. nigra) and ecotypes (P. halepensis) means of statistically significant morphometric traits.