Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in PortugalShort Communication
- Juan Guerra Hernandez
- Eduardo González Ferreiro
- Alexandre Sarmento
- João Silva
- Alexandra Nunes
- Alexandra Cristina Correia
- Luis Fontes
- Maria Margarida Branco de Brito Tavares Tomé
- Ramón Alberto Díaz Varela
ISSN: 2171-5068
Year of publication: 2016
Volume: 25
Issue: 2
Pages: 16
Type: Article
More publications in: Forest systems
Metrics
Cited by
JCR (Journal Impact Factor)
- Year 2016
- Journal Impact Factor: 0.893
- Journal Impact Factor without self cites: 0.848
- Article influence score: 0.269
- Best Quartile: Q3
- Area: FORESTRY Quartile: Q3 Rank in area: 38/64 (Ranking edition: SCIE)
SCImago Journal Rank
- Year 2016
- SJR Journal Impact: 0.434
- Best Quartile: Q2
- Area: Soil Science Quartile: Q2 Rank in area: 56/143
- Area: Forestry Quartile: Q2 Rank in area: 52/165
- Area: Ecology, Evolution, Behavior and Systematics Quartile: Q3 Rank in area: 345/648
Scopus CiteScore
- Year 2016
- CiteScore of the Journal : 1.7
- Area: Forestry Percentile: 67
- Area: Soil Science Percentile: 50
- Area: Ecology, Evolution, Behavior and Systematics Percentile: 43
Abstract
Aim of study: The study aims to analyse the potential use of low‑cost unmanned aerial vehicle (UAV) imagery for the estimation of Pinus pinea L. variables at the individual tree level (position, tree height and crown diameter).Area of study: This study was conducted under the PINEA project focused on 16 ha of umbrella pine afforestation (Portugal) subjected to different treatments.Material and methods: The workflow involved: a) image acquisition with consumer‑grade cameras on board an UAV; b) orthomosaic and digital surface model (DSM) generation using structure-from-motion (SfM) image reconstruction; and c) automatic individual tree segmentation by using a mixed pixel‑ and region‑based based algorithm.Main results: The results of individual tree segmentation (position, height and crown diameter) were validated using field measurements from 3 inventory plots in the study area. All the trees of the plots were correctly detected. The RMSE values for the predicted heights and crown widths were 0.45 m and 0.63 m, respectively.Research highlights: The results demonstrate that tree variables can be automatically extracted from high resolution imagery. We highlight the use of UAV systems as a fast, reliable and cost‑effective technique for small scale applications.Keywords: Unmanned aerial systems (UAS); forest inventory; tree crown variables; 3D image modelling; canopy height model (CHM); object‑based image analysis (OBIA), structure‑from‑motion (SfM). ERRATUM PDF
Bibliographic References
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