LiDAR (light detection and ranging) sensors, mounted on UAVs (unmanned aerial vehicles), are a consolidated technology for the remote sensing of the urban and/or natural structural parameters. This study investigates a practical aspect of the advantages of drone UAV LiDAR systems in estimating the main dendrometric parameters in a Calabrian laricio pine forest. In particular, the criteria of hypsometric dendrometry were applied, in which, unlike the classic criteria based on field surveys only, the variable to be determined is the diameter of the individual trees rather than the height. In fact, this last variable is definitely more available for more shafts than the diameter, thanks to LiDAR surveys. Dendrometric variables, such as trees’ density, diameter and height, were measured adopting classic field-based methods for all the trees within some survey sample areas (SSAs), and other mean parameters were then obtained (e.g., mean basal area, mean diameter, mean Lorey’s height, above ground trees’ volume). The same parameters, retrieved by integrating hypsometric dendrometry and LiDAR data, were thus compared, and the degree of correlation/error was calculated. The error degree, obtained by comparing the field-measured diameters with the respective ones predicted using the LiDAR-based hypsometric model (R2 = 0.62; RMSE = 11.30 cm; Bias = 0.48 cm), confirmed the reliability of LiDAR systems for their practical application in the professional forestry sector.

UAV LiDAR Survey for Forest Structure Metrics Estimation in Planning Scenario. A Case Study on a Laricio Pine Forest in the Sila Mountains (Southern Italy)

Modica Giuseppe
Ultimo
2023-01-01

Abstract

LiDAR (light detection and ranging) sensors, mounted on UAVs (unmanned aerial vehicles), are a consolidated technology for the remote sensing of the urban and/or natural structural parameters. This study investigates a practical aspect of the advantages of drone UAV LiDAR systems in estimating the main dendrometric parameters in a Calabrian laricio pine forest. In particular, the criteria of hypsometric dendrometry were applied, in which, unlike the classic criteria based on field surveys only, the variable to be determined is the diameter of the individual trees rather than the height. In fact, this last variable is definitely more available for more shafts than the diameter, thanks to LiDAR surveys. Dendrometric variables, such as trees’ density, diameter and height, were measured adopting classic field-based methods for all the trees within some survey sample areas (SSAs), and other mean parameters were then obtained (e.g., mean basal area, mean diameter, mean Lorey’s height, above ground trees’ volume). The same parameters, retrieved by integrating hypsometric dendrometry and LiDAR data, were thus compared, and the degree of correlation/error was calculated. The error degree, obtained by comparing the field-measured diameters with the respective ones predicted using the LiDAR-based hypsometric model (R2 = 0.62; RMSE = 11.30 cm; Bias = 0.48 cm), confirmed the reliability of LiDAR systems for their practical application in the professional forestry sector.
2023
978-3-031-37113-4
978-3-031-37114-1
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3271449
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact