Data di Pubblicazione:
2021
Abstract:
The need to rely on accurate information about the wood biomass available in riparian
zones under management, inspired the land reclamation authority of southern Tuscany to develop
a research based on the new remote sensing technologies. With this aim, a series of unmanned aerial
vehicle (UAV) flight campaigns flanked by ground-data collection were carried out on 5 zones and
15 stream reaches belonging to 3 rivers and 7 creeks, being representative of the whole area under
treatment, characterized by a heterogeneous spatial distribution of trees and shrubs of different
sizes and ages, whose species' mix is typical of this climatic belt. A careful preliminary analysis of
the zones under investigation, based on the available local orthophotos, followed by a quick pilot
inspection of the riverbank segments selected for trials, was crucial for choosing the test sites. The
analysis of a dataset composed of both measured and remotely sensed acquired parameters allowed
a system of four allometric models to be built for estimating the trees' biomass. All four developed
models showed good results, with the highest correlation found in the fourth model (Model 4, R2 =
0.63), which also presented the lowest RMSE (0.09 Mg). The biomass values calculated with Model
4 were in line with those provided by the land reclamation authority for selective thinning, ranging
from 38.9 to 70.9 Mg ha-1. Conversely, Model 2 widely overestimated the actual data, while Model
1 and Model 3 offered intermediate results. The proposed methodology based on these new
technologies enabled an accurate estimation of the wood biomass in a riverbank environment,
overcoming the limits of a traditional ground monitoring and improving management strategies to
benefit the river system and its ecosystems.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
precision forestry; unmanned aerial vehicle; image analysis; crown detection; biomass; river analysis
Elenco autori:
Berton, Andrea; Dainelli, Riccardo; Pastonchi, Laura; Nati, Carla; Matese, Alessandro; Toscano, Piero; DI GENNARO, SALVATORE FILIPPO
Link alla scheda completa:
Pubblicato in: