Applying High-Resolution UAV-LiDAR and Quantitative Structure Modelling for Estimating Tree Attributes in a Crop-Livestock-Forest System

Land

Ana Paula Dalla Corte¹  Matheus Niroh Inoue Sanquetta¹  Hudson Franklin Pessoa Veras¹  Jonathan William Trautenmüller¹  Mauro Alessandro Karasinski¹  Franciel Eduardo Rex¹  Carlos Roberto Sanquetta¹  Carine Klauberg²  Rodrigo Vieira Leite³  Cibele Hummel do Amaral³  Danilo Roberti Alves de Almeida⁴  Midhun Mohan⁵  Anibal de Moraes⁶  Bruna Nascimento de Vasconcellos⁷  Karla da Silva Rocha⁸  Carlos Alberto Silva⁹  Angelica Maria Almeyda Zambrano^1,10  Eben North Broadbent^1,11 

[1] BIOFIX Research Center, Federal University of Parana, Curitiba 80210-170, Brazil;Department of Forest Engineering, Federal University of João Del Rei, Sete Lagoas 35701-970, Brazil;Department of Forest Engineering, Federal University of Viçosa, Viçosa 36570-900, Brazil;Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba 13418-900, Brazil;Department of Geography, University of California, Berkeley, CA 94709, USA;Department of Plant Sciences, Federal University of Parana, Curitiba 80210-170, Brazil;EMBRAPA Florestas, Colombo 83411-000, Brazil;Geoprocessing Laboratory, Federal University of Acre, Rio Branco 69980-000, Brazil;School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA;Spatial Ecology and Conservation Laboratory, Center for Latin America Studies, University of Florida, Gainesville, FL 32611, USA;Spatial Ecology and Conservation Laboratory, School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA;

关键词: quantitative structure modelling;    laser scanning;    tree modelling;   

DOI  :  10.3390/land11040507

来源: DOAJ

【 摘 要 】

Individual tree attributes, such as stem volume and biomass, are usually predicted by using traditional field-derived allometric models. However, these models are derived from data collected from small areas and lack a level of detail of tree components (e.g., stem, branches, and leaves). Remote sensing techniques such as the Quantitative Structure Modelling (QSM) applied on high-density LiDAR data emerge as a promising solution for obtaining extensive and detailed tree attribute estimates. We used a high-density LiDAR data on board of a Unmanned Aerial Vehicle (UAV) to evaluate the performance of the QSM approach in estimating field-derived individual tree attributes such as the diameter at breast height (dbh), tree height (ht), and volume (v), as well as the stem (SAGB), branch (BAGB), and total (TAGB) aboveground biomass of eucalyptus trees. QSM was used in two different approaches: (i) using dbh and h derived from QSM and then applied into the field-based equations for estimation of volume and (ii) deriving tree volume directly from QSM. In general, all fitted models using the QSM approach were satisfactory, but with a slight tendency of over-estimation of dbh (9.33%), ht (12.40%), v-QSM1 (26.35%), v-QSM2 (26.66%), TAGB (27.08%), SAGB (25.57%), and BAGB (20.08%). Non-significant differences were noticed when estimating the dbh, tree volume, stem, and aboveground biomass. Despite the overestimation, this study indicates that using the QSM approach to estimate individual tree attributes from UAV-LiDAR is a promising alternative to support the decision-making process regarding forest management activities, especially when considering tree architecture and biomass components.

【 授权许可】

Unknown