Individual Tree Detection and Qualitative Inventory of a Eucalyptus sp. Stand Using UAV Photogrammetry Data

被引:14
|
作者
Almeida, Andre [1 ]
Goncalves, Fabio [2 ]
Silva, Gilson [3 ]
Mendonca, Adriano [3 ]
Gonzaga, Maria [4 ]
Silva, Jeferson [5 ]
Souza, Rodolfo [6 ]
Leite, Igor [1 ]
Neves, Karina [7 ]
Boeno, Marcus [2 ]
Sousa, Braulio [8 ]
机构
[1] Univ Fed Sergipe, Dept Agr Engn, Av Marechal Rondon S-N, BR-49100000 Sao Cristovao, Brazil
[2] Canopy Remote Sensing Solut, BR-88032005 Florianopolis, SC, Brazil
[3] Univ Fed Espirito Santo, Dept Forest & Wood Sci, BR-29550 Jeronimo Monteiro, Brazil
[4] Univ Fed Sergipe, Dept Agron Engn, Av Marechal Rondon S-N, BR-49100000 Sao Cristovao, Brazil
[5] Univ Fed Espirito Santo, Forest Sci Post Graduat Program, BR-29550 Jeronimo Monteiro, Brazil
[6] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77840 USA
[7] Univ Fed Sergipe, Water Resources Post Grad Program, Av Marechal Rondon S-N, BR-49100000 Sao Cristovao, Brazil
[8] Univ Fed Sergipe, Dept Zootechn, Av Marechal Rondon S-N, BR-49100000 Sao Cristovao, Brazil
关键词
UAS; 3D point cloud; enhanced forest inventories; precision silviculture; SfM; individual tree detection; Gini; lorenz curve; AIRBORNE LIDAR; VEGETATION STRUCTURE; POINT CLOUDS; FOREST; HEIGHT; VARIABLES; ACCURACY; IMAGERY; AREA; QUANTIFICATION;
D O I
10.3390/rs13183655
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Digital aerial photogrammetry (DAP) data acquired by unmanned aerial vehicles (UAV) have been increasingly used for forest inventory and monitoring. In this study, we evaluated the potential of UAV photogrammetry data to detect individual trees, estimate their heights (ht), and monitor the initial silvicultural quality of a 1.5-year-old Eucalyptus sp. stand in northeastern Brazil. DAP estimates were compared with accurate tree locations obtained with real time kinematic (RTK) positioning and direct height measurements obtained in the field. In addition, we assessed the quality of a DAP-UAV digital terrain model (DTM) derived using an alternative ground classification approach and investigated its performance in the retrieval of individual tree attributes. The DTM built for the stand presented an RMSE of 0.099 m relative to the RTK measurements, showing no bias. The normalized 3D point cloud enabled the identification of over 95% of the stand trees and the estimation of their heights with an RMSE of 0.36 m (11%). However, ht was systematically underestimated, with a bias of 0.22 m (6.7%). A linear regression model, was fitted to estimate tree height from a maximum height metric derived from the point cloud reduced the RMSE by 20%. An assessment of uniformity indices calculated from both field and DAP heights showed no statistical difference. The results suggest that products derived from DAP-UAV may be used to generate accurate DTMs in young Eucalyptus sp. stands, detect individual trees, estimate ht, and determine stand uniformity with the same level of accuracy obtained in traditional forest inventories.
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页数:21
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