Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

编号 030021703

推送时间 20191216

研究领域 森林经理 

年份 2019 

类型 期刊 

语种 英语

标题 Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

来源期刊 FORESTS

期 第217期

发表时间 20191015

关键词 unmanned?aerial?vehicles (UAV);  forest?inventory;  volume;  canopy height model (CHM);  object based image analysis (OBIA);  structure from motion (SfM); 

摘要 Estimating?forest?inventory variables is important in monitoring?forest?resources and mitigating climate change. In this respect,?forest?managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model?forest?structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital?aerial?photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from?Unmanned?Aerial?Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m(3) and 0.026 m(3), rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m(3) and 0.0004 m(3)) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

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