Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model

编号 030038103

推送时间 20230206

研究领域 森林经理 

年份 2022 

类型 期刊 

语种 英语

标题 Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model

来源期刊 REMOTE SENSING

期 第381期

发表时间 20230122

关键词 3-PG model;  eucalyptus;  forest age;  forest structureremote sensing;  sensitivity; 

摘要 Eucalyptus plantations play an important role in the timber supply and global warming mitigation around the world.?Forest?age is a critical factor for evaluating and modeling?forest?structure (e.g., diameter at breast height (DBH), height (H), aboveground carbon stocks (ACS)) and their dynamics. Recently, the spatial distribution of?forest?age at different scales based on time series remote sensing data has been widely investigated. However, it is unclear whether such data can effectively support the simulation and assessment of?forest?structure, especially in fast-growing plantation forests. In this study, the physiological principles in predicting?growth?(3-PG) model was firstly optimized and calibrated using survey and UAV lidar data at the sample plot (SP) scale, and was then applied at the?forest?sub-compartment (FSC) scale by designing different simulation scenarios driven by different?forest?age data sources and adjustments. The sensitivity of the simulated?forest?structure parameters to?forest?age was assessed at the SP and FSC levels. The results show that both the survey?forest?age data and the remote-sensing-derived?forest?age data could accurately estimate the DBH, H, and ACS of eucalyptus plantations with the coefficients of determination (R-2) ranging from 0.87 to 0.94, and the relative root mean square error (RRMSE) below 20% at SP level. At the FSC level, the simulation results based on remotely sensed?forest?age data are significantly better than FSC?forest?age data from surveys by forestry bureaus, with R-2 of ACS 0.7, RMSE 9.12 Mg/ha, and RRMSE 28.24%. The results of the sensitivity analysis show that the DBH, H, and ACS show different degrees of variation under different adjusted?forest?ages at SP and FSC level. The maximum difference in ACS is 82.91% at the SP scale if the?forest?age decreases 12 months and 41.23% at the FSC scale if the?forest?age increases 12 months. This study provides an important reference for future studies using?forest?age data obtained by remote sensing to drive the?forest?carbon model in a large spatial scale.

服务人员 付贺龙

服务院士 唐守正

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