作者: Chloe Brown , Doreen Boyd , Sofie Sjögersten , Daniel Clewley , Stephanie Evers
DOI: 10.3390/RS10050671
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摘要: Accurate estimation of above ground biomass (AGB) is required to better understand the variability and dynamics tropical peat swamp forest (PSF) ecosystem function resilience disturbance events. The objective this work examine relationship between PSF AGB small-footprint airborne Light Detection Ranging (LiDAR) discrete return (DR) full waveform (FW) derived metrics, with a view establishing optimal use technology in environment. study was undertaken North Selangor (NSPSF) reserve, Peninsular Malaysia. Plot-based multiple regression analysis performed established strongest predictive models using DR metrics (only), FW combination metrics. Overall, results demonstrate that Combination-model, coupling benefits from both had best performance modelling for (R2 = 0.77, RMSE 36.4, rRMSE 10.8%); however, no statistical difference found model only We conclude approach LiDAR relate description mid-canopy. This should inform remote sensing how innovation LiDAR-based could be usefully deployed.