Aboveground Biomass and Tree Mortality Revealed Through Multi-Scale LiDAR Analysis DOI Creative Commons
Inácio Thomaz Bueno, Carlos Alberto Silva, Kristina J. Anderson‐Teixeira

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 796 - 796

Published: Feb. 25, 2025

Accurately monitoring aboveground biomass (AGB) and tree mortality is crucial for understanding forest health carbon dynamics. LiDAR (Light Detection Ranging) has emerged as a powerful tool capturing structure across different spatial scales. However, the effectiveness of predicting AGB depends on type instrument, platform, resolution point cloud data. We evaluated three distinct LiDAR-based approaches in 25.6 ha North American temperate forest. Specifically, we following: GEDI-simulated waveforms from airborne laser scanning (ALS), grid-based structural metrics derived unmanned aerial vehicle (UAV)-borne lidar data, individual detection (ITD) ALS Our results demonstrate varying levels performance approaches, with ITD emerging most accurate modeling median R2 value 0.52, followed by UAV (0.38) GEDI (0.11). findings underscore strengths approach fine-scale analysis, while used to analyze showed promise broader-scale monitoring, if more uncertainty acceptable. Moreover, complementary scales each method may offer valuable insights management conservation efforts, particularly dynamics informing strategic interventions aimed at preserving mitigating climate change impacts.

Language: Английский

Aboveground Biomass and Tree Mortality Revealed Through Multi-Scale LiDAR Analysis DOI Creative Commons
Inácio Thomaz Bueno, Carlos Alberto Silva, Kristina J. Anderson‐Teixeira

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 796 - 796

Published: Feb. 25, 2025

Accurately monitoring aboveground biomass (AGB) and tree mortality is crucial for understanding forest health carbon dynamics. LiDAR (Light Detection Ranging) has emerged as a powerful tool capturing structure across different spatial scales. However, the effectiveness of predicting AGB depends on type instrument, platform, resolution point cloud data. We evaluated three distinct LiDAR-based approaches in 25.6 ha North American temperate forest. Specifically, we following: GEDI-simulated waveforms from airborne laser scanning (ALS), grid-based structural metrics derived unmanned aerial vehicle (UAV)-borne lidar data, individual detection (ITD) ALS Our results demonstrate varying levels performance approaches, with ITD emerging most accurate modeling median R2 value 0.52, followed by UAV (0.38) GEDI (0.11). findings underscore strengths approach fine-scale analysis, while used to analyze showed promise broader-scale monitoring, if more uncertainty acceptable. Moreover, complementary scales each method may offer valuable insights management conservation efforts, particularly dynamics informing strategic interventions aimed at preserving mitigating climate change impacts.

Language: Английский

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