Assessing Earthquake-Triggered Ecosystem Carbon Loss Using Field Sampling and UAV Observation

Earthquakes disrupt local organic carbon distribution by stripping vegetation, destabilizing soil, and triggering landslides, leading to immediate carbon loss and potential long-term climate impacts. While remote sensing techniques effectively assess post-earthquake vegetation loss, they fail to capture subsurface carbon dynamics along vertical profiles. This study quantifies ecosystem carbon loss from the Luding Earthquake by integrating field sampling, UAV-based LiDAR, and machine learning models to assess vegetation and soil carbon stocks. Field investigations were conducted at landslide deposits, debris flow deposits, and undisturbed sites to analyze soil organic carbon and biomass carbon content. UAV-derived point cloud data improved vegetation biomass estimation, reducing sample plot overestimation by 30.4% due to uneven vegetation distribution. The results indicate that landslides and debris flows caused an 83.9–95.9% reduction in carbon storage, with the total ecosystem carbon loss estimated at 7.36 × 105 Mg. This study provides a comprehensive assessment of earthquake-triggered carbon loss, offering critical insights for carbon budget research on natural disasters and the development of post-earthquake ecological restoration policies.

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Publication Details

Journal
Land
Published
2025-04-23
DOI
https://doi.org/10.3390/land14050915
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Assessing Earthquake-Triggered Ecosystem Carbon Loss Using Field Sampling and UAV Observation

Wen Zeng, Siwen Yu, Yu Zhan, Tan Mi et al.
Land
Atmospheric and Environmental Gas Dynamics
article

Assessing Earthquake-Triggered Ecosystem Carbon Loss Using Field Sampling and UAV Observation

Wen Zeng, Siwen Yu, Yu Zhan, Tan Mi, Baofeng Di, Junhui Li, Wen He, Ziquan Zuo
article en

Abstract

Earthquakes disrupt local organic carbon distribution by stripping vegetation, destabilizing soil, and triggering landslides, leading to immediate carbon loss and potential long-term climate impacts. While remote sensing techniques effectively assess post-earthquake vegetation loss, they fail to capture subsurface carbon dynamics along vertical profiles. This study quantifies ecosystem carbon loss from the Luding Earthquake by integrating field sampling, UAV-based LiDAR, and machine learning models to assess vegetation and soil carbon stocks. Field investigations were conducted at landslide deposits, debris flow deposits, and undisturbed sites to analyze soil organic carbon and biomass carbon content. UAV-derived point cloud data improved vegetation biomass estimation, reducing sample plot overestimation by 30.4% due to uneven vegetation distribution. The results indicate that landslides and debris flows caused an 83.9–95.9% reduction in carbon storage, with the total ecosystem carbon loss estimated at 7.36 × 105 Mg. This study provides a comprehensive assessment of earthquake-triggered carbon loss, offering critical insights for carbon budget research on natural disasters and the development of post-earthquake ecological restoration policies.

LandVol. 14(5)
Hong Kong Polytechnic University (HK), Sichuan University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 91%
Atmospheric and Environmental Gas Dynamics
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Assessing Earthquake-Triggered Ecosystem Carbon Loss Using Field Sampling and UAV Observation — Wen Zeng, Siwen Yu, et al. · Land (2025) | TGRS Research Map | TGRS