Assessing the Carbon Sequestration Potential of Human-Controlled Wetlands: A Remote Sensing Approach Using Google Earth Engine
Year: 2025
Type: article
Abstract: Blue carbon ecosystems, including mangroves, seagrasses, and salt marshes, play a crucial role in mitigating climate change by capturing and storing atmospheric CO₂ at rates exceeding those of terrestrial forests.This study explores the potential of HCWs (Human-Controlled Wetlands) in the Italian Venice Lagoon as an underappreciated component of the global blue carbon pool.Using GEE (Google Earth Engine), we conducted a large-scale assessment of carbon sequestration in these wetlands, demonstrating its advantages over traditional in situ methods in addressing spatial variability.Our findings highlight the significance of below-water mud sediments as primary carbon reservoirs, with a TC (Total Carbon) content of 3.81% ± 0.94% and a stable storage function akin to peat, reinforced by high CEC (Cation Exchange Capacity).GEE analysis identified a redoximorphic zone at a depth of 20-30 cm, where microbial respiration shifts to anaerobic pathways, preventing carbon release and maintaining long-term sequestration.The study also evaluates key factors affecting remote sensing accuracy, including tidal variations, water depth, and sky cover.The strong correlation between field-measured and satellite-derived carbon parameters (R² > 0.85) confirms the reliability of our approach.Furthermore, we developed a GEE-based script for monitoring sediment bioturbation, leveraging Sentinel-1 SAR (Synthetic Aperture Radar) and Sentinel-2 optical data to quantify biological disturbances affecting carbon fluxes.Our results underscore the value of HCWs for carbon sequestration, reinforcing the need for targeted conservation strategies.The scalability and efficiency of remote sensing methodologies, particularly GEE, make them essential for the long-term monitoring of blue carbon ecosystems and the development of effective climate mitigation policies.
Authors: Doimi Mauro, L. D’Amanzo, G. Minetto
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408088125