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Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

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Published on: June 24, 2019

Quantifying mangrove carbon assimilation rates using UAV imagery.

Javier Blanco-Sacristán¹, Kasper Johansen², Mariana Elías-Lara²

¹Climate and Livability Initiative, Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, 23955-6900, Thuwal, Saudi Arabia. javier.blancosacristan@kaust.edu.sa.

Scientific Reports

|February 26, 2024

Summary

Mangrove forests effectively store carbon, especially in drylands. This study uses drone imagery to map leaf area and estimate carbon assimilation, aiding conservation efforts.

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Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

Area of Science:

Ecology
Remote Sensing
Carbon Sequestration

Background:

Mangrove forests are crucial carbon sinks, particularly in arid environments.
Accurate mapping of carbon assimilation in mangroves is vital for natural capital accounting and conservation.
Remote sensing techniques can provide valuable data on vegetation health and carbon uptake.

Purpose of the Study:

To develop and validate a method for retrieving Leaf Area Index (LAI) in Red Sea mangroves using UAV multispectral data.
To estimate carbon assimilation rates in dryland mangrove ecosystems.
To provide a tool for quantifying the carbon mitigation potential of mangrove reforestation.

Main Methods:

Applied a linear regression model to UAV-derived multispectral data to estimate LAI.
Validated UAV-derived LAI against ground-sampled LiCOR LAI-2200C data.
Combined UAV-derived LAI with field-measured net photosynthesis rates (LiCOR 6400/XT) to estimate carbon assimilation.

Main Results:

Achieved an R² of 0.72 for UAV-derived LAI compared to ground measurements.
Estimated carbon assimilation in dryland mangrove systems at approximately 3000 tons C km⁻² yr⁻¹.
Demonstrated the potential of integrating remote sensing and field data for monitoring mangrove carbon dynamics.

Conclusions:

UAV-based remote sensing effectively retrieves LAI in mangrove ecosystems.
This approach provides a robust method for estimating carbon assimilation in dryland mangroves.
The findings support the quantification of carbon mitigation potential for mangrove conservation and restoration projects.