When organisations undergo environmental safeguards assessments, understanding carbon sinks is often required. Not just what you emit, but what you offset. The traditional approach has limitations. Someone walks around with a clipboard, counts trees, measures a few diameters, and extrapolates. When you are dealing with carbon credits or ESG reporting, approximations do not hold up.
At GeoFront, we combine field data collection with remote sensing and machine learning because each method compensates for the other’s limitations, and we are proud to see some of the projects we contributed to on due diligence being picked up by investors.
Our approach is getting into the field to document species; here we picked Eucalyptus, Jacaranda, and Grevillea with precise diameter measurements.
For scale, we acquired satellite imagery at 30 to 50 cm resolution and processed it through a YOLO v3 neural network fine-tuned for tree detection. The model performed canopy segmentation and classified trees into five height categories.
Methods: Carbon sequestration was calculated through biomass estimation using allometric equations. Above-ground biomass was derived using AGB = 0.25 × D² × H. Below-ground biomass was estimated at 20% of AGB. Total biomass was converted to dry weight at 72.5%, then to carbon content at 50%. Final CO² equivalent used the molecular weight ratio of 3.67.
Results: In this example, our client’s properties contain approximately 3,015 tonnes of sequestered CO². Mature trees alone contributed over 1,865 tonnes.
Accurate carbon sink quantification opens access to carbon markets and strengthens ESG reporting. It also informs land use decisions. Before removing a mature tree, understanding it represents 50 years of carbon sequestration changes the calculation.
The trees are already doing their job. Someone just needs to measure it properly. If you need any of these, GeoFront Consulting is here to walk with you.
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- #RemoteSensing
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