Overview
As a key component of the Supplementary Environmental and Social Impact Assessment (ESIA) study, Amilen Africa conducted a comprehensive baseline Greenhouse Gas (GHG) emissions assessment for the proposed New Iconic Nairobi Central Station and Public Square.
This assessment adhered to the methodologies outlined in IEMA’s Environmental Impact Assessment Guide to: Assessing Greenhouse Gas Emissions and Evaluating their Significance, 1 encompassing both qualitative and quantitative analyses of pertinent activities within the project area, including transportation, energy consumption, and waste management.
To enhance the accuracy and efficiency of baseline carbon sink estimation, Amilen Africa integrated advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Specifically, Convolutional Neural Networks (CNNs) were employed for the detailed analysis of satellite imagery. This enabled precise identification and analysis of tree canopies and facilitated tree height classification across the project area.
This innovative application of AI/ML provided a more accurate and granular assessment of existing carbon sequestration capacity, offering crucial insights for informed environmental management and sustainability planning throughout the project lifecycle.
What we did
- Baseline greenhouse gas assessment for an environmental and social impact study
- AI (convolutional neural networks) on satellite images to measure tree canopy and height
- Estimate of how much carbon existing trees absorb
