Quantification of Carbon Sequestration in Urban Forests
This addresses the lack of efficient quantification methods for tracking carbon storage in urban trees, which is important for environmental monitoring and climate change mitigation, though it appears incremental as it builds on existing remote sensing techniques.
The paper tackled the problem of quantifying carbon sequestration in urban forests by developing a method to estimate carbon storage in trees using multi-spectral aerial imagery and LiDAR data, resulting in an estimate of 52,000 tons of carbon sequestered in Manhattan.
Vegetation, trees in particular, sequester carbon by absorbing carbon dioxide from the atmosphere. However, the lack of efficient quantification methods of carbon stored in trees renders it difficult to track the process. We present an approach to estimate the carbon storage in trees based on fusing multi-spectral aerial imagery and LiDAR data to identify tree coverage, geometric shape, and tree species -- key attributes to carbon storage quantification. We demonstrate that tree species information and their three-dimensional geometric shapes can be estimated from aerial imagery in order to determine the tree's biomass. Specifically, we estimate a total of $52,000$ tons of carbon sequestered in trees for New York City's borough Manhattan.