Steve Petrie: Mapping carbon uptake with high accuracy across different agricultural land cover types
Author Information:
Steve Petrie*,
Rebecca Allen*,
Philip Branch*,
Christopher Fluke*,
Mark Adams*,
- Swinburne University of Technology
-
Introduction and scientific context – Measuring CO2 flux is important for understanding the carbon cycle in terrestrial ecosystems. Eddy covariance (EC) towers can measure CO2 flux with high accuracy. Australia’s current EC network has good coverage of natural ecosystems (e.g. forests), but little coverage of agricultural land.
-
Methodology/project summary – We used novel, mobile EC towers to measure CO2 flux in agricultural grasslands in Tasmania, then combined the measurements with satellite data to produce large-scale, high-accuracy maps of carbon uptake in agricultural land. We combined machine learning-based image segmentation of Sentinel-2 satellite imagery with calculations of EC tower measurement footprints to disentangle proportional contributions to CO2 fluxes from different land cover types. Our model is able to separate out contributions to carbon flux from different land cover types, making efficient use of available data, providing more complete information for satellite-based upscaling, and enabling a single EC tower to simultaneously measure fluxes from multiple surrounding land cover types.
-
Results – The resulting satellite-based upscaling model is able to explain 82% of the variation in the observed carbon uptake (R^2 = 0.82), producing high-accuracy maps of carbon uptake in agricultural land, at hourly timescales and 10m resolution.
-
Audience – Those interested in weather data, greenhouse gas emissions, carbon sequestration, and methods that combine satellite imagery with ground-truth data via appropriate models.
-
Keywords – Eddy covariance (flux) towers, carbon uptake, carbon sequestration, land management.