Algorithm

Composite number

Ecology

Biology

Carbon cycle

Accounting

Land cover

Carbon fibers

Bookkeeping

Geology

Business

Greenhouse gas

Mathematics

Biomass (ecology)

Environmental science

Land use

Atmospheric sciences

Carbon accounting

Carbon dioxide

Carbon sequestration

Ecosystem

The Science of The Total Environment

Reducing terrestrial carbon emissions to the atmosphere requires accurate measuring, reporting and verification of land surface activities that emit or sequester carbon. Many carbon accounting practices in use today provide only regionally aggregated estimates and neglect the spatial variation of pre-disturbance forest conditions and post-disturbance land cover dynamics. Here, we present a spatially explicit carbon bookkeeping model that utilizes a high-resolution map of aboveground biomass and land cover dynamics derived from time series analysis of Landsat data. The model produces estimates of carbon emissions/uptake with model uncertainty at Landsat resolution. In a case study of the Colombian Amazon, an area of 47 million ha, the model estimated total emissions of 3.97 ± 0.71 Tg C yr-1 and uptake by regenerating forests of 1.11 ± 0.23 Tg C yr-1 2001-2015, with an additional 45.1 ± 7.99 Tg of carbon remaining in the form of woody products, decomposing slash and charcoal at the end of 2015 (estimates provided with ±95% confidence intervals). Total emissions attributed to the study period (including carbon not yet released) is 6.97 ± 1.24 Tg C yr-1. The presented model is based on recent technological advancements in the field of remote sensing to achieve spatially explicit modeling of carbon emissions and uptake associated with land surface changes and post-disturbance landscapes that is compliant with international reporting criteria.

Spatiotemporal tracking of carbon emissions and uptake using time series analysis of Landsat data: A spatially explicit carbon bookkeeping model