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Biomass Carbon Trend (CarbonFlux)

Analysis of long-term trends (2001–2022) in total biomass carbon, identifying whether ecosystems are gaining, losing, or maintaining carbon stocks.

Description

This indicator tracks whether biomass carbon has increased, decreased, or remained stable from 2001 to 2022. It applies the Mann-Kendall trend test (Kendall Tau) to annual carbon stock estimates, producing a per-pixel measure of trend direction and strength.

Values range from -1 to 1:

  • -1 represents a perfect decreasing trend (continuous carbon loss).
  • 0 represents a neutral trend (no significant change).
  • +1 represents a perfect increasing trend (continuous carbon gain).

Intermediate values indicate mixed trajectories, where some years show accumulation and others show loss. A threshold is applied to classify values greater than 0.01 as positive, less than -0.01 as negative, and between -0.01 and 0.01 as neutral.

What it measures

  • Long-term trend in total biomass carbon.
  • Areas of consistent carbon loss (deforestation, fires) or gain (restoration, regrowth).
  • Neutral zones with stable carbon dynamics.

How to interpret

  • Negative values (< -0.01): ecosystems consistently losing biomass carbon.
  • Positive values (> 0.01): ecosystems consistently accumulating carbon.
  • Neutral (-0.01 to 0.01): no significant trend detected.

Unit / Scale

Trend index (-1 to 1).
Temporal coverage: 2001–2022.
Spatial resolution: 309 m.
Update frequency: Annual.

Author / Source

Lemu — based on biomass carbon modelling.

Key sources include:

  • Copernicus Climate Change Service (C3S): Land cover classification maps.
  • Gibbs, H. K., & Ruesch, A. — IPCC Tier-1 Global Biomass Carbon Map (2000).
  • Giglio, L., Justice, C., Boschetti, L., & Roy, D. (2021). MODIS Burned Area Dataset (NASA EOSDIS).
  • Hussain, M., & Mahmud, I. (2019). pyMannKendall: A Python package for non-parametric Mann-Kendall trend tests. Journal of Open Source Software, 4(39), 1556.

🔗 https://climate.copernicus.eu
🔗 https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=932

Applications in Atlas

  • Identify regions of persistent carbon loss to target conservation actions.
  • Detect areas of carbon recovery through restoration or regrowth.
  • Support climate reporting by showing carbon dynamics over two decades.
  • Provide evidence for carbon offset projects and ecosystem resilience studies.
Updated on Aug 31, 2025