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PACHAMA INSIGHTS

Dynamic Baseline

Assess the baseline scenario with AI and remote sensing powered tooling.

Dynamic Control Area Baseline

About our tech

Pachama’s Dynamic Control Area Baseline (DCAB) dynamically estimates carbon impact by using satellite data and AI to first select a control area representative of the project and then observe forest change in the control and project areas over time.

Our DCAB was the first-ever AI tool to dynamically calculate baselines for forest carbon projects and critically quantify the uncertainty of estimates. 

Baseline Graph with caption

Get a validation-ready baseline in days

Looking to validate a carbon project? Get everything you need to build a compelling case for your dynamic baseline in your Project Design Document (PDD).

  • Dynamic baseline with project and control plots compliant with ARR standards (e.g., VM0047)
  • Downloadable figures and descriptions ready to drop directly into your PDD
  • Technical appendices to answer tough questions from validators

  • Why baselines matter

    A baseline represents a business-as-usual scenario used to estimate expected removals or emissions in the absence of a project. The baseline scenario is one of the most critical components in determining whether a project has a net additional climate benefit.

    Historically, baselines have relied on predictions derived from historical trends, but new dynamic baseline technology has unlocked the ability to observe baseline trends over time. If a project has high forest regeneration rates in selected baseline areas then it can have high credit delivery risk.

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  • Pachama’s evaluation approach
  • How you can use baseline insights
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