dMRV Implementation and Monitoring

Updated 2026-11-02 · 2 min read · By the akar.earth specialist team

dMRV implementation and monitoring for forest, agroforestry and mangrove carbon projects: field apps, satellite layers and audit-ready data pipelines.

dMRV implementation sets up the digital system that measures, records and reports your project’s carbon results for each monitoring period. We combine field data collection, satellite layers and a traceable data pipeline, so that every reported tonne can be followed back to a plot, a tree and a timestamp.

Who it is for

• ARR, agroforestry and mangrove projects starting their first monitoring period.
• Projects moving from paper forms and spreadsheets to a digital workflow.
• Smallholder programmes that need per-farm or per-tree records at scale.
• Companies that want one monitoring system for carbon and EUDR evidence.

The problem it solves

Monitoring is where many projects lose credibility. Plot data gets transcribed by hand, photos are not linked to locations, survival counts are estimated, and calculations live in spreadsheets nobody else understands. At verification, the auditor cannot trace the numbers. A dMRV pipeline fixes this by capturing data digitally at source and keeping every step reproducible.

What we deliver

• Monitoring design aligned with the project’s monitoring plan and methodology, for example the plot and remote sensing components of VM0047.
• Field app setup in AKAR dMRV: forms, species lists, validation rules and offline use.
• Field team training on the app, measurement protocols and QA.
• Satellite monitoring layers: land-cover change, canopy and disturbance alerts, see deforestation alerts.
• Data pipeline from app to cleaned dataset to calculation outputs, with version control.
• Dashboard for survival, growth and coverage in the AKAR Dashboard.
• Monitoring report inputs: tables, maps and evidence ready for the monitoring report.

How it works

1. Assessment. Review the monitoring plan, existing data and team capacity.
2. Configuration. Set up forms, plot lists, boundaries and calculation steps.
3. Pilot. A short field pilot to test the workflow and fix problems.
4. Rollout. Training and full data collection.
5. Ongoing support. QA checks each period, satellite updates and help preparing verification data.

What you provide

• The project’s monitoring plan and methodology.
• Boundaries, plot network and existing data.
• A field team, or a budget for us to supply enumerators.
• Smartphones or tablets for data collection.

Typical timeline

Setup and pilot typically take four to eight weeks. Monitoring then runs for as long as the project needs it, usually aligned with each monitoring period.

Tools we use

AKAR dMRV for field capture, AKAR Mapper for drone layers, AKAR Eligibility for satellite change checks and AKAR Dashboard for reporting. Where AI models help, for example flagging outliers or classifying imagery, a specialist reviews the results; see AI in carbon MRV.

What good monitoring data looks like

Each record carries who collected it, where, when and with which device. Edits are logged rather than overwritten. Calculations run from raw data with fixed, documented steps, so anyone can reproduce the reported total. Satellite layers are dated and their source recorded. When an auditor asks how a number was produced, you can show the chain in minutes rather than weeks. That traceability is the main return on a dMRV investment.

Next step

Read the dMRV hub. If you need a first inventory before monitoring starts, see field data campaigns. Then message us with project type, area, number of plots or farms, and your next verification date.