Canopy Carbon Map

High-resolution LiDAR and multispectral analysis quantifies carbon stocks in dense forest canopies, ensuring transparent verification for nature-based carbon credit projects.

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How does it work?

Measuring carbon storage in dense forest canopies is challenging with traditional ground-based surveys and satellite indices alone. Combining LiDAR and multispectral analytics provides precise, scalable verification that meets stringent carbon credit standards.

High-Resolution Mapping: Our platform uses airborne or drone LiDAR to capture detailed forest structure at sub-meter resolution. This reveals canopy complexity and biomass distribution that satellite imagery cannot resolve.
Accurate Carbon Quantification: Advanced algorithms convert 3D canopy metrics into precise carbon stock estimates. Validation against field plots ensures errors are below 5% at project scale.
Independent Audit Trail: Automated processing logs every data source and analysis step for full traceability. This audit-ready record simplifies third-party verification and compliance.
Rapid Project Scaling: Cloud-based analytics handle thousands of hectares in parallel, reducing processing time from weeks to days. This scalability accelerates credit issuance cycles.
Compliance Reporting: Preformatted reports align with VCS, Verra, and other carbon standards. Custom dashboards visualize carbon metrics, change over time, and confidence intervals.
Platform Integration: APIs connect seamlessly with GIS, MRV, and credit management systems. This integration streamlines data import, analysis, and downstream reporting.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

What is deep-canopy carbon verification?: Deep-canopy carbon verification uses LiDAR and multispectral imagery to measure forest carbon stocks beneath dense foliage. It enhances traditional methods by capturing 3D structure and biomass at high resolution.
How does this compare to ground-based surveys?: Ground surveys provide precise plots but are time-consuming and limited in spatial coverage. Our remote sensing approach scales across large areas while maintaining comparable accuracy under 5% error.
Why is LiDAR popular for carbon projects?: LiDAR offers direct measurement of canopy height and density, key predictors of biomass. Its popularity stems from proven accuracy and compatibility with international carbon standards.
Can satellite imagery be used instead?: Satellite sensors offer broader coverage but lack the vertical resolution to capture complex canopy structure. Combining LiDAR with multispectral satellites balances detail and cost-effectiveness.
What are limitations of this method?: High-resolution LiDAR surveys require specialized equipment and flight planning, which can increase upfront costs. Dense understorey and steep terrain may still pose challenges for full canopy penetration.
Are there alternatives for carbon stock estimation?: Alternatives include photogrammetry and radar-based biomass models, which can be less expensive but generally offer lower vertical accuracy. Our platform supports hybrid workflows to integrate multiple data sources.

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Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

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Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

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Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

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