01RGB
See the canopy
High-resolution imagery provides visible structure, crown boundaries, seasonal cues, and contextual information.
Independent research prototype · 2026
From a forestto individual trees.
An interactive exploration of how imagery, LiDAR, satellite observations, field data, and AI can contribute to richer forest and biodiversity understanding.
Synthetic demo scene · no restricted or institution-internal data
Multimodal view
Different sensors describe different parts of the same forest.
The prototype does not treat one modality as the answer. It is designed around the idea that complementary observations can be aligned, evaluated, and interpreted together.
02LiDAR
Measure in 3D
Point clouds expose vertical structure and support tree-level geometry such as height, crown form, and spatial arrangement.
03Satellite
Scale across landscapes
Repeated Earth observations add broad spatial coverage and temporal context beyond a single field campaign.
04Field
Ground the models
Field observations connect remote measurements with species, ecology, validation, and biodiversity interpretation.
Research-to-interface method
Make the reasoning visible, not only the final map.
- 01Observe
Represent each public sensing modality separately.
- 02Align
Bring spatial and semantic observations into a shared view.
- 03Model
Show candidate AI outputs such as tree delineation and attributes.
- 04Evaluate
Keep uncertainty, provenance, and validation visible to the user.
Public research cases
Research themes translated into an interactive product concept.
These case studies are based only on publicly available NIBIO pages. They provide conceptual context; this site is an independent prototype and does not reproduce internal software, unpublished methods, or restricted data.
NIBIOPublic source
SFI SmartForest
A public research initiative focused on bringing digitalisation and Industry 4.0 approaches into the Norwegian forest sector.
forest digitalisationdecision supportdata integration
Public NIBIO project page used as conceptual inspiration only; this prototype is independent.
Read the public source ↗NIBIOPublic source
AI opens the door to single-tree-based forestry
Public research communication describing AI and laser-scanning approaches for extracting detailed information at individual-tree level.
LiDARindividual treesmachine learning
Public NIBIO article used to frame tree-level visualization and AI-output concepts.
Read the public source ↗NIBIOPublic source
SmartForest with artificial intelligence in the cloud
Public research communication on cloud-based processing and AI analysis of large forest datasets and sensor observations.
cloudsensor dataAI workflows
Public NIBIO article used as architectural inspiration for data-processing and decision-support concepts.
Read the public source ↗Provenance & uncertainty
The interface shows what is real, synthetic, and illustrative.
The current forest geometry and model-style overlays are demonstrations, not empirical measurements or scientific results.
Generated deterministically in application code. Contains no external or real-world observations.
The value is illustrative UI data only. It is not a benchmark, calibrated confidence score, or research finding.
Public-source discipline
Built to be safe to publish.
The repository uses public research pages for conceptual framing and synthetic data for the initial 3D experience. External datasets or assets are only added after provenance and reuse rights are documented.
View source policy ↗