A
Finished geodata
GEODATA- Orthomosaic / GeoTIFF / COG
- CHM / DSM / DTM
- AOI: GPKG / GeoJSON / Shapefile
- Optional: tree / control points
White-label processing for UAV and forest geodata
Turn your UAV data into deliverable forest layers.
We process orthomosaics, CHMs and boundaries into QGIS-ready tree, crown and structure layers — complete with manifest, QA notes and delivery under your brand.
No drone operations. No end-client outreach. No black-box AI.
QGIS-readyGPKG + COGEvidence pack optionalPartner-branded delivery
AOI · demo sector
CRS · EPSG:25832
DELIVERY PACKAGEpartner_delivery/
- forest_layers.gpkg
- canopy_height_model.cog.tif
- qgis_project.qgz
- processing_manifest.json
EVIDENCE PACKpackaged
Two input routes · one delivery package
What you send — what you receive
A clear technical handoff for existing UAV and GIS projects — optionally starting from UAV imagery and sidecars.
B
Optional: UAV imagery + sidecars
UAV + METAIf rasters are missing, we review imagery and metadata as a basis for orthomosaics, elevation models or COG outputs.
JPG / TIFF UAV imageryEXIF / GPS metadataMRK / RTK / NAV / OBS / OBKFlight folders / mission structure
OUT
Deliverable outputs
QGIS- orthomosaic.cog.tif · DSM / DTM / CHM
- tree_points.gpkg
- crown_candidates.gpkg
- qgis_project.qgz
- processing_manifest.json
- QA summary · optional Evidence Pack
Processing workflow
From data intake to delivery.
Six concise stages, including optional raster generation and documented handoff.
01
INPUTData intake
Raster, vector, imagery, sidecar and AOI assets are received in a structured package.
02
RASTEROptional: raster foundation
UAV imagery is reviewed for suitable orthomosaic, elevation-model and COG outputs.
03
NORMALIZEData normalization & canonicalization
CRS, NoData, units, resolution and file structure are normalised.
04
PROCESSAI/geospatial processing
Tree points, crown polygons and structure layers are processed with defined parameters.
05
EVIDENCEQA, manifest & evidence pack
Processing steps, checksums, parameters and outputs are documented for your project context.
06
DELIVERPartner-branded delivery
QGIS-ready package using the agreed output schema and handoff process.
Visual product proof
Raw imagery or rasters in. Delivery package out.
Both input routes lead into the same documented processing and partner-ready handoff.
Imagery + sidecarsOrthomosaic + CHM
GPKG + COG + EVIDENCE
Interactive layer demo prepared
The map area can later be replaced with a real QGIS or Leaflet view.
Productised packages
Start small. Standardise later.
Start with a bounded dataset. Once the workflow fits, we standardize outputs, handoff and repeatability.
Sample Processing
from €490
Best forFirst real dataset and technical feasibility
For partners who want to see what can be derived from their UAV/GIS data.
- Data check
- Small AOI subset
- 1–2 output layers
- Sample manifest
- Short result note
- Partner call
Forest Layer Essentials
from €1,500 per project
Best forStandard QGIS tree and crown package
The robust base package for standardised forest layers and QGIS hand-off.
- Canonical ingest
- Boundary clipping
- CHM/orthomosaic normalisation
- Tree point candidates
- Crown polygon candidates
- QGIS-ready GPKG
- Basic audit manifest
Forest Metrics Pro
from €3,500 per project
Best forExtended metrics and documentation
Extended structure metrics and partner-ready project documentation.
- Everything in Essentials
- Height statistics
- Crown areas
- Crown-diameter proxy
- Canopy density
- QA report
- Partner-branded summary
- Optional pilot modules: canopy gap / health screening
Partner Engine
custom
Best forRecurring processing with fixed schemas
For recurring white-label partners with defined workflows.
- Recurring processing
- Defined output schemas
- Partner branding
- Prioritisation
- API/S3 hand-off
- NDA available
- No end-client contact
- Repeatable audit trail
Premium add-on
Evidence Pack
A structured project record with input/output references, checksums, parameters, processing steps, QA notes and handoff documentation.
from €750 per projectDiscuss evidence pack ↗Final scope is confirmed after data review and requested outputs.
White-label partnership
Your clients stay your clients.
digitalforestry.ai works as a processing layer in the background. You run the project, communication and delivery. We provide technical forest layers, QA notes and processing evidence within your workflow.
✓No drone operations
✓No end-client outreach
✓No publication without approval
✓Partner branding available
✓NDA available
✓Upload and handoff workflows by agreement
✓Reproducible outputs with manifest
PARTNERdigitalforestry.ai
You run the project. We deliver the AI processing.
Client relationship, interpretation, approval and delivery remain within your process.
Premium processing evidence
Chain of evidence for your processing workflow.
A manifest records one run. The optional evidence pack combines input references, checksums, processing steps, parameters, versions, outputs, QA notes and handoff documentation into a traceable project record.
01 Manifest
→ Technical run and output artifact.
02 Evidence Pack
Structured chain of evidence for internal QA, client documentation and project records.
Add-on from €750 per projectPremium add-on
Discuss evidence pack evidence_pack / project record EVIDENCE PACK
▾ evidence_pack/
0000_project_summary.md✓
0101_input_assets.json✓
0202_checksums.sha256✓
0303_processing_steps.json✓
0404_parameters.json✓
0505_worker_versions.json✓
0606_output_assets.json✓
0707_qa_notes.md✓
0808_handoff_readme.md✓
ChecksumsQA packageReproducibilityClient handoff
Use cases
Where the processing layer fits your offer.
Concrete integration points for teams that capture, review and deliver geodata to their own clients.
01
UAV forestry projects
- Challenge
- Orthomosaics and height products exist, but specialised forest AI analysis is missing.
- Output
- Normalised data, tree/crown candidates and a QGIS package.
- Partner value
- More value per flight project without an in-house ML team.
02
Digital forest inventory preparation
- Challenge
- Fieldwork and GIS review need structured pre-analysis layers.
- Output
- Candidate layers and structure metrics for professional review.
- Partner value
- More focused checks and consistent project preparation.
03
Tree and crown candidate layers
- Challenge
- Manual pre-segmentation is slow and difficult to scale.
- Output
- Point and polygon candidates with QA notes.
- Partner value
- A faster start for qualified review workflows.
04
CHM processing
- Challenge
- Height models vary in CRS, units, resolution and quality.
- Output
- Checked, clipped and normalised CHM.
- Partner value
- A dependable technical basis for downstream analysis.
Specialist processing studio
Expert-led geospatial AI processing
digitalforestry.ai is built as a specialist processing studio for UAV, GIS and forestry teams. Technical direction is led by René Schubotz, an AI and geospatial developer with experience in computer vision, UAV data processing and reproducible geospatial pipelines. The focus: robust white-label outputs that professional partners can integrate into their own projects.
The focus is reproducible pipelines for professional service providers — not generic AI demos.
AI & Computer VisionUAV / geospatial processingReproducible pipelinesWhite-label delivery workflows
FAQ
Technical questions before the first project.
Short answers for UAV, GIS, surveying and forestry teams.
01How quickly will I receive results?+
Timing depends on data volume, area and requested outputs. After data review, we provide a realistic estimate; sample processing uses a clearly bounded subset.
02What happens if data quality is insufficient?+
We respond with concrete QA notes and clarify early which outputs can be produced reliably.
03How does technical data handoff work?+
For v0, handoff is agreed via a suitable upload or cloud-storage route. Fixed S3 structures or API-adjacent workflows can be prepared for recurring partners.
04Can you generate rasters from UAV imagery?+
Optionally, yes. We review imagery, EXIF/GPS and sidecars and derive suitable raster foundations where data quality, overlap and project goals make this technically sensible.
05Which sidecar files help processing?+
MRK, RTK, NAV, OBS and OBK files are useful, as are complete flight folders and mission structures.
06What is the difference between a manifest and an Evidence Pack?+
A manifest describes one processing run or output package. The Evidence Pack bundles inputs, checksums, parameters, processing steps, outputs, QA and handoff into a project record.
07Is the Evidence Pack a certification?+
No. It documents our part of the workflow and supports internal QA and client documentation; it is not an external certification.
08Are revisions or QA questions included?+
Yes. QA questions are part of the process so inputs, output scope and delivery format are clearly defined.
Start with real data
Start with sample processing.
Send a bounded dataset. We will clarify raster foundations, deliverable forest layers and the right documentation depth.