AI data & evaluation · Geospatial
A map becomes training data when the place has been verified.
Aerial and satellite imagery, street-level capture and map-anchored sensor traces, collected, annotated and validated for the model task. Processing in the EEA.
- Satellite imagery
- POI data
- GIS datasets
- Sensor data
- 3D spatial maps
The map says one thing.
The ground says another.
A routing model learns the wrong door, a perception model learns a lane that was repainted, a crop model learns last season. Geospatial training data holds when the place, the time and the geometry have been checked against the world, and that check is recorded with the data.
Satellite and Aerial Imagery
Satellite tiles and aerial capture annotated and classified for computer vision and remote sensing, with the acceptance metrics written for the imagery task.
- Multispectral analysis
- Object detection and classification
- Change detection between passes
POI and Geographic Datasets
Point-of-interest data geocoded, categorised and enriched with the attributes your model reads, and checked on the ground where the map is in doubt.
- Country coverage scoped per project
- Ground-truth verification by local contributors
- Custom attribute enrichment
3D Spatial Mapping
Point clouds and terrain models for navigation and urban planning, with position tolerances agreed per project and validated against reference measurements.
- Position tolerance agreed per project
- Textured mesh generation
- Semantic segmentation
Prove geospatial fitness on representative routes
A logistics pilot combines address, road, access-point, restriction, traffic and route data, then tests coverage, currency, geometry, provenance and delivery against your actual routing requirements.
The pilot returns sampled data, source and transformation records, metric definitions, validation findings, exceptions and a production recommendation.
Industries that run on location data
Public Sector and Critical Infrastructure
Infrastructure monitoring and emergency response
Finance and Insurance
Risk assessment and asset monitoring
Retail and E-commerce
Market analysis and site selection
Agriculture and Resources
Crop monitoring and resource management
Healthcare and Life Sciences
Population mapping and resource planning
Telecommunications
Network planning and coverage analysis
Five model tasks, and the data each one needs
Each task names its own coverage, currency and geometry requirement. The acceptance plan is written from those.
Autonomous Vehicles and Drones
Road geometry, lane markings, traffic signs and moving objects annotated for perception models, with the position tolerance your stack requires written into the acceptance plan.
What is delivered
- HD map features for autonomous navigation
- LiDAR point cloud annotation
- Traffic sign and signal recognition
- Dynamic object tracking data
Logistics and Last-Mile Delivery
Address locations, delivery zones, access points and restrictions verified on the ground, so a routing model learns the door the driver actually uses.
What is delivered
- Delivery zone mapping
- Access point identification
- Traffic and restriction currency
- Fleet routing data
Retail and Site Selection
Footfall patterns, competitor proximity, demographic overlays and accessibility scoring assembled with the provenance of every source recorded.
What is delivered
- Foot traffic analysis
- Competitor proximity mapping
- Demographic overlay data
- Accessibility scoring
Agriculture and Environmental Monitoring
Multispectral imagery across the growing season, with ground-truth comparison for crop health, yield prediction and irrigation models.
What is delivered
- Crop health monitoring
- Yield prediction modelling
- Irrigation planning
- Environmental impact assessment
Emergency Response and Disaster Management
Damage assessment, evacuation routing and resource allocation data, with the update latency measured so the model works on the map as it is today.
What is delivered
- Damage assessment imagery
- Evacuation route planning
- Resource allocation inputs
- Risk zone identification
Four acquisition channels, one delivery
Imagery, ground truth, integrated sources and annotation land in one schema with one provenance record
Remote Sensing and Imagery
Satellite, aerial and drone imagery acquired for the project, including multispectral and hyperspectral bands where the task reads them.
- Open and licensed satellite tiles
- Aerial and drone capture scoped per project
- Collection timed to the season and the task
- Processing of open satellite data
Ground Truth from Local Contributors
A 210,000+ contributor network across 50+ countries verifies places, addresses and access points on the ground and records what the map left out.
- Contributors recruited in the region
- Local knowledge and ground truth
- Coverage in emerging markets
- Hard-to-reach areas mapped on foot
Source Integration and Aggregation
Third-party geospatial APIs and open datasets normalised into one schema, with the provenance of each source kept.
- OpenStreetMap and GIS databases
- Data source normalisation
- Processing under GDPR
- ETL pipelines per project
Annotation and Enrichment
Semantic segmentation, object detection and attribute tagging by annotators qualified for geospatial work, with review at every stage.
- Model-assisted bounding box annotation
- Semantic classification
- Contextual data enrichment
- Multi-stage validation
Geospatial data integrity and compliance
Every check is reported against the acceptance plan agreed before collection
Quality Assurance
Multi-stage verification reports positional, classification, completeness, topology and freshness checks against the agreed acceptance plan.
Ethical and Regulatory Compliance
Location data identifies people by where they are. Personal data is anonymised or aggregated before delivery, consent is recorded per contributor and purpose, and local property and mapping law is checked per geography.
How the data is checked
GIS Specialists
Review and correction by specialists qualified for geospatial work
Documented Methods
Procedures and protocols written down and delivered with the data
Measured Acceptance
Project-specific metrics and evidence before production scale
QUESTIONS
Questions geospatial and mapping teams ask
Which geospatial data can YPAI deliver?
Satellite and aerial imagery, point-of-interest and geographic datasets, 3D point clouds and terrain models, street-level capture and map-anchored sensor traces, collected, annotated and validated for the model task.
How is a place verified on the ground?
Local contributors from a 210,000+ network across 50+ countries verify places, addresses and access points on site and record what the map left out.
How is quality checked?
In four steps: initial annotation, expert audit by GIS specialists, topological verification and multi-source calibration. Positional, classification, completeness, topology and freshness checks are reported against the acceptance plan agreed before collection.
How is location data about people handled?
Personal data is anonymised or aggregated before delivery, consent is recorded per contributor and purpose, and local property and mapping law is checked per geography. Processing happens in the EEA under a GDPR Article 28 DPA.
What does a pilot return?
Sampled data, source and transformation records, metric definitions, validation findings, exceptions and a production recommendation, tested against your coverage, currency and geometry requirements.
Which standards can a delivery follow?
The ISO 19115 metadata schema, with the Locus Charter as the ethical reference for location data use.
Geospatial data collected, labelled and delivered
YPAI collects and annotates satellite imagery, mapping and location data for the model task it has to support, and delivers it with the coverage, geometry and provenance record.
The place, verified. The record, delivered with it.
Scope a geospatial data project
Tell us the model task, the geography and the tolerance it has to hold. A named project lead replies inside one EU business day.
Scope a geospatial data project
A named project lead replies inside one EU business day.
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