--- title: "Geospatial Data Solutions | YPAI" url: https://ypai.ai/geospatial-data-solutions/ description: "Aerial, satellite and street-level imagery plus map-anchored sensor traces, collected, annotated and validated for the model task, ground-verified, in the EEA." source: "src/copy/routes (route /geospatial-data-solutions/)" --- # A map becomes training data when the place has been verified. > Aerial, satellite and street-level imagery plus map-anchored sensor traces, collected, annotated and validated for the model task, ground-verified, in the EEA. - imagery, maps, points, tracks and sensor data - coverage, currency, geometry and quality acceptance ## 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. ## 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. ## 3D Spatial Mapping - Point clouds and terrain models for navigation and urban planning, with position tolerances agreed per project and validated against reference measurements. ## Public Sector and Critical Infrastructure ## Finance and Insurance ## Retail and E-commerce ## Agriculture and Resources ## Healthcare and Life Sciences ## Telecommunications ## Autonomous Vehicles - 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. - HD map features for autonomous navigation ## Logistics and Delivery - Address locations, delivery zones, access points and restrictions verified on the ground, so a routing model learns the door the driver actually uses. ## Retail and Site Selection - Footfall patterns, competitor proximity, demographic overlays and accessibility scoring assembled with the provenance of every source recorded. ## Agriculture and Environment - Multispectral imagery across the growing season, with ground-truth comparison for crop health, yield prediction and irrigation models. ## Emergency Response - Damage assessment, evacuation routing and resource allocation data, with the update latency measured so the model works on the map as it is today. ## Remote Sensing and Imagery - Satellite, aerial and drone imagery acquired for the project, including multispectral and hyperspectral bands where the task reads them. - Aerial and drone capture scoped per project - Collection timed to the season and the task ## 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. ## Source Integration and Aggregation - Third-party geospatial APIs and open datasets normalised into one schema, with the provenance of each source kept. ## Annotation and Enrichment - Semantic segmentation, object detection and attribute tagging by annotators qualified for geospatial work, with review at every stage. ## Initial Annotation ## Expert Audit ## Topological Verification ## Multi-Source Calibration ## Privacy Protection - Personal data anonymised or aggregated before delivery ## GDPR Compliance ## Local Law - Property rights and regional regulations checked per geography ## Bias Assessment ## Locus Charter - The ethical reference for location data use ## ISO 19115 - The metadata schema a delivery can follow ## 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 Aerial and satellite imagery, street-level capture and map-anchored sensor traces, collected, annotated and validated for the model task. Processing in the EEA. ## 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. ## 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. Configured to the geography, the use case and the tolerance model Industries that run on location data ## 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. ## Four acquisition channels, one delivery Imagery, ground truth, integrated sources and annotation land in one schema with one provenance record ## 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 ## 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. - GDPR Article 28 DPA on every engagement A named project lead replies inside one EU business day. Processed in the EEA under a GDPR Article 28 DPA ## 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.