Comprehensive core data flips industry model
Geospatial data users have a need for accurate, up-to-date information to make informed decisions. They need to know the reality of a location – what’s there and what’s not. And their preference is to have that without having to travel there themselves to see. That’s where Spatiall Data comes in. It provides a solid core of current information about the road infrastructure, regularly mapped in the Netherlands.
A trusty core of truth
Spatiall Data is created from data physically collected over thousands of kilometers by our mapping drivers – millions of images and data points. Every year, they map the entire country by driving its public roads and capturing a panoramic image every five meters. This isn’t selective sampling or partial coverage. It’s systematic, repeatable, and complete.
Our mapping vehicles combine high-resolution panoramic cameras with LiDAR technology, generating images and detailed point clouds and precisely geolocating every data point using GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System).
This combination provides comprehensive information about what is there at ground level. It includes all the assets surrounding the roads – like traffic signs, light poles, and street furniture.
Check and balances to confirm quality
Accuracy is not achieved by chance – it is the result of a carefully controlled refinement process. After data is captured, it enters a structured refinement pipeline where quality is verified at multiple stages before it can be used further.
Each recording is first validated through automated pre-checks to ensure completeness, correct metadata, and technical consistency. Only data that passes these checks continues through the pipeline.
From there, image and LiDAR data are processed using specialized workflows. Images are georeferenced, privacy-sensitive elements are blurred, and panoramic imagery is prepared for further use. LiDAR data is processed into accurate point clouds.
Throughout this process, we continuously apply quality controls. We check data for positional accuracy, completeness, and usability. Only data that has successfully passed these quality checks is made available for downstream use, such as AI-based extraction and publication.
This quality-first approach ensures that users can rely on Spatiall Data as a trusted, accurate, and verifiable foundation for decision-making.
Preparing for publication
When the data is ready for publication, it is rendered. Because of the sheer amount of information collected, data sizes are enormous, and not ideal for storage or streaming. As an example, a one-hour recording fills 40GB of space, and could even reach 100GB! That’s because it holds a great deal of information – hi-res and panoramic images, multiple sensor output, and dense LiDAR data.
The images are compressed to reduce data size, and the team divides panoramic images into Virtual Camera Images (VCAM). This software produces digital pictures from specific angles and a standard resolution, which is used for development and analysis. This all helps in the process to prepare them for the next stage in the Spatiall process – AI extraction and enrichment.
The refined data is then made available to users and made available in the Spatiall Studio viewing platform.
Fresh, relevant, and accurate data for informed decisions
For governments, infrastructure specialists, and utility companies, outdated or incomplete spatial data is risky. It leads to unnecessary site visits, slower decision-making, and higher costs. It can also have a substantial environmental impact.
Spatiall Data flips that model. By providing an accurate, up-to-date, and verifiable geospatial data core, organizations can assess, manage, and maintain infrastructure remotely and efficiently. It also provides a strong base for extraction and analysis to provide valuable insights in the future. That all means fewer field trips, better decisions, and lower costs.