Frequently Asked Questions (FAQ)

A geospatial data platform, such as the one developed by north.io is designed to manage, visualise, and analyse both terrestrial and marine geospatial data efficiently. This platform leverages cloud-native technology to provide scalable data storage and processing, ensuring users can handle growing data volumes with ease. It supports 2D and 3D visualisations directly in a web browser, requiring no special hardware or software. This enables users to find, share, and visualise data seamlessly, enhancing the efficiency and accuracy of geospatial data handling for various projects. Additionally, the platform includes advanced features such as smart geospatial search, which allows users to locate hydrographic survey and underwater inspection data quickly using a map-based interface. This significantly improves data management efficiency by reducing the time needed to find specific datasets. The platform also supports secure data storage and protection, making it a reliable solution for managing valuable geospatial data across different environments. Read more about geospatial data.

Data quality control for raw sensor datasets is crucial before proceeding with further analytics. For Multibeam datasets, the algorithms focus on various parameters including the altitude-range ratio, beam footprint measurements (across track, along track, and area), spatial coverage, data point density, general data point spacing, and resolution (both horizontal and vertical). Additionally, sensor motion is also taken into account.

For Side Scan Sonar datasets, quality control algorithms assess the altitude-range ratio, beam footprint along track, coverage, general data point spacing, and signal quality (signal-to-noise ratio and signal footprint across track). For Subbottom profiler data, the algorithms consider cmp fold, beam footprint, coverage, data point spacing, horizontal resolution, and signal-to-noise ratio. Magnetics data is checked for altitude, data point spacing (both across track/line spacing and along track), footprint, and signal-to-noise ratio. Lastly, Pointclouds are evaluated based on point density and point spacing.

Data analysis on raw datasets, particularly at the pointcloud level, involves a variety of specialised algorithms tailored to specific use cases. These algorithms include Anisotropy, which measures directional dependency, and Change of Curvature, which identifies variations in curvature. Geomorphons categorize landform elements, while Gradient and Gradient Factor assess slope steepness and changes. Horizontal and Vertical Curvature algorithms evaluate surface curvature in respective planes. Additional functions such as Linearity, Maximal Curvature, Mean Curvature, Minimal Curvature, Omnivariance, Planarity, Point Density, and Point Spacing provide detailed surface analysis. Other significant functions include Rotor, Slope Aspect, Slope Steepness, Sphericity, Topographic Positioning Index, Terrain Ruggedness Index, and Unsphericity, each contributing to a comprehensive understanding of the terrain and underlying features. Read more on data analysis.

The native cloud geospatial data platform allows secure data storage, protection and redundancy, automated backups and recovery which is crucial in complex infrastructure projects. The technology is cloud-agnostic, operating on all cloud types (public, private and hybrid) and can be adapted to almost any environment. It is based on the microservice architecture pattern based on Kubernetes allowing data and application isolation, standardised high-performance interfaces and scalability for all workloads. Read more about data security on our architecture paper.

Our business model focuses on delivering Software as a Service (SaaS) solution designed to meet your specific needs. The foundation of our pricing model is a monthly subscription fee, which includes access to the geospatial data platform and a specified number of user seats. Additionally, the subscription fee covers data storage, with redundancy through a second availability zone and backup options using S3 cloud storage. To enhance your experience and support your operations, we offer first-level support, regular software updates, a comprehensive onboarding, workshops, and training sessions. We also provide a variety of modules to cater to your unique requirements, such as weather information (provided by Spire Global) and a Track Planner. Further support is available through additional services, including data preparation, consulting, and API integration. Our flexible pricing model ensures you only pay for what you use, with the ability to scale services and storage according to your needs. This approach allows us to offer competitive pricing while delivering high-quality, reliable services tailored to your requirements. Read more about our SaaS model.