Discover. Validate. Create.
Flexible solutions delivering a deeper understanding to our planet
Join the HIVEGeoHIVE is a Collective Intelligence Platform.
The world is in a constant state of change. From naturally-occurring phenomena to manmade events, the world of today is nothing like the world of yesterday and will be nothing like the world of tomorrow. GeoHIVE enables organizations, small and large, to do more with geospatial data. Our cutting edge Machine Learning models and highly accurate crowdsourced data are all powered by Maxar’s high resolution satellite imagery.
Our Services
Dataset Creation
Fast data creation over a large area of interest—including points of interest, bounding boxes, and semantic segmentations—we provide the capabilities to generate results with the highest spatial accuracy and confidence.
Data Validation
We combine crowdsourcing and Machine Learning to validate and enrich massive amounts of distributed data. Our models help eliminate unnecessary work from the crowd and crowdsourcing labels what is left, saving you time and money.
Training Datasets
High-quality training data is essential in producing accurate and effective machine learning algorithms. Spatiotemportal datasets can be used to optimize your existing Machine Learning models.
Customizable end-to-end solutions providing a richer view into geospatial data.
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Public
Infrastructure -
Disaster
Response -
Oil & Gas
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Wildlife
Use Cases
GeoHIVE has a wide variety of uses that are not exclusive to any one industry or project. GeoHIVE’s provides insight for emergency response services, government organizations, commercial businesses, and NGOs. Whether it’s a damage reporting after a natural disaster, creating training tools for machine learning, or monitoring wildlife populations, GeoHIVE campaigns can answer the tough questions and provide fast situational awareness to reduce time to action.
Training Dataset Workflow
Meet with client to understand the business context and needs.
Raw data is sourced
Validation and labeling of data
Models are trained
Training data is sent to the model
Highest confidence data is sent to customer
