Unify disparate data, add spatial context, and exponentially increase the features available in your analysis and modeling.
Make your data “spatially aware” and AI Ready
Streamline geospatial data ingestion and unification
- Remove the complexity and data wrangling from geospatial data unification.
- Automatically join unlimited datasets based on shared location.
- Integrate spatial and non-spatial data.
Augment data with ease
- Contextualize your data with Paper Crane’s convenient extensive library of curated foundational data layers.
- Leverage 100s of data layers available including property boundaries, building footprints, roads, schools, flood zones, census, elevation, tree canopy, historic fire burn parameters, aerial imagery, and many others.
- Append 100’s of additional Paper Crane-derived characteristics such as topographic position, distance from front door to nearest road, percent tree canopy cover over the roof, hardscape area, etc.
Transform spatial data and expose relationships
- Take advantage of automatic spatial feature engineering designed to expose the full information content hidden within spatial data.
- Expand your feature set with explicit variables representing intra and inter-feature relationships such as proximities, densities, spatial inclusions and overlaps, zonal statistics, and more.
AI-enable geospatial data
- Turn hundreds of disparate data layers into single unified tabular data ready for ingestion into downstream modelling applications.
- Aggregate variables across all layers to any new spatial geometry in seconds.
- Export your AI-ready data in a format of your choice for downstream processing.
Centralize geospatial data
- Eliminate analysis silos by centralizing geospatial data in Paper Crane.
- Give all your teams the accurate, curated and expanded data they need to do their jobs faster and better.
- Ingest over 250 different supported formats (both spatial and non-spatial) including vector formats, imagery (aerial and satellite), and other raster data.
Powerful User Interface
Streamline data ingestion and unification to save time
Centralize, combine and integrate spatial and non-spatial data
Transform and expand data via automated spatial feature engineering
AI-enable geospatial data for advanced predictive analytics
Augment data with contextual and geospatial information to uncover new insights