TensorFlight provides high-quality data on commercial properties generated from images using state-of-the-art AI. Using different imagery sources from different perspectives (satellite, aerial, drone and street view) we are able to extract reliable data.
|Commercial building footprint||Polygon||Footprint of commercial or industrial building - e.g. shopping mall or gas station.|
|Residential building footprint||Polygon||Footprint of residential building - either house or block of flats.|
|Temporary building footprint||Polygon||Building-like structure that is not permanent - e.g. tent or trailer.|
|Missing part of building||Polygon||Part of the building that is missing a standard structure - e.g. it is still in construction or part of the roof that have been torn by a Hurricane|
|Building degradation||Polygon||Property degradation that is not affecting a structural integrity of the property - e.g. pooling water, missing shingles, facade paint cracking.|
|Tree||Bounding box||Tree - posing risk of catching fire or falling under heavy wind.|
|Dead tree||Bounding box||Dead tree is likely dead, so it's posing higher risk of fire and wind than tree with leaves.|
|Vehicle||Bounding box||Vehicle - e.g. car, truck or ship|
|Parking space||Bounding box||Parking space - counting empty parking spots helps estimate activity around the property.|
|Solar panels||Polygon||Group of solar panels. If multiple solar panels are adjacent they are counted as a one group.|
|Wind-borne debris||Bounding box||Items nearby property that can be blown by the wind and damage the property envelope - e.g. chairs, lumber, piles of trash.|
|Mechanical euipment on the roof||Bounding box||Mechanical equipment on the roof, that can be blown by the wind - e.g. HVAC.|
|Pool||Polygon||Swimming pool. Other water sources like ponds or fountains are not included|
|Window or skylight||Polygon||Either skylight on the roof or window on the facade.|
|Antenna or satellite dishes||Bounding box||Antennas or satellite dishes on the roof that can be blown by the wind.|
|Construction type||Classification||Classification of construction type - e.g. wood frame, masonry, tilt-up, engineered structure|
|Number of stories||Classificiation||Count of stories in the building.|
|Occupancy type||Classifitcation||Type of building usage - e.g. Retail trade, Professional technical and business, Apartment/Condo, Restaurants.|
|Signage||Bounding box||A sign that allows to extract more information about the business or pose a risk of blowing by the wind.|
|Door or gate||Polygon||Door, if visible from imagery.|
|Building height||Regression||Height of building in meters.|
|Estimated building age||Regression||Estimate building age based on the visual characteristics.|
|Roof shape||Classificiation||Flat, low/moderate/steep pitch.|
|Roof material||Classification||E.g. metal, shingle, tile.|
|Roof age||Regression||Time since roof was remodeled last time.|
Customization and other items
For client needs we also prepare individual projects that consist of:
- Improving accuracy of existing classes. We usually can reach 90%+ accuracy of direct work on a specific class in 2-8 weeks given priorities specified by the client.
- New object types. We can add also add new object classes upon request. It usually takes between 1 and 3 months to support a new object class.
How TensorFlight will deliver data results to me?
- Web dashboard: Web dashboard that allows users to request new processing or view and edit results of our analyses. Please create an account and explore the dashboard at https://tensorflight.com/app .
- GeoJSON: Standard format for describing GIS polygons easily integrated with web mapping tools available via the API accessible via an API.
- Shapefile: Shapefile is one of standard GIS formats that can be easily imported into tools like ArcGIS or QGIS available via the API of the dashboard.
- Vector tiles: URLs to slippy map tiles with vectors that can be overlaid on top of web based mapping tools available via the API. Example tile.
Rectangle around the object – min/max latitude/longitude.
Using this output type you can estimate object dimensions – e.g. bigger HVAC or bigger trees pose higher risk in case of a heavy wind. Based on object location we can also understand magnitude of the risk – e.g. tree or wind-borne debris dangerously close to the property is more likely to cause damage.