Polygon Data: Best Polygon Datasets & Databases
Recommended Polygon Data Products
Xtract.io Polygon Data | All Park and Ride store locations data in US and Canada
ZIP+4. Complete dataset based on US postal data consisting of plus 35 millions of polygons
Xtract.io Polygon Data | Stores within top 150 Airports in US and Canada
Getchee - Shopping streets in South Korea (POI data, polygons)
Xtract.io Polygon Data | Automotive and Repair Shops in US and Canada
Xtract.io Polygon Data | New Car Dealers (Automotive) store locations data in US and Canada
Xtract.io Location data | Polygon Geofences for Beverage places in US and Canada
Xtract.io Polygon Data | Centre Points and Boundaries of Heliports in US and Canada
Xtract.io Polygon Data | Centre Points and Boundaries of Airports in US and Canada
Xtract.io Polygon Data | All Home Furnishing and Electronics, Home Centre stores in US and Canada
More Polygon Data Products
The Ultimate Guide to Polygon Data 2023
What is Polygon Data?
Polygon data is geospatial information relating to the boundaries of a chosen building or area. It’s used to develop a better understanding of real world surroundings and has a range of location-based use cases, from digital marketing to urban development.
What are the attributes of Polygon Data?
Polygon data is a subcategory of POI data. As such, it shares many of the same data attributes. Most obviously, lat/long coordinates, which are an attribute of almost all branches of geospatial data. Similarly, polygon data will also include the street name and ZIP code the polygon belongs to.
Polygon data is also related to building shapes and building footprint data. As such, these data types share many overlapping data attributes. A polygon database will typically include building-specific attributes, like building type, building ID, and building footprint area. More advanced polygon data providers will be applied to supply additional data points. These attributes include the building purpose (retail, office space, public amenity), its opening hours, and even the stock ticker of the company which owns the building.
What are the use cases of Polygon Data?
If you’re a business owner looking to expand stores, it’s likely that you’ll research local POIs in order to select a site with strong foot traffic. Adding more polygons using external polygon datasets to enrich your in-house data adds an additional layer of coverage to your POI mapping. It means there are no gaps in your location intelligence, so you’re more likely to choose a strong, well-connected site.
Geotargeting is when marketers and advertisers target a consumer based on their real world locations. There are lots of location-based marketing strategies relying on geotargeting - many of which rely on polygon data. For example, programmatic advertising. Marketers can trigger adverts to be displayed when a consumer enters a certain polygon. For example, an advert for a specific restaurant within a shopping mall may be displayed on the consumer’s phone when the individual crosses the boundary into the mall.
What are the sources of Polygon Data?
To understand shapes from overhead, satellites provide an aerial view of the outer boundaries of a polygon. This is the same technology that’s used for GPS navigation. The images created by satellites are then analyzed and the areas of interest divided into polygons based on the boundaries, buildings and regions the user is interested in. Typically, this raw polygon data is aggregated and anonymized for privacy purposes. This way, the satellite images won’t include footage of people, only building footprints and POIs.
Polygon datasets are becoming more precise thanks to new data collection techniques. These include machine learning. Machine learning is also helping data providers deliver more reliable data products. For example, a polygon API will provide instant, ultra-precise updates about a polygon. This is especially useful for data cleansing. To give an example scenario, a polygon database sourced from outdated satellite imagery may indicate that a derelict building is still in use as a shopping center. Howreve, an ML-optimized polygon API would detect that the building is out of commercial use. This way, users only focus on polygons really relevant to them. Keeping with the shopping center scenario, an ML-verified polygon data provider would reduce research time for retail site selection as the data would show straight away whether or not a building is suitable or not.
Where can I buy Polygon Data?
Data providers and vendors listed on Datarade sell Polygon Data products and samples. Popular Polygon Data products and datasets available on our platform are Xtract.io Polygon Data | All Park and Ride store locations data in US and Canada by Xtract, ZIP+4. Complete dataset based on US postal data consisting of plus 35 millions of polygons by Geojunxion, and Xtract.io Polygon Data | Stores within top 150 Airports in US and Canada by Xtract.
How can I get Polygon Data?
You can get Polygon Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Polygon Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Polygon Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Polygon Data?
Polygon Data is similar to Building Footprint Data and POI Visitation Data. These data categories are commonly used for Geotargeting and Digital Out-of-home (DOOH) Advertising.
What are the most common use cases for Polygon Data?
The top use cases for Polygon Data are Geotargeting, Digital Out-of-home (DOOH) Advertising, and Foot Traffic Analytics.