Parcel Boundaries USA
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https://marketplace.databricks.com/details/d458f337-3fdb-48ab-8b08-37fe31fdfda3/Precisely_Parcel-Boundaries-USA
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**Overview**
Parcel boundary data helps users map and analyze property characteristics across an entire area of interest, or conduct sophisticated spatial analysis such as proximity, overlay, and buffer zone operations. Parcel Boundaries contains polygonal property outlines. Features within the dataset, such as the PreciselyID and Assessor Parcel Numbers, enable interoperability with property attributes, building footprints, U.S. Census Bureau data, and address genealogy.
This is a free sample of Precisely's Parcel Boundaries USA product covering the San Francisco, CA area. The full USA product is available as Paid access. Contact Databricks.partnership@precisely.com for full product licensing information.
**Use cases**
**Location Data Enrichment**
Link Parcel Boundaries to World Points of Interest, Property Attribute Assessments, and Buildings for improved location intelligence
**Risk Analysis**
Quantify risks associated with flood, wildfire, or other hazards to accurately price insurance policies & assess damage after catastrophic events by overlaying parcel data on satellite imagery
**Location Planning**
Locate retail and site properties for sale and learn more about surrounding geographies
**Location Geocoding**
Identify property location, centroids and boundaries, for display and spatial analysis
**Product details**
Parcel Boundaries is one of the property data enrichment products that work with Precisely Property Graph.
Parcel Boundaries provide polygons with the following attribution:
• Unique parcel identifier
• FIPS and APN
• Census codes for state, county, tract, block group, and block
• Centroid elevation in feet
• Centroid latitude and longitude
• Property primary base street address
• Property unit number
• Property city
• Property state
• Property postal code
For more details, refer to the embedded notebook.
**Additional Insights**
https://support.precisely.com/
提供机构:
Precisely



