The map of America is divided and subdivided by hundreds of geographies and geometries at a wide variety of spatial scales. Some of these ever-present boundaries are familiar, for example, the geopolitical boundaries of our towns, counties, and states. Others, like parcel data, are less frequently referenced, discussed, and visualized. But with its deep granularity and implications on land ownership, taxation, and more, parcel data is a powerful resource for data enrichment and spatial analysis.
Landgrid, a product of Detroit, Michigan-based Loveland technologies, is a national parcel dataset released in 2019. Noting that parcel data and geometries, while important, have often been inaccessible, requiring the compilation of data from wide-ranging and incomplete sources, their goal is for Landgrid to provide a unified view.
Boasting over 143 million land parcels across 2,800 counties, covering 95% of residents of The US and Puerto Rico, Landgrid is comprehensive. In addition to ID’s and geometric boundaries, much of their parcel data includes further detail such as address, owner, tax details and assessment information, and more. In total, their parcel data has additional detail across over 100 different data fields.
Take a look below at a sample of this parcel data, representing all parcels within a two mile radius of downtown Dallas, and visualized using CARTOframes:
Leveraging this data, within a solution that allows you to visualize and filter by the dataset’s additional fields and categorizations, can help to provide a deeper level of spatial insight for businesses and organizations across industries.
CARTO’s Data Observatory is designed to enable Data Scientists to augment their data and broaden their analyses with the latest and greatest in location data. With applications across dozens of industries, adding Landgrid’s parcel data is a no-brainer and an instant value add for CARTO users. Among its many applications, this data can be used to augment analysis for:
Start augmenting your data and leveraging Landgrid’s parcel data in your analysis today!
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