Neighborhood Database from Urban Mapping
|Neighborhoods in San Francisco
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Traditional methods of defining urban environments, such as ZIP and postal codes, were created for administrative purposes. The ZIP code boundaries were established to allow for the most efficient means of mail delivery, not as a practical way to define regions.
The concept of the neighborhoods evolved through human perception, and hence neighborhoods are defined in a way that is consistent with the way people view urban space. Therefore, presenting location based information through the context of neighborhoods is a much more useable way to communicate information concerning urban geography.
Urban Mapping has organized informal neighborhood data making it
practical to use and simple to obtain. Plus it lines up perfectly with NAVTEQ street data!
Urban Mapping Neighborhood Database includes the following:
- Relationships and corresponding ZIP/postal codes
- Additional data, such as demographics and business listings are also available
- Quarterly Updates
US coverage includes more than 3,200 municipalities, representing more than 89,000 neighborhood names.
Canadian coverage includes 216 cities, representing more than 6,900 neighborhood names.
European coverage includes 70 cities across 14 countries, representing more than 10,000 neighborhood names.
Neighborhoods are informally defined. They are not defined by municipal governments, but defined for historical or cultural reasons. For example, downtown usually refers to a city’s commercial center, while New York’s TriBeCa is short for the “Triangle Below Canal Street.” There is no hard and fast rule that dictates how neighborhoods are defined or named.
Due to the informal nature of neighborhoods, boundaries can sometimes become fuzzy. While it may seem like a good idea to draw hard boundaries between neighborhoods, exclusive boundaries do not accurately describe locations situated on or close to the boundary.
Urban Mapping’s Neighborhood Database defines boundaries in a way that accounts for the informal nature of urban geography. Through recognizing that a location can technically be in two or more neighborhoods, they are able to eliminate binary boundaries and replace them with conditional boundaries. These conditional boundaries incorporate the fuzzy space that exists between neighborhoods and where neighborhood overlap occurs. This results in neighborhood boundaries that are not only more realistic and accurate, but also more in tune with the way people view informal space.
- Esri - shape (.shp) and File GeoDatabase format - (1 TB limit per dataset). Must have version 9.2
- Oracle 11g or 10g - Transportable Tablespaces or Import Version