CSV Table. This table includes coded descriptions for Land Use Codes in the St. Louis County, Missouri parcel dataset. This is the land use description for a property. Please see field LUCODE in the Parcel dataset. Link to Metadata.

Zip Codes (5-digit). The dataset polygons represent location and attributes of zip codes, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Zip Codes were identified from public records (US Postal Service) and created selecting arcs from the street centerlines and vector property map.

MassGIS had received quarterly updates of these data as part of its license for the HERE (Navteq) core map release (streets and related data); however, that license has expired. These ZIP Code boundaries are aligned to the street centerlines of the Q2 2018 HERE product (with a release date of April 1, 2018) and use a then-recent USPS source file.In March 2024, MassGIS modified the boundaries for all ZIP Code areas in Boston based on the U.S. Postal Service's ZIP Code Look Up by Address website. MassGIS also added polygons for ZIP Codes 02199 and 02203.Five-digit ZIP Codes were developed by the USPS and first introduced in 1963 for efficient mail delivery (the term ZIP stands for Zone Improvement Plan) but are difficult to map with complete certainty. In most cases, addresses in close proximity to each other are grouped in the same ZIP Code, which gives the appearance that ZIP Codes are defined by a clear geographic boundary. However, even when ZIP Codes appear to be geographically grouped, a clear ZIP Code boundary cannot always be drawn because ZIP Codes are only assigned to a point of delivery and not the spaces between delivery points. In areas without a regular postal route or no mail delivery, ZIP Codes may not be defined or have unclear boundaries.The USPS does not maintain an official ZIP Code map. The Census Bureau and many other commercial services will interpolate the data to create polygons to represent the approximate area covered by a ZIP code, but none of these maps are official or entirely accurate. Please see this good discussion of the issues of mapping ZIP Codes.See full metadata.Feature service also available.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 36 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 29 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This feature service is derived from the Esri "United States Zip Code Boundaries" layer, queried to only CA data.For the original data see: https://esri.maps.arcgis.com/home/item.html?id=5f31109b46d541da86119bd4cf213848Published by the California Department of Technology Geographic Information Services Team.The GIS Team can be reached at ODSdataservices@state.ca.gov.U.S. ZIP Code Boundaries represents five-digit ZIP Code areas used by the U.S. Postal Service to deliver mail more effectively. The first digit of a five-digit ZIP Code divides the United States into 10 large groups of states (or equivalent areas) numbered from 0 in the Northeast to 9 in the far West. Within these areas, each state is divided into an average of 10 smaller geographical areas, identified by the second and third digits. These digits, in conjunction with the first digit, represent a Sectional Center Facility (SCF) or a mail processing facility area. The fourth and fifth digits identify a post office, station, branch or local delivery area.As of the time this layer was published, in January 2025, Esri's boundaries are sourced from TomTom (June 2024) and the 2023 population estimates are from Esri Demographics. Esri updates its layer annually and those changes will immediately be reflected in this layer. Note that, because this layer passes through Esri's data, if you want to know the true date of the underlying data, click through to Esri's original source data and look at their metadata for more information on updates.Cautions about using Zip Code boundary dataZip code boundaries have three characteristics you should be aware of before using them:Zip code boundaries change, in ways small and large - these are not a stable analysis unit. Data you received keyed to zip codes may have used an earlier and very different boundary for your zip codes of interest.Historically, the United States Postal Service has not published zip code boundaries, and instead, boundary datasets are compiled by third party vendors from address data. That means that the boundary data are not authoritative, and any data you have keyed to zip codes may use a different, vendor-specific method for generating boundaries from the data here.Zip codes are designed to optimize mail delivery, not social, environmental, or demographic characteristics. Analysis using zip codes is subject to create issues with the Modifiable Areal Unit Problem that will bias any results because your units of analysis aren't designed for the data being studied.As of early 2025, USPS appears to be in the process of releasing boundaries, which will at least provide an authoritative source, but because of the other factors above, we do not recommend these boundaries for many use cases. If you are using these for anything other than mailing purposes, we recommend reconsideration. We provide the boundaries as a convenience, knowing people are looking for them, in order to ensure that up-to-date boundaries are available.

The City of Tempe ZIP Codes feature class is from Maricopa County GIS Open Data and is intended to show the USPS ZIP Code boundaries within Tempe, Arizona.

CSV Table. This table includes coded descriptions for Property Class Codes in the St. Louis County, Missouri Parcel dataset. Property Class Codes are the Tax Subclass Codes for a property. Please see field PROPCLASS in the Parcel dataset. Link to Metadata.

This dataset contains model-based ZIP Code tabulation Areas (ZCTA) level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 27 measures at the ZCTA level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.

Census ZIP Code Tabulation Areas This feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays ZIP Code Tabulation Areas in the United States. Per the USCB, “ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery.” Tabulation Area: 90210 Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (ZIP Code Tabulation Areas) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 58 (Series Information for 2020 Census 5-Digit ZIP Code Tabulation Area (ZCTA5) National TIGER/Line Shapefiles, Current)OGC API Features Link: (Census ZIP Code Tabulation Areas - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: ZIP Code Tabulation Areas (ZCTAs)For feedback please contact: Esri_US_Federal_Data@esri.comThumbnail source: Esri BasemapsNGDA Data Set This data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the “boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes.” For other NGDA Content: Esri Federal Datasets

This dataset represents ZIP code boundaries in Pima County. ZIP codes are used by the USPS for mail delivery but are linear routes, not polygons. The ZIP code polygons in this dataset are approximations based on parcel boundaries and exclude unique ZIP codes (e.g., high-volume locations or PO boxes).

For more information, see Pima County's metadata here.

Purpose To display approximate areas of ZIP codes within Pima County for planning and geographical analysis.

Dataset Classification Level 0 – Open

Known Uses Supports planning, and demographic analysis.

Known Errors ZIP code polygons are approximations; USPS ZIP codes are based on mail carrier routes. Unique, military, and PO box ZIP codes are excluded.

Data Contact Steve Whitney Pima County GIS GISdata@pima.gov

Update Frequency As needed based on changes to ZIP code boundaries.

High-precision polygonal and centroid-based geographic representations of all U.S. postal ZIP Codes for mapping, analytics, and data enrichment. Built from USPS carrier route data with quarterly updates. Includes boundary polygons (~41,000 deliverable ZIP Codes) and centroids (~33,000 total ZIP Codes including PO Box and Unique types). Features continuous nationwide coverage with filler ZIPs, delivery statistics (residential, multifamily, single-family, business counts), and support for 8 file formats: Shapefile, GeoJSON, SQL Server, MySQL, PostgreSQL, WKT, CSV, and KML. WGS84 coordinate system with 6 decimal precision. Compatible with all major GIS platforms including ArcGIS, QGIS, MapInfo, Tableau, Power BI, and web mapping libraries. All purchases include quarterly updates, unlimited downloads, FTP access, and free technical support.

This feature class was created by exporting the Census Zip Code features from the 2020 TIGER/Line Geodatabase.TIGER Geodatabases are spatial extracts from the Census Bureau’s MAF/TIGER database. These files do not include demographic data, but they contain geographic entity codes that can be linked to the Census Bureau’s demographic data.

This dataset represents an ongoing effort to approximate the geographic extents of 5 digit zip codes. The dataset was produced using a combination of methods and is based on several sets of source data. Methods include: 1) using local zip code polygon data obtained from counties and cities contained within these counties; 2 ) examining the 2000 Census TIGER line file's zip code attributes; and 3) using UGRC address grid quadrant boundaries to assign the zip code to segments within a boundary corresponding to a place location (city, town, places) from the postal service website and address information system (AIS). In addition, UGRC has used the locations of mailing addresses known to have valid zip codes to fine tune this dataset.

This layer originated from ZCTAs and has been modified in places by Grant County GIS staff based on input from local US Postal Service staff and landowners.ZIP Code Tabulation Areas (ZCTAs™) are a statistical geographic entity produced by the U.S. Census Bureau for tabulating summary statistics from the 2010 Census, first developed for Census 2000. This entity was developed to overcome the difficulties in precisely defining the land area covered by each ZIP Code™, which is necessary in order to accurately tabulate census data for that area.ZCTAs are generalized area representations of U.S. Postal Service (USPS) ZIP Code service areas. They represent the most frequently occurring five-digit ZIP Code found in a given area. Simply put, each ZCTA is built by aggregating 2010 Census blocks, whose addresses use a given ZIP Code. Each resulting ZCTA is then assigned the most frequently occurring ZIP Code as its ZCTA code. For more information, please refer to the ZCTA Frequently Asked Questions (FAQ).

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

This dataset represents the Zip code boundaries within Jackson County. This data is based on ECSO911 'Community' layer.

US Postal Service ZIP Code boundaries in Wake County, NC. This dataset is updated as needed when property lines change and when source data from the US Postal Service is updated, and it is maintained by the Wake County GIS Addressing Team. GIS metadata is available here.

Overview

This dataset contains all DOMI Street Closure Permit data in the Computronix (CX) system from the date of its adoption (in May 2020) until the present. The data in each record can be used to determine when street closures are occurring, who is requesting these closures, why the closure is being requested, and for mapping the closures themselves. It is updated hourly (as of March 2024).

Preprocessing/Formatting

It is important to distinguish between a permit, a permit's street closure(s), and the roadway segments that are referenced to that closure(s).

• The CX system identifies a street in segments of roadway. (As an example, the CX system could divide Maple Street into multiple segments.)

• A single street closure may span multiple segments of a street.

• The street closure permit refers to all the component line segments.

• A permit may have multiple streets which are closed. Street closure permits often reference many segments of roadway.

The roadway_id field is a unique GIS line segment representing the aforementioned segments of road. The roadway_id values are assigned internally by the CX system and are unlikely to be known by the permit applicant. A section of roadway may have multiple permits issued over its lifespan. Therefore, a given roadway_id value may appear in multiple permits.

The field closure_id represents a unique ID for each closure, and permit_id uniquely identifies each permit. This is in contrast to the aforementioned roadway_id field which, again, is a unique ID only for the roadway segments.

City teams that use this data requested that each segment of each street closure permit be represented as a unique row in the dataset. Thus, a street closure permit that refers to three segments of roadway would be represented as three rows in the table. Aside from the roadway_id field, most other data from that permit pertains equally to those three rows. Thus, the values in most fields of the three records are identical.

Each row has the fields segment_num and total_segments which detail the relationship of each record, and its corresponding permit, according to street segment. The above example produced three records for a single permit. In this case, total_segments would equal 3 for each record. Each of those records would have a unique value between 1 and 3.

The geometry field consists of string values of lat/long coordinates, which can be used to map the street segments.

All string text (most fields) were converted to UPPERCASE data. Most of the data are manually entered and often contain non-uniform formatting. While several solutions for cleaning the data exist, text were transformed to UPPERCASE to provide some degree of regularization. Beyond that, it is recommended that the user carefully think through cleaning any unstructured data, as there are many nuances to consider. Future improvements to this ETL pipeline may approach this problem with a more sophisticated technique.

Known Uses

These data are used by DOMI to track the status of street closures (and associated permits).

Further Documentation and Resources

An archived dataset containing historical street closure records (from before May of 2020) for the City of Pittsburgh may be found here: https://data.wprdc.org/dataset/right-of-way-permits