7 datasets found
  1. C

    Neighborhoods

    • data.wprdc.org
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +2more
    csv, geojson, html +2
    Updated Sep 17, 2025
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    City of Pittsburgh (2025). Neighborhoods [Dataset]. https://data.wprdc.org/dataset/neighborhoods2
    Explore at:
    csv, html, kml(1078560), zip(329463), geojson(1200006)Available download formats
    Dataset updated
    Sep 17, 2025
    Dataset authored and provided by
    City of Pittsburgh
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Pittsburgh Neighborhoods

  2. C

    Redlining Maps from the Home Owners Loan Corporation, 1937

    • data.wprdc.org
    • gimi9.com
    geojson, html, jpeg +1
    Updated Jul 8, 2025
    + more versions
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    Western Pennsylvania Regional Data Center (2025). Redlining Maps from the Home Owners Loan Corporation, 1937 [Dataset]. https://data.wprdc.org/dataset/redlining-maps-from-the-home-owners-loan-corporation
    Explore at:
    jpeg(46615911), zip(38339897), html, zip(12934532), jpeg(10667368), zip(7566), jpeg(13882165), zip(10818554), zip(7807), zip(17077497), geojson(54280), zip(10561768), zip(24301995), jpeg(5141992), geojson(39108), zip(12025), jpeg(6317290), zip(45384487), geojson(593066), geojson(46444), zip(75315), zip(7509), geojson(60598), zip(154680053), geojson(269553), zip(31784339)Available download formats
    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Western Pennsylvania Regional Data Center
    License

    http://www.opendefinition.org/licenses/cc-by-sahttp://www.opendefinition.org/licenses/cc-by-sa

    Description

    Most of the text in this description originally appeared on the Mapping Inequality Website. Robert K. Nelson, LaDale Winling, Richard Marciano, Nathan Connolly, et al., “Mapping Inequality,” American Panorama, ed. Robert K. Nelson and Edward L. Ayers,

    "HOLC staff members, using data and evaluations organized by local real estate professionals--lenders, developers, and real estate appraisers--in each city, assigned grades to residential neighborhoods that reflected their "mortgage security" that would then be visualized on color-coded maps. Neighborhoods receiving the highest grade of "A"--colored green on the maps--were deemed minimal risks for banks and other mortgage lenders when they were determining who should received loans and which areas in the city were safe investments. Those receiving the lowest grade of "D," colored red, were considered "hazardous."

    Conservative, responsible lenders, in HOLC judgment, would "refuse to make loans in these areas [or] only on a conservative basis." HOLC created area descriptions to help to organize the data they used to assign the grades. Among that information was the neighborhood's quality of housing, the recent history of sale and rent values, and, crucially, the racial and ethnic identity and class of residents that served as the basis of the neighborhood's grade. These maps and their accompanying documentation helped set the rules for nearly a century of real estate practice. "

    HOLC agents grading cities through this program largely "adopted a consistently white, elite standpoint or perspective. HOLC assumed and insisted that the residency of African Americans and immigrants, as well as working-class whites, compromised the values of homes and the security of mortgages. In this they followed the guidelines set forth by Frederick Babcock, the central figure in early twentieth-century real estate appraisal standards, in his Underwriting Manual: "The infiltration of inharmonious racial groups ... tend to lower the levels of land values and to lessen the desirability of residential areas."

    These grades were a tool for redlining: making it difficult or impossible for people in certain areas to access mortgage financing and thus become homeowners. Redlining directed both public and private capital to native-born white families and away from African American and immigrant families. As homeownership was arguably the most significant means of intergenerational wealth building in the United States in the twentieth century, these redlining practices from eight decades ago had long-term effects in creating wealth inequalities that we still see today. Mapping Inequality, we hope, will allow and encourage you to grapple with this history of government policies contributing to inequality."

    Data was copied from the Mapping Inequality Website for communities in Western Pennsylvania where data was available. These communities include Altoona, Erie, Johnstown, Pittsburgh, and New Castle. Data included original and georectified images, scans of the neighborhood descriptions, and digital map layers. Data here was downloaded on June 9, 2020.

  3. p

    Asset-based Community Development and Outreach Map Western Regional Data...

    • data.pa.gov
    csv, xlsx, xml
    Updated Jun 17, 2020
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    Federal, State and Local Authorities (2020). Asset-based Community Development and Outreach Map Western Regional Data Center Pittsburgh [Dataset]. https://data.pa.gov/Local-Government/Asset-based-Community-Development-and-Outreach-Map/vr45-6mwi
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Jun 17, 2020
    Dataset authored and provided by
    Federal, State and Local Authorities
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    Pittsburgh
    Description

    The asset map is designed to help people implement asset-based community development and outreach, and includes data from a number of available local, state, and federal data sources.

  4. Data from: Development of Crime Forecasting and Mapping Systems for Use by...

    • icpsr.umich.edu
    • datasets.ai
    • +2more
    Updated Aug 31, 2006
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    Cohen, Jacqueline; Gorr, Wilpen L. (2006). Development of Crime Forecasting and Mapping Systems for Use by Police in Pittsburgh, Pennsylvania, and Rochester, New York, 1990-2001 [Dataset]. http://doi.org/10.3886/ICPSR04545.v1
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    Dataset updated
    Aug 31, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Cohen, Jacqueline; Gorr, Wilpen L.
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/4545/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/4545/terms

    Time period covered
    1990 - 2001
    Area covered
    Rochester, New York, Pittsburgh, Pennsylvania, United States, New York
    Description

    This study was designed to develop crime forecasting as an application area for police in support of tactical deployment of resources. Data on crime offense reports and computer aided dispatch (CAD) drug calls and shots fired calls were collected from the Pittsburgh, Pennsylvania Bureau of Police for the years 1990 through 2001. Data on crime offense reports were collected from the Rochester, New York Police Department from January 1991 through December 2001. The Rochester CAD drug calls and shots fired calls were collected from January 1993 through May 2001. A total of 1,643,828 records (769,293 crime offense and 874,535 CAD) were collected from Pittsburgh, while 538,893 records (530,050 crime offense and 8,843 CAD) were collected from Rochester. ArcView 3.3 and GDT Dynamap 2000 Street centerline maps were used to address match the data, with some of the Pittsburgh data being cleaned to fix obvious errors and increase address match percentages. A SAS program was used to eliminate duplicate CAD calls based on time and location of the calls. For the 1990 through 1999 Pittsburgh crime offense data, the address match rate was 91 percent. The match rate for the 2000 through 2001 Pittsburgh crime offense data was 72 percent. The Pittsburgh CAD data address match rate for 1990 through 1999 was 85 percent, while for 2000 through 2001 the match rate was 100 percent because the new CAD system supplied incident coordinates. The address match rates for the Rochester crime offenses data was 96 percent, and 95 percent for the CAD data. Spatial overlay in ArcView was used to add geographic area identifiers for each data point: precinct, car beat, car beat plus, and 1990 Census tract. The crimes included for both Pittsburgh and Rochester were aggravated assault, arson, burglary, criminal mischief, misconduct, family violence, gambling, larceny, liquor law violations, motor vehicle theft, murder/manslaughter, prostitution, public drunkenness, rape, robbery, simple assaults, trespassing, vandalism, weapons, CAD drugs, and CAD shots fired.

  5. Community Access to Information Dashboard (CAID) Current State Police

    • data.pa.gov
    csv, xlsx, xml
    Updated Sep 20, 2021
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    Pennsylvania State Police (2021). Community Access to Information Dashboard (CAID) Current State Police [Dataset]. https://data.pa.gov/w/mnei-j72p/33ch-zxdi?cur=ruNU1otFWKM
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Sep 20, 2021
    Dataset authored and provided by
    Pennsylvania State Policehttp://www.psp.pa.gov/
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description


    The dashboard displays aggregated State Police incident data. It contains no personally identifiable information. Users can refine the data with custom date ranges, locations, and categories.
    The CAID currently contains crash and enforcement data for both commercial and non-commercial vehicles, including Incident maps. Data regarding various crimes (including violent crimes where a firearm was involved in the commission) is now on the dashboard, with mapping for counties and municipalities. A map of PSP's coverage area throughout the commonwealth is also available.

    PSP is interested in your feedback. Use the Contact Us button located at the top of the dashboard to:
    • Submit suggestions for dashboard enhancements
    • Submit ideas on how we can provide better service and improve the quality of life in your neighborhood (such as sobriety checkpoints, radar details, community presentations, etc.)


    Feedback is reviewed by the CAID Development Team and the Office of Community Engagement. At all times, PSP welcomes your comments on how we are meeting our Core Values of Honor, Service, Integrity, Respect, Trust, Courage, and Duty.

  6. Digital Surficial Geologic-GIS Map of Delaware Water Gap National Recreation...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Sep 14, 2025
    + more versions
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    National Park Service (2025). Digital Surficial Geologic-GIS Map of Delaware Water Gap National Recreation Area and Vicinity, New Jersey, Pennsylvania and New York (NPS, GRD, GRI, DEWA, DEWA_surficial digital map) adapted from NJGS maps by Pallis and Marzulli, Witte and Epstein, Witte, Pristas, PaGS maps by Epstein, Sevon, Berg, Schultz and Crowl, Bucek, Braun, a NYSM map by Cadwell, Connally, Dineen, Fleisher, Fuller, Sirkin, and Wiles and a USGS NHD by USGS [Dataset]. https://catalog.data.gov/dataset/digital-surficial-geologic-gis-map-of-delaware-water-gap-national-recreation-area-and-vici
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    Dataset updated
    Sep 14, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Delaware Water Gap, Pennsylvania
    Description

    The Digital Surficial Geologic-GIS Map of Delaware Water Gap National Recreation Area and Vicinity, New Jersey, Pennsylvania and New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (dewa_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (dewa_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (dewa_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (dewa_surficial_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (dewa_surficial_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (dewa_surficial_geology_metadata_faq.pdf). Please read the dewa_surficial_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: New Jersey Geological Survey, Pennsylvania Geological Survey, New York State Museum and U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (dewa_surficial_geology_metadata.txt or dewa_surficial_geology_metadata_faq.pdf). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  7. a

    Allegheny County Municipal Boundaries

    • openac-alcogis.opendata.arcgis.com
    • data.wprdc.org
    • +4more
    Updated Apr 18, 2016
    + more versions
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    County of Allegheny, PA (2016). Allegheny County Municipal Boundaries [Dataset]. https://openac-alcogis.opendata.arcgis.com/datasets/AlCoGIS::allegheny-county-municipal-boundaries/about
    Explore at:
    Dataset updated
    Apr 18, 2016
    Dataset authored and provided by
    County of Allegheny, PA
    Area covered
    Description

    This dataset demarcates the municipal boundaries in Allegheny County. Data was created to portray the boundaries of the 130 Municipalities in Allegheny County the attribute table includes additional descriptive information including Councils of Government (COG) affiliation (regional governing and coordinating bodies comprised of several bordering municipalities), School District, Congressional District, FIPS and County Municipal Code and County Council District.

    If viewing this description on the Western Pennsylvania Regional Data Center’s open data portal (https://www.wprdc.org), this dataset is harvested on a weekly basis from Allegheny County’s GIS data portal (https://openac.alcogis.opendata.arcgis.com/). The full metadata record for this dataset can also be found on Allegheny County’s GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the “Explore” button (and choosing the “Go to resource” option) to the right of the “ArcGIS Open Dataset” text below.

    Category: Civic Vitality and Governance

    Organization: Allegheny County

    Department: Geographic Information Systems Group; Department of Information Technology

    Temporal Coverage: current

    Data Notes:

    Coordinate System: Pennsylvania State Plane South Zone 3702; U.S. Survey Foot

    Development Notes: none

    Other: none

    Related Document(s): Data Dictionary (none)

    Frequency - Data Change: As needed

    Frequency - Publishing: As needed

    Data Steward Name: Eli Thomas

    Data Steward Email: gishelp@alleghenycounty.us

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    Learn how you can add new datasets to our index.

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City of Pittsburgh (2025). Neighborhoods [Dataset]. https://data.wprdc.org/dataset/neighborhoods2

Neighborhoods

Explore at:
csv, html, kml(1078560), zip(329463), geojson(1200006)Available download formats
Dataset updated
Sep 17, 2025
Dataset authored and provided by
City of Pittsburgh
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Pittsburgh Neighborhoods

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