Allows users to look up City of Pittsburgh Neighborhoods

Pittsburgh Neighborhoods

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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.

This polygon shapefile displays the 91 neighborhoods in the City of Pittsburgh.

This data shows the attendance boundaries used to assign students to feeder pattern schools based on their place of residence. These boundaries were adopted for the 2012-13 school year by the Pittsburgh Public Schools. The boundaries were drawn to align with major roads, neighborhood boundaries, and natural features. Efforts were also made to enable all students within an elementary school to move to the same middle school, and allow all students in a middle school to transition to the same high school.

This EnviroAtlas dataset shows the boundary of the Pittsburgh, PA Atlas Area. It represents the outside edge of all the block groups included in the EnviroAtlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Most people don't know the history of their street, neighborhood, or even city. The Pittsburgh Mapping and Historical Site Viewer provides a window into the past, allowing anyone to see how the city took shape over time. It shows how the city of 22,433 people in 1835 changes over time: how neighborhoods grow and expand, while others were planned but never built. Street names change over time, empty lots become buildings, and schools and churches open and close. The maps were made by cutting and georeferencing hand-drawn paper maps made over 100 years ago. Using historic maps, some more than 175 years old, this interactive map highlights sites in the National Registry of Historic Places among others. By browsing through the years at a location, you'll find a cemetery that became a school, the arrival of rail yards, and other indicators of how the city has evolved around changes in transportation, industry, and population. This map service includes a mosaic of several volumes of plat maps that were originally bound atlases. The mosaic was created using ArcGIS software from the scanned JPEG images, varying from 300-600 dpi. These images were obtained from the Historic Pittsburgh website (http://digital.library.pitt.edu/maps/hopkins.html) The images were georeferenced to WGS84 Web Mercator and the borders were clipped to create a contiguous map.This product is to be used for reference purposes only. The original historical paper maps were sometimes damaged or distorted to varying degrees due to age and use. There are spatial inaccuracies and some places where the footprints do not lineup perfectly or in some cases overlap.Read and see more about this project:KDKA News feedEsri BlogPittsburgh Post-Gazette articleUniversity of Pittsburgh