This dataset contains the boundaries of New Jersey Smart Growth Areas. This metadata mainly describes the elements derived from elements of the NJ State Development and Redevelopment Plan mapping, along with mapping from the NJ Pinelands Commission, and the Meadowlands Commission. See the metadata for the Pinelands Management Areas or the Meadowlands for specific information concerning their geographic areas.

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated or updated as part of the the 2023 BAS or the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

The Home Owners' Loan Corporation (HOLC) was created in the New Deal Era and trained many home appraisers in the 1930s. The HOLC created a neighborhood ranking system infamously known today as redlining. Local real estate developers and appraisers in over 200 cities assigned grades to residential neighborhoods. These maps and neighborhood ratings set the rules for decades of real estate practices. The grades ranged from A to D. A was traditionally colored in green, B was traditionally colored in blue, C was traditionally colored in yellow, and D was traditionally colored in red. A (Best): Always upper- or upper-middle-class White neighborhoods that HOLC defined as posing minimal risk for banks and other mortgage lenders, as they were "ethnically homogeneous" and had room to be further developed.B (Still Desirable): Generally nearly or completely White, U.S. -born neighborhoods that HOLC defined as "still desirable" and sound investments for mortgage lenders.C (Declining): Areas where the residents were often working-class and/or first or second generation immigrants from Europe. These areas often lacked utilities and were characterized by older building stock.D (Hazardous): Areas here often received this grade because they were "infiltrated" with "undesirable populations" such as Jewish, Asian, Mexican, and Black families. These areas were more likely to be close to industrial areas and to have older housing.Banks received federal backing to lend money for mortgages based on these grades. Many banks simply refused to lend to areas with the lowest grade, making it impossible for people in many areas to become homeowners. While this type of neighborhood classification is no longer legal thanks to the Fair Housing Act of 1968 (which was passed in large part due to the activism and work of the NAACP and other groups), the effects of disinvestment due to redlining are still observable today. For example, the health and wealth of neighborhoods in Chicago today can be traced back to redlining (Chicago Tribune). In addition to formerly redlined neighborhoods having fewer resources such as quality schools, access to fresh foods, and health care facilities, new research from the Science Museum of Virginia finds a link between urban heat islands and redlining (Hoffman, et al., 2020). This layer comes out of that work, specifically from University of Richmond's Digital Scholarship Lab. More information on sources and digitization process can be found on the Data and Download and About pages. NOTE: This map has been updated as of 1/16/24 to use a newer version of the data layer which contains more cities than it previously did. As mentioned above, over 200 cities were redlined and therefore this is not a complete dataset of every city that experienced redlining by the HOLC in the 1930s. Map opens in Sacramento, CA. Use bookmarks or the search bar to get to other cities.Cities included in this mapAlabama: Birmingham, Mobile, MontgomeryArizona: PhoenixArkansas: Arkadelphia, Batesville, Camden, Conway, El Dorado, Fort Smith, Little Rock, Russellville, TexarkanaCalifornia: Fresno, Los Angeles, Oakland, Sacramento, San Diego, San Francisco, San Jose, StocktonColorado: Boulder, Colorado Springs, Denver, Fort Collins, Fort Morgan, Grand Junction, Greeley, Longmont, PuebloConnecticut: Bridgeport and Fairfield; Hartford; New Britain; New Haven; Stamford, Darien, and New Canaan; WaterburyFlorida: Crestview, Daytona Beach, DeFuniak Springs, DeLand, Jacksonville, Miami, New Smyrna, Orlando, Pensacola, St. Petersburg, TampaGeorgia: Atlanta, Augusta, Columbus, Macon, SavannahIowa: Boone, Cedar Rapids, Council Bluffs, Davenport, Des Moines, Dubuque, Sioux City, WaterlooIllinois: Aurora, Chicago, Decatur, East St. Louis, Joliet, Peoria, Rockford, SpringfieldIndiana: Evansville, Fort Wayne, Indianapolis, Lake County Gary, Muncie, South Bend, Terre HauteKansas: Atchison, Greater Kansas City, Junction City, Topeka, WichitaKentucky: Covington, Lexington, LouisvilleLouisiana: New Orleans, ShreveportMaine: Augusta, Boothbay, Portland, Sanford, WatervilleMaryland: BaltimoreMassachusetts: Arlington, Belmont, Boston, Braintree, Brockton, Brookline, Cambridge, Chelsea, Dedham, Everett, Fall River, Fitchburg, Haverhill, Holyoke Chicopee, Lawrence, Lexington, Lowell, Lynn, Malden, Medford, Melrose, Milton, Needham, New Bedford, Newton, Pittsfield, Quincy, Revere, Salem, Saugus, Somerville, Springfield, Waltham, Watertown, Winchester, Winthrop, WorcesterMichigan: Battle Creek, Bay City, Detroit, Flint, Grand Rapids, Jackson, Kalamazoo, Lansing, Muskegon, Pontiac, Saginaw, ToledoMinnesota: Austin, Duluth, Mankato, Minneapolis, Rochester, Staples, St. Cloud, St. PaulMississippi: JacksonMissouri: Cape Girardeau, Carthage, Greater Kansas City, Joplin, Springfield, St. Joseph, St. LouisNorth Carolina: Asheville, Charlotte, Durham, Elizabeth City, Fayetteville, Goldsboro, Greensboro, Hendersonville, High Point, New Bern, Rocky Mount, Statesville, Winston-SalemNorth Dakota: Fargo, Grand Forks, Minot, WillistonNebraska: Lincoln, OmahaNew Hampshire: ManchesterNew Jersey: Atlantic City, Bergen County, Camden, Essex County, Monmouth, Passaic County, Perth Amboy, Trenton, Union CountyNew York: Albany, Binghamton/Johnson City, Bronx, Brooklyn, Buffalo, Elmira, Jamestown, Lower Westchester County, Manhattan, Niagara Falls, Poughkeepsie, Queens, Rochester, Schenectady, Staten Island, Syracuse, Troy, UticaOhio: Akron, Canton, Cleveland, Columbus, Dayton, Hamilton, Lima, Lorain, Portsmouth, Springfield, Toledo, Warren, YoungstownOklahoma: Ada, Alva, Enid, Miami Ottawa County, Muskogee, Norman, Oklahoma City, South McAlester, TulsaOregon: PortlandPennsylvania: Allentown, Altoona, Bethlehem, Chester, Erie, Harrisburg, Johnstown, Lancaster, McKeesport, New Castle, Philadelphia, Pittsburgh, Wilkes-Barre, YorkRhode Island: Pawtucket & Central Falls, Providence, WoonsocketSouth Carolina: Aiken, Charleston, Columbia, Greater Anderson, Greater Greensville, Orangeburg, Rock Hill, Spartanburg, SumterSouth Dakota: Aberdeen, Huron, Milbank, Mitchell, Rapid City, Sioux Falls, Vermillion, WatertownTennessee: Chattanooga, Elizabethton, Erwin, Greenville, Johnson City, Knoxville, Memphis, NashvilleTexas: Amarillo, Austin, Beaumont, Dallas, El Paso, Forth Worth, Galveston, Houston, Port Arthur, San Antonio, Waco, Wichita FallsUtah: Ogden, Salt Lake CityVirginia: Bristol, Danville, Harrisonburg, Lynchburg, Newport News, Norfolk, Petersburg, Phoebus, Richmond, Roanoke, StauntonVermont: Bennington, Brattleboro, Burlington, Montpelier, Newport City, Poultney, Rutland, Springfield, St. Albans, St. Johnsbury, WindsorWashington: Seattle, Spokane, TacomaWisconsin: Kenosha, Madison, Milwaukee County, Oshkosh, RacineWest Virginia: Charleston, Huntington, WheelingAn example of a map produced by the HOLC of Philadelphia:

The 2022 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

There is a newer and more authoritative version of this layer here! It is owned by the University of Richmond's Digital Scholarship Lab and contains data on many more cities.The Home Owners' Loan Corporation (HOLC) was created in the New Deal Era and trained many home appraisers in the 1930s. The HOLC created a neighborhood ranking system infamously known today as redlining. Local real estate developers and appraisers in over 200 cities assigned grades to residential neighborhoods. These maps and neighborhood ratings set the rules for decades of real estate practices. The grades ranged from A to D. A was traditionally colored in green, B was traditionally colored in blue, C was traditionally colored in yellow, and D was traditionally colored in red. A (Best): Always upper- or upper-middle-class White neighborhoods that HOLC defined as posing minimal risk for banks and other mortgage lenders, as they were "ethnically homogeneous" and had room to be further developed.B (Still Desirable): Generally nearly or completely White, U.S. -born neighborhoods that HOLC defined as "still desirable" and sound investments for mortgage lenders.C (Declining): Areas where the residents were often working-class and/or first or second generation immigrants from Europe. These areas often lacked utilities and were characterized by older building stock.D (Hazardous): Areas here often received this grade because they were "infiltrated" with "undesirable populations" such as Jewish, Asian, Mexican, and Black families. These areas were more likely to be close to industrial areas and to have older housing.Banks received federal backing to lend money for mortgages based on these grades. Many banks simply refused to lend to areas with the lowest grade, making it impossible for people in many areas to become homeowners. While this type of neighborhood classification is no longer legal thanks to the Fair Housing Act of 1968 (which was passed in large part due to the activism and work of the NAACP and other groups), the effects of disinvestment due to redlining are still observable today. For example, the health and wealth of neighborhoods in Chicago today can be traced back to redlining (Chicago Tribune). In addition to formerly redlined neighborhoods having fewer resources such as quality schools, access to fresh foods, and health care facilities, new research from the Science Museum of Virginia finds a link between urban heat islands and redlining (Hoffman, et al., 2020). This layer comes out of that work, specifically from University of Richmond's Digital Scholarship Lab. More information on sources and digitization process can be found on the Data and Download and About pages. This layer includes 7,148 neighborhoods spanning 143 cities across the continental United States. NOTE: As mentioned above, over 200 cities were redlined and therefore this is not a complete dataset of every city that experienced redlining by the HOLC in the 1930s. More cities are available in this feature layer from University of Richmond.Cities included in this layerAlabama: Birmingham, Mobile, MontgomeryCalifornia: Fresno, Los Angeles, Sacramento, San Diego, San Francisco, San Jose, StocktonColorado: DenverConnecticut: East Hartford, New Britain, New Haven, StamfordFlorida: Jacksonville, Miami, St. Petersburg, TampaGeorgia: Atlanta, Augusta, Chattanooga, Columbus, MaconIllinois: Aurora, Chicago, Decatur, Joliet, GaryIndiana: Evansville, Fort Wayne, Indianapolis, Gary, Muncie, South Bend, Terre HauteKansas: Greater Kansas City, WichitaKentucky: Lexington, LouisvilleLouisiana: New OrleansMassachusetts: Arlington, Belmont, Boston, Braintree, Brockton, Brookline, Cambridge, Chelsea, Dedham, Everett, Haverhill, Holyoke Chicopee, Lexington, Malden, Medford, Melrose, Milton, Needham, Newton, Quincy, Revere, Saugus, Somerville, Waltham, Watertown, Winchester, WinthropMaryland: BaltimoreMichigan: Battle Creek, Bay City, Detroit, Flint, Grand Rapids, Kalamazoo, Muskegon, Pontiac, Saginaw, ToledoMinnesota: Duluth, MinneapolisMissouri: Greater Kansas City, Springfield, St. Joseph, St. LouisNorth Carolina: Asheville, Charlotte, Durham, Greensboro, Winston SalemNew Hampshire: ManchesterNew Jersey: Atlantic City, Bergen Co., Camden, Essex County, Hudson County, TrentonNew York: Bronx, Brooklyn, Buffalo, Elmira, Binghamton/Johnson City, Lower Westchester Co., Manhattan, Niagara Falls, Poughkeepsie, Queens, Rochester, Staten Island, Syracuse, UticaOhio: Akron, Canton, Cleveland, Columbus, Dayton, Hamilton, Lima, Lorrain, Portsmouth, Springfield, Toledo, Warren, YoungstownOregon: PortlandPennsylvania: Altoona, Erie, Johnstown, New Castle, Philadelphia, PittsburghSouth Carolina: AugustaTennessee: Chattanooga, KnoxvilleTexas: DallasVirginia: Lynchburg, Norfolk, Richmond, RoanokeWashington: Seattle, Spokane, TacomaWisconsin: Kenosha, Milwaukee, Oshkosh, RacineWest Virginia: Charleston, WheelingAn example of a map produced by the HOLC of Philadelphia:

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.