This is a graphical polygon dataset depicting the polygon boundaries of the ten City of San Antonio City Council Districts. 2012 Redistricting Plan precleared by D.O.J. under Section 5 of the Voting Rights Act 11/27/2012. Updated per Limited Purpose Annexation Ordinance 2014-11-06-0861, of 36.266 Acres. Ordinance 2014-01-09-0001 of Areas 1 - 4.Updated per Ordinance 2015-01-15-0020, Boundary Adjustment of approx. 1,906.12 Acres (Government Cayon)

Historical districts contain multiple properties and/or objects that share historical significance. The City’s Historical Resources Board can establish a district if the contributing resources meet one of six criteria. For more information, read the nomination guidelines.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

City Council adopted new district boundaries that are effective for the May 2023 municipal election for City Council. You can learn more about these district changes at the City’s redistricting website: https://www.sabexarcountmein.org/.

California State Assembly boundaries adopted for the June 2012 primary elections. Districts located within the County of San Diego were extracted and reprojected into SanGIS standard projection.Every 10 years, after the federal census, California must redraw the boundaries of its Congressional, State Senate, State Assembly, and State Board of Equalization districts, to reflect the new population data. Now those lines are drawn by the Commission. California voters authorized the creation of the Commission when they passed the Voters First Act, which appeared as Proposition 11 on the November 2008 general election ballot. Under the Act, the Commission is charged with drawing the boundaries of California’s Congressional, Senate, Assembly and Board of Equalization electoral districts.The commission has14 members from varied ethnic backgrounds and geographic locations in the state and includes five Democrats, five Republicans, and four Decline to State.http://wedrawthelines.ca.gov/

Neighborhoods within the City of San Diego.

Fire Battalion districts have a chief that oversees 6 to 7 fire stations.

This is a geographic database of historical districts within the City of San Antonio

The SanGIS data set includes an extensive collection of GIS maps that are available to the public.

 Application Data Included:

 1. Public Safety: Crime Mapping & Analysis, Computer Aided Dispatch,
 Emergency Response Planning

 2. Planning & Development: Specific Plans, Vegetation Mapping, Zoning,
 Geologic Hazards, Codes Enforcement

 3. Facilities Management: Water and Waste Water Utilities, Street
 Lighting, Storm Drains, Pavement Management

 4. Subdivision Mapping: Basemap Maintenance, Parcel Mapping, Survey
 Control, Orthophotography

 5. Route Management: Water Meter Readers, Trash & Recycling Routes

 6. Decision Support & Analysis: Facility Siting, Airport Noise, Slope
 Analysis, Demographics, Economic Development

 SanGIS was created in July, 1997, as a Joint Powers Agreement (JPA)
 between the City and County of San Diego. After 13 years of working
 together on data and application development, the City and County
 decided to formalize their partnership in GIS by creating the SanGIS
 JPA. Finding that access to correct and current geographic data was
 considered more important than application development to County and
 City departments, SanGIS focuses on ensuring geographic data is
 maintained and accessible.

 SanGIS Mission:

 To maintain and promote the use of a regional geographic data
 warehouse for the San Diego area and to facilitate the development of
 shared geographic data and automated systems which use that data.

 SanGIS Goals:

 1. To ensure geographic data currency and integrity.

 2. To provide cost effective access to geographic data to member
 agencies, subscribers and the public.

 3. To generate revenue from the sale of geographic data products to
 reduce the cost of map maintenance to member agencies.

 Data Collection:

 SanGIS data was created or obtained from several sources. Some of our
 data is licensed; some data was created from tabular digital files;
 some data was digitized from paper maps; and other data was entered
 using coordinate geometry tools.

 Updating the Data:

 Responsibility for the maintenance of the over 200 geographic data
 layers is distributed to City and County departments based on several
 factors such as who has the source documents, who has the greatest
 need for the data, and who is held accountable for this data as part
 of their city-wide or county-wide duties. Most basemap maintenance is
 completed by SanGIS staff. SanGIS is also responsible for coordinating
 with other data maintainers to ensure currency and accuracy for all
 participants.

 Data Coverage:

 All of the SanGIS geographic data is within San Diego County
 only. Much of our data covers the entire County of San Diego but some
 is only for the City of San Diego.

 [Summary provided by SanGIS]

This is a geographic database of historical districts within the City of San Antonio

The San Diego Coast District, Department of Natural Resources, and California State Parks created a fine-scale vegetation map of portions of the Los Penasquitos Lagoon. San Diego Coast District, Department of Natural Resources, and California State Parks conducted field reconnaissance assistance for this project, as well as accuracy assessment (AA) field data collection. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area consists of approximately 1204.82 acres of San Diego county. Prior to performing field work, preliminary polygons were delineated on a 2013 true color aerial image with 6 inch pixel resolution. The majority of polygons were later surveyed in the field and redrawn as needed to accurately reflect the boundaries of each vegetation type. Field data was collected from mid 2013 to early 2015. The primary purpose of the project was to further CDFW’s goal of developing fine-scale digital vegetation maps as part of the California Biodiversity Initiative Roadmap of 2018. Mapped vegetation was classified according to the Vegetation Manual for Western San Diego County (AECOM 2011) codes. Holland (sensu Oberbauer 2008) classes were derived via the crosswalk recommended in the Vegetation Manual for Western San Diego County (AECOM 2011). CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). The vegetation map was produced applying heads-up digitizing techniques using LIDAR vegetation elevation data, false color infrared, and other aerial imagery. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 0.1 hectares. Mappers retained salt panne, mudflat, and water polygons that were below the MMU due to the importance of these habitats. In addition, polygons that were enclosed by these habitat types (such as islands of Salicornia pacifica surrounded by water) were allowed as exceptions to the MMU rule, as were polygons on the perimeter of the mapped area. Polygons initially mapped as salt panne, mudflat, or water that were later changed to a different category based on examination in the field were also allowed as exceptions to the MMU rule. Field reconnaissance and accuracy assessment enhanced map quality. The accuracy assessment was performed in the autumn of 2016. A total of 61 plots from 20 categories were evaluated. The final map accuracy was 56% using a traditional error matrix. There was a total of 42 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map, at the association levels, is 89% percent.

This layer comprises polygons of City Council Districts within the City of Poway. Council districts for all incorporated cities within the County of San Diego can be found on the SanGIS/SANDAG Regional Data Warehouse.

This is a polygon dataset depicting the polygon boundaries of the patrol districts for the San Antonio Police Department. Districts updated 12/30/2017

The California State Water Resources Control Board (State Water Board) and the nine Regional Water Quality Control Boards (Regional Water Boards), collectively known as the California Water Boards (Water Boards), are dedicated to a single vision: abundant clean water for human uses and environmental protection to sustain California’s future. Under the federal Clean Water Act (CWA) and the state’s pioneering Porter-Cologne Water Quality Control Act, the State and Regional Water Boards have regulatory responsibility for protecting the water quality of nearly 1.6 million acres of lakes, 1.3 million acres of bays and estuaries, 211,000 miles of rivers and streams, and about 1,100 miles of California coastline.The State Water Board is located in Sacramento. There are nine Regional Water Boards, the boundaries of which are generally based on watersheds, also known as hydrologic areas. The nine Regional Water Boards are referred to by specific names, which are: (1) North Coast, (2) San Francisco Bay, (3) Central Coast, (4) Los Angeles, (5) Central Valley, (6) Lahontan, (7) Colorado River Basin, (8) Santa Ana, and (9) San Diego. Due to their size, and/or geographic spread, the Central Valley Board has three offices and the Lahontan Board has two offices. In addition, the Drinking Water Program has fourteen District offices spread throughout the state.This map service shows the jurisdictional boundaries of the nine Regional Water Boards and the locations of their administrative offices. The official legal definitions of Regional Water Quality Control Board jurisdictions may be found in the Section 13200 of the California Water Code.For more information, please visit the California Water Boards website at https://www.waterboards.ca.gov.

This dataset represents a compilation of data from various government agencies throughout the City of New York. The underlying geography is derived from the Tax Lot Polygon feature class that is part of the Department of Finance's Digital Tax Map (DTM). The tax lots have been clipped to the shoreline, as defined by NYCMap planimetric features. The attribute information is from the Department of City Planning's PLUTO data. The attribute data pertains to tax lot and building characteristics and geographic, political and administrative information for each tax lot in New York City.The Tax Lot Polygon feature class and PLUTO are derived from different sources. As a result, some PLUTO records do not have a corresponding tax lot in the Tax Lot polygon feature class at the time of release. These records are included in a separate non-geographic PLUTO Only table. There are a number of reasons why there can be a tax lot in PLUTO that does not match the DTM; the most common reason is that the various source files are maintained by different departments and divisions with varying update cycles and criteria for adding and removing records. The attribute definitions for the PLUTO Only table are the same as those for MapPLUTO. DCP Mapping Lots includes some features that are not on the tax maps. They have been added by DCP for cartographic purposes. They include street center 'malls', traffic islands and some built streets through parks. These features have very few associated attributes.To report problems, please open a GitHub issue or email DCPOpendata@planning.nyc.gov.DATES OF INPUT DATASETS:Department of City Planning - E-Designations: 2/5/2021Department of City Planning - Zoning Map Index: 7/31/2019Department of City Planning - NYC City Owned and Leased Properties: 11/15/2020Department of City Planning - NYC GIS Zoning Features: 2/5/2021Department of City Planning - Polictical and Administrative Districts: 11/17/2020Department of City Planning - Geosupport version 20D: 11/17/2020Department of Finance - Digital Tax Map: 1/30/2021Department of Finance - Mass Appraisal System (CAMA): 2/10/2021Department of Finance - Property Tax System (PTS): 2/6/2021Landmarks Preservation Commission - Historic Districts: 2/4/2021Landmarks Preservation Commission - Individual Landmarks: 2/4/2021Department of Information Telecommunications & Technology - Building Footprints: 2/10/2021Department of Parks and Recreation - GreenThumb Garden Info: 1/4/2021

This is a graphical polygon dataset depicting the polygon boundaries of the Historic River Overlay Districts of San Antonio, Texas.

Neighborhood Conservation Districts

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 central core of SAPD's Community Policing activities is the SAFFE (San Antonio Fear Free Environment) Unit. First established in 1994-95 with 60 officers and supervisors, then enlarged in 1996 with an additional 40 officers, the SAFFE Unit consists of officers who focus on identifying, evaluating and resolving community crime problems with the cooperation and participation of community residents.SAFFE officers are assigned to specific areas or neighborhoods within the city, and work closely with both residents and the district patrol officers also assigned to those areas. SAFFE officers establish and maintain day-to-day interaction with residents and businesses within their assigned beats, in order to prevent crimes before they happen. SAFFE officers also act as liaisons with other city agencies, work closely with schools and youth programs, coordinate graffiti-removal activities, and serve as resources to residents who wish to take back their neighborhoods from crime and decay.SAFFE Website

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: