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The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.

Roadways (streets and highways) for the San Francisco Bay Region. Feature set was assembled using all roads county-based 2021 TIGER/Line shapefiles by the Metropolitan Transportation Commission.The All Roads shapefiles includes all features within the Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB) Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, stairways, and winter trails.The feature set contains multiple overlapping road segments where a segment is associated with more than one road feature. For example, if a road segment is associated with US Route 36 and State Highway 7 and 28th Street, the route will contain three spatially coincident segments, each with a different name. The roadway feature set contains the set of unique road segments for each county, along with other linear features.Primary roads are generally divided limited-access highways within the Federal interstate highway system or under state management. Interchanges and ramps distinguish these roads, and some are toll highways.Secondary roads are main arteries, usually in the U.S. highway, state highway, or county highway system. These roads have one or more lanes of traffic in each direction, may or may not be divided, and usually have at-grade intersections with many other roads and driveways. They often have both a local name and a route number.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, stairways, and winter trails.

The California Association Local Agency Formation Commissions defines a sphere of influence (SOI) as "a planning boundary outside of an agency’s legal boundary (such as the city limit line) that designates the agency’s probable future boundary and service area." This feature set represents the SOIs of the incorporated jurisdictions for the San Francisco Bay Region.The Metropolitan Transportation Commission (MTC) updated the feature set in late 2019 as part of the jurisdiction review process for the BASIS data gathering project. Changes were made to the growth boundaries of the following jurisdictions based on BASIS feedback and associated work: Antioch, Brentwood, Campbell, Daly City, Dublin, Fremont, Hayward, Los Gatos, Monte Sereno, Newark, Oakland, Oakley, Pacifica, Petaluma, Pittsburg, Pleasanton, San Bruno, San Francisco (added to reflect other jurisdictions whose SOI is the same as their jurisdiction boundary), San Jose, San Leandro, Santa Clara, Saratoga, and Sunnyvale.Notes: With the exception of San Mateo and Solano Counties, counties included jurisdiction (city/town) areas as part of their SOI boundary data. San Mateo County and Solano County only provided polygons representing the SOI areas outside the jurisdiction areas. To create a consistent, regional feature set, the Metropolitan Transportation Commission (MTC) added the jurisdiction areas to the original, SOI-only features and dissolved the features by name.Because of differences in base data used by the counties and the MTC, edits were made to the San Mateo County and Solano County SOI features that should have been adjacent to their jurisdiction boundary so the dissolve function would create a minimum number of features.Original sphere of influence boundary acquisitions:Alameda County - CityLimits_SOI.shp received as e-mail attachment from Alameda County Community Development Agency on 30 August 2019Contra Costa County - BND_LAFCO_Cities_SOI.zip downloaded from https://gis.cccounty.us/Downloads/Planning/ on 15 August 2019Marin County - 'Sphere of Influence - City' feature service data downloaded from Marin GeoHub on 15 August 2019Napa County - city_soi.zip downloaded from their GIS Data Catalog on 15 August 2019City and County of San Francisco - does not have a sphere of influenceSan Mateo County - 'Sphere of Influence' feature service data downloaded from San Mateo County GIS open data on 15 August 2019Santa Clara County - 'City Spheres of Influence' feature service data downloaded from Santa Clara County Planning Office GIS Data on 15 August 2019Solano County - SphereOfInfluence feature service data downloaded from Solano GeoHub on 15 August 2019Sonoma County - 'SoCo PRMD GIS Spheres Influence.zip' downloaded from County of Sonoma on 15 August 2019

A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the southern portion of San Francisco Bay, was constructed from bathymetric surveys collected from 2005 to 2020. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ranging from 18- to just over 100-meters wide. These swaths were separated by data gaps ranging from 10- to just over 300-meters wide. The no-data areas required interpolation to create a continuous surface. The OPC surveys were combined with additional data sets collected by the United States Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), NOAA National Ocean Service (NOS), and the United States Army Corps of Engineers (USACE) to create a cont ...

These footprint extents are collapsed from an earlier 3D building model provided by Pictometry of 2010, and have been refined from a version of building masses publicly available on the open data portal for over two years.The building masses were manually split with reference to parcel lines, but using vertices from the building mass wherever possible.These split footprints correspond closely to individual structures even where there are common walls; the goal of the splitting process was to divide the building mass wherever there was likely to be a firewall. An arbitrary identifier was assigned based on a descending sort of building area for 177,023 footprints. The centroid of each footprint was used to join a property identifier from a draft of the San Francisco Enterprise GIS Program's cartographic base, which provides continuous coverage with distinct right-of-way areas as well as selected nearby parcels from adjacent counties. See accompanying document SF_BldgFoot_2017-05_description.pdf for more on methodology and motivation

This GIS layer (zipped shapefile format) includes all open space boundaries. Boundaries that have been vetted by Planning for the purposes of conducting shadow impact analyses are attributed with a 'Y' in the [vetted] field. To confirm boundaries for open spaces that are not vetted in this layer, please contact the assigned environmental coordinator or current planner.

In 2018, the Golden Gate National Parks Conservancy (Parks Conservancy) (https://parksconservancy.org), non-profit support partner to the National Park Service (NPS) Golden Gate National Recreation Area (GGNRA), initiated a fine scale vegetation mapping project in Marin County. The GGNRA includes lands in San Francisco and San Mateo counties, and NPS expressed interest in pursuing fine scale vegetation mapping for those lands as well. The Parks Conservancy facilitated multiple meetings with potential project stakeholders and was able to build a consortium of funders to map all of San Mateo County (and NPS lands in San Francisco). The consortium included the San Francisco Public Utilities Commission (SFPUC), Midpeninsula Regional Open Space District (MROSD), Peninsula Open Space Trust (POST), San Mateo City/County Association of Governments, and various County of San Mateo departments including Parks, Agricultural Weights and Measures, Public Works/Flood Control District, Office of Sustainability, and Planning and Building. Over a 3-year period, the project, collectively referred to as the “San Mateo Fine Scale Veg Map”, has produced numerous environmental GIS products including 1-foot contours, orthophotography, and other land cover maps. A 106-class fine-scale vegetation map was completed in April 2022 that details vegetation communities and agricultural land cover types, including forests, grasslands, riparian vegetation, wetlands, and croplands. The environmental data products from the San Mateo Fine Scale Veg Map are foundational and can be used by organizations and government departments for a wide range of purposes, including planning, conservation, and to track changes over time to San Mateo County''s habitats and natural resources.Development of the San Mateo fine-scale vegetation map was managed by the Golden Gate National Parks Conservancy and staffed by personnel from Tukman Geospatial (https://tukmangeospatial.com/), Aerial Information Systems (AIS; http

A) This data describes the Special Flood Hazard Areas (SFHA's) pursuant to the Federal Emergency Management Agency's (FEMA's) Flood Insurance Rate Map (FIRM) for the City and County of San Francisco.

B) These map products were created by FEMA and you can find more information on their creation on the following page: https://www.fema.gov/flood-maps/products-tools/products

C) These maps are updated periodically in light of new information if flooding conditions change for a jurisdiction. This occurs on an as needed basis and is coordinated through the

D) In order to use this dataset it is important to know what each zone designation means. You can find these designations below -- Zone AE, AO, and VE (AREAS WITH HIGH FLOOD RISK (SPECIAL FLOOD HAZARD AREAS; REGULATIONS APPLY): Properties within SFHAs are subject to flooding during the 1-percent-chance flood, a flood with a 1 percent chance of occurrence in any given year (also referred to as the Base Flood or 100-year flood).

Zone D (AREA OF UNDETERMINED FLOOD RISK): In San Francisco, Zone D is an area of possible, but undefined, flood risk for waterfront piers operated by the Port of San Francisco.

Zone X Shaded or Unshaded (AREA OF LOW OR MINIMAL FLOOD RISK): "Shaded" Zone X represents areas of moderate or low flood risk – these areas are subject to inundation during a flood having a 0.2-percent-annual-chance of occurrence, or during the 1-percent-annual-chance flood with depth less than 1 foot. "Unshaded" Zone X represents areas of minimal flood risk or areas that FEMA did not study or map.

E) For regulatory implications of map, see: https://onesanfrancisco.org/San-Francisco-Floodplain-Management-Program

For more detailed information on specific properties impacted by FIRM Map, see: https://sfplanninggis.org/PIM/

Analysis of ‘San Francisco County Land Use Survey 2014’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1683121c-b974-4a1d-9b23-988a05b77afa on 26 January 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

This shapefile contains tax rate area (TRA) boundaries in San Francisco County for the specified assessment roll year. Boundary alignment is based on the 2014 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

A. SUMMARY This data represents the boundaries of City-owned lands maintained in the City's Facility System of Record (FSR). Note: Not all lands are within the City and County proper. The City owns properties outside of its boundaries, including lands managed by SF Recreation and Parks, SF Public Utilities Commission, and other agencies. Certain lands are managed by following agencies which are not directly part of the City and County of San Francisco, but are included here for reference: San Francisco Housing Authority (SFHA), San Francisco Office of Community Investment and Infrastructure (OCII), and City College of San Francisco. B. HOW THE DATASET IS CREATED The Enterprise GIS program in the Department of Technology is the technical custodian of the FSR. This team creates and maintains this dataset in conjunction with the Real Estate Division and the Capital Planning Program of the City Administrator’s Office, who act as the primary business data stewards for this data. C. UPDATE PROCESS There are a handful of events that may trigger changes to this dataset: 1. The sale of a property 2. The leasing of a property 3. The purchase of a property 4. The change in jurisdiction of a property (e.g. from MTA to DPW) 5. The removal or improvement of the property Each of these changes triggers a workflow that updates the FSR. The Real Estate Division and Capital Planning make updates on an ongoing basis. The full dataset is reviewed quarterly to ensure nothing is missing or needs to be corrected. Updates to the data, once approved, are immediately reflected in the internal system and are updated here in the open dataset on a monthly basis. D. HOW TO USE THIS DATASET See here for an interactive map of all the City lands in this dataset. To track the facilities on City lands, join this dataset to the City Facilities dataset using the land_id field. If you see an error in the data, you can submit a change request with the relevant information to dtis.helpdesk@sfgov.org. Please be as specific about the error as you can (including relevant land_id(s)). E. RELATED DATASETS City Facilities

This map shows the percentage of housing that is vacant in the U.S., by state, county, tract and block group. The data shown is from the U.S. Census Bureau's SF1 and TIGER data sets for 2010. The map switches from state, to county, to tract, to block group data as the map zooms in.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This shapefile contains tax rate area (TRA) boundaries in San Francisco County for the specified assessment roll year. Boundary alignment is based on the 2014 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

This dataset includes one file for each of the 51 counties that were collected, as well as a CA_Merged file with the parcels merged into a single file.Note – this data does not include attributes beyond the parcel ID number (PARNO) – that will be provided when available, most likely by the state of California.DownloadA 1.6 GB zipped file geodatabase is available for download - click here.DescriptionA geodatabase with parcel boundaries for 51 (out of 58) counties in the State of California. The original target was to collect data for the close of the 2013 fiscal year. As the collection progressed, it became clear that holding to that time standard was not practical. Out of expediency, the date requirement was relaxed, and the currently available dataset was collected for a majority of the counties. Most of these were distributed with minimal metadata.The table “ParcelInfo” includes the data that the data came into our possession, and our best estimate of the last time the parcel dataset was updated by the original source. Data sets listed as “Downloaded from” were downloaded from a publicly accessible web or FTP site from the county. Other data sets were provided directly to us by the county, though many of them may also be available for direct download. Â These data have been reprojected to California Albers NAD84, but have not been checked for topology, or aligned to county boundaries in any way. Tulare County’s dataset arrived with an undefined projection and was identified as being California State Plane NAD83 (US Feet) and was assigned by ICE as that projection prior to reprojection. Kings County’s dataset was delivered as individual shapefiles for each of the 50 assessor’s books maintained at the county. These were merged to a single feature class prior to importing to the database.The attribute tables were standardized and truncated to include only a PARNO (APN). The format of these fields has been left identical to the original dataset. The Data Interoperablity Extension ETL tool used in this process is included in the zip file. Where provided by the original data sources, metadata for the original data has been maintained. Please note that the attribute table structure changes were made at ICE, UC Davis, not at the original data sources.Parcel Source InformationCountyDateCollecDateCurrenNotesAlameda4/8/20142/13/2014Download from Alamenda CountyAlpine4/22/20141/26/2012Alpine County PlanningAmador5/21/20145/14/2014Amador County Transportation CommissionButte2/24/20141/6/2014Butte County Association of GovernmentsCalaveras5/13/2014Download from Calaveras County, exact date unknown, labelled 2013Contra Costa4/4/20144/4/2014Contra Costa Assessor’s OfficeDel Norte5/13/20145/8/2014Download from Del Norte CountyEl Dorado4/4/20144/3/2014El Dorado County AssessorFresno4/4/20144/4/2014Fresno County AssessorGlenn4/4/201410/13/2013Glenn County Public WorksHumboldt6/3/20144/25/2014Humbodt County AssessorImperial8/4/20147/18/2014Imperial County AssessorKern3/26/20143/16/2014Kern County AssessorKings4/21/20144/14/2014Kings CountyLake7/15/20147/19/2013Lake CountyLassen7/24/20147/24/2014Lassen CountyLos Angeles10/22/201410/9/2014Los Angeles CountyMadera7/28/2014Madera County, Date Current unclear likely 7/2014Marin5/13/20145/1/2014Marin County AssessorMendocino4/21/20143/27/2014Mendocino CountyMerced7/15/20141/16/2014Merced CountyMono4/7/20144/7/2014Mono CountyMonterey5/13/201410/31/2013Download from Monterey CountyNapa4/22/20144/22/2014Napa CountyNevada10/29/201410/26/2014Download from Nevada CountyOrange3/18/20143/18/2014Download from Orange CountyPlacer7/2/20147/2/2014Placer CountyRiverside3/17/20141/6/2014Download from Riverside CountySacramento4/2/20143/12/2014Sacramento CountySan Benito5/12/20144/30/2014San Benito CountySan Bernardino2/12/20142/12/2014Download from San Bernardino CountySan Diego4/18/20144/18/2014San Diego CountySan Francisco5/23/20145/23/2014Download from San Francisco CountySan Joaquin10/13/20147/1/2013San Joaquin County Fiscal year close dataSan Mateo2/12/20142/12/2014San Mateo CountySanta Barbara4/22/20149/17/2013Santa Barbara CountySanta Clara9/5/20143/24/2014Santa Clara County, Required a PRA requestSanta Cruz2/13/201411/13/2014Download from Santa Cruz CountyShasta4/23/20141/6/2014Download from Shasta CountySierra7/15/20141/20/2014Sierra CountySolano4/24/2014Download from Solano Couty, Boundaries appear to be from 2013Sonoma5/19/20144/3/2014Download from Sonoma CountyStanislaus4/23/20141/22/2014Download from Stanislaus CountySutter11/5/201410/14/2014Download from Sutter CountyTehama1/16/201512/9/2014Tehama CountyTrinity12/8/20141/20/2010Download from Trinity County, Note age of data 2010Tulare7/1/20146/24/2014Tulare CountyTuolumne5/13/201410/9/2013Download from Tuolumne CountyVentura11/4/20146/18/2014Download from Ventura CountyYolo11/4/20149/10/2014Download from Yolo CountyYuba11/12/201412/17/2013Download from Yuba County

Zoning Districts from 2008. Part of the San Francisco Planning Code. Data is a zipped GIS shapefile.

This layer is sourced from gis.acgov.org.