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A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.
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.
Geospatial data about City of San Francisco, California Schools. Export to CAD, GIS, PDF, CSV and access via API.
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.
MIT Licensehttps://opensource.org/licenses/MIT
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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
These data provide an accurate high-resolution shoreline compiled from imagery of Port of San Francisco, CA . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attr...
Geospatial data about City of San Francisco, California Zoning Map — Height Districts. Export to CAD, GIS, PDF, CSV and access via API.
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.
This eelgrass layer includes the maximum extent of eelgrass beds that have been surveyed in the San Francisco Bay shown in green. It was created by merging the Bay-wide eelgrass surveys conducted by Merkel & Associates, Inc. (Merkel) in 2003, 2009, 2014, and a Richardson Bay survey conducted by Merkel in 2019. Merkel has granted permission for public use of these data. These eelgrass surveys represent the best available data on comprehensive eelgrass extent throughout San Francisco Bay in 2021 and are developed using a combination of acoustic and aerial surveys and site-specific ground truthing. This layer may be used as a reference to determine potential direct and indirect impacts to eelgrass habitat from dredging projects. These data do not replace the need for site-specific eelgrass surveys.Data from the 2003, 2009, and 2014 eelgrass surveys and associated Merkel reports which include information on mapping methodology are available for download on the San Francisco Estuary Institute’s (SFEI) website. Methods for creating this layer are as follows:Downloaded the Merkel Baywide Eelgrass Surveys for 2003, 2009, and 2014 from SFEI and combined into a single layer. Obtained original Richardson Bay 2019 eelgrass survey data from Merkel. Loaded all layers into ArcGIS Pro © ESRI and re-projected all data to the NAD 1983 UTM Zone 10N coordinate system. Ran union of both the SFEI and Richardson Bay 2019 layers. Merged features to create one single attribute table for eelgrass cover from all survey years. Removed extraneous columns in the attribute table, recalculated area fields based on new extent, and applied symbology.
This feature service provides transit routes for the San Francisco Bay Region that were produced by the California Department of Transportation (Caltrans). The features were extracted by Metropolitan Transportation Commission staff from statewide data produced by Caltrans.For information on how Caltrans developed the source data, and to access the complete data set, please visit the High Quality Transit Areas Analysis Open Data Portal.
The Digital Geologic Map of San Francisco and parts of Oakland, California is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: USGS. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (sfoa_metadata.txt; available at http://nrdata.nps.gov/goga/nrdata/geology/gis/sfoa_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (sfoa_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Golden Gate National Recreation Area, Fort Point National Historic Site, Rosie the Riveter National Historical Park and San Francisco Maritime National Historical Park.
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-for-modeling-version-4-1## A more recent version of this product appears here:
This product will continue to be distributed for archival purposes.
Changes in the current bathymetry release (version 4) are limited to the region east of the Carquinez Strait (starting around Carquinez Bridge). To facilitate compatibility released by us and our partners, DWR distribute the region west as a separate companion tile and delineate the boundary of active revision in the present product in a place where its source data matches that of other Bay elevation models, e.g., the 2m seamless high-resolution bathymetric and topographic DEM of San Francisco Bay by USGS Earth Resources Observation and Science Center (EROS) (https://topotools.cr.usgs.gov/coned/sanfrancisco.php ), the 2010 San Francisco Bay DEM by National Oceanic and Atmospheric Administration (https://www.ngdc.noaa.gov/metaview/page?xml=NOAA/NESDIS/NGDC/MGG/DEM/iso/xml/741.xml&view=getDataView&header=none ) or the prior (version 3) 10m digital elevation model (https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-v3 ).The 10m DEM for the Bay-Delta is based on the first on the list, i.e. EROS’ 2m DEM for the Bay
New work reported here was done at 2m resolution, although the improvements have been incorporated into the 10m products as much as possible. Relative to the previous DWR release (https://data.cnra.ca.gov/dataset/san-francisco-bay-and-sacramento-san-joaquin-delta-dem-v3), the 2m DEM product reported here consolidates work at this resolution into a small number of larger surfaces representing approximately one-third of the Delta (link to the Coverage Areas page). Laterally, the 2m models now extend over the levee crest as needed to match well with Delta LiDAR (http://www.atlas.ca.gov/download.html#/casil/imageryBaseMapsLandCover/lidar2009 ), the main terrestrial source of data used in this work. The 10m product (link to the Coverage Areas page) is based on the updated USGS DEM (https://www.sciencebase.gov/catalog/item/58599681e4b01224f329b484 ). In places where updated 2m models overlap the 10 meters, the 10m base elevation model was updated by resampling the new 2m model and adding levee enforcement. At the border between the 2m and 10m models, the two resolutions were locally edge-matched over a small region to maintain smoothness. For more information, please refer to the article: A Revised Continuous Surface Elevation Model for Modeling (link to Chapter 5 in the 2018 Annual Report).
Please note that by agreement with our data providers we distribute only our own integrated maps, not the original source point data.
Version: | 4 |
Time Completed: | June 2018 |
Horizontal Datum: | NAD83 |
Spheroid: | GRS1980 |
Projection: | UTM_Zone_10N (meters) |
Vertical Datum: | NAVD88 (meters) |
This point shapefile contains the locations of transit routes, including railways, ferries, and buses in the San Francisco Bay Area of California. This layer is part of the Bay Area Metropolitan Transportation Commission (MTC) GIS Maps and Data collection.
The Digital Geologic Map of the San Francisco North Quadrangle and part the Point Bonita Quadrangle, California is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: USGS. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (sfno_metadata.txt; available at http://nrdata.nps.gov/goga/nrdata/geology/gis/sfno_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (sfno_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Fort Point National Historic Site and Golden Gate National Recreation Area.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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A. SUMMARY This dataset contains San Francisco Board of Supervisor district boundaries approved by the San Francisco Redistricting Task Force in April 2022 following redistricting based on the 2020 Decennial Census.
B. HOW THE DATASET IS CREATED The dataset was created from the final map submitted by the San Francisco Redistricting Task Force. Boundaries in this map were decided using data from the 2020 Census on the number of people living in each census block in the City and County. This data includes the number of individuals incarcerated in facilities under the control of the Department of Corrections and Rehabilitation based on their last known residential address. This information is made available by the Statewide Database based on U.S. Census Bureau Census Redistricting Data (P.L. 94-171).
These map boundaries were trimmed to align with the city and county's physical boundaries for greater usability. This trimming mainly consisted of excluding the water around the City and County from the boundaries.
C. UPDATE PROCESS Supervisor District boundaries are updated every 10 years following the federal decennial census. The Supervisor District boundaries reflected in this dataset will remain unchanged. A new dataset will be created after the next decennial census and redistricting process are completed.
The dataset is manually updated as new members of the Board of Supervisors take office. The most recent manual update date is reflected in the 'data_as_of' field.
Once the redistricting process is completed after the next decennial census and a new dataset is published, this dataset will become static and will no longer be updated.
D. HOW TO USE THIS DATASET This dataset can be joined to other datasets for analysis and reporting at the Supervisor District level.
If you are building an automated reporting pipeline using Socrata API access, we recommend using this dataset if you'd like your boundaries to remain static. If you would like the boundaries to automatically update after each decennial census to reflect the most recent Supervisor District boundaries, see the Current Supervisor Districts dataset or the Current Supervisor Districts (trimmed to remove water and other non-populated City territories) dataset.
E. RELATED DATASETS Supervisor Districts (2012) Current Supervisor Districts Current Supervisor Districts (trimmed to remove water and non-populated areas)
This is an ESRI (ArcGIS) shapefile of a 50 km buffer surrounding the Upper San Francisco Estuary hydrodynamic subregions (see GIS Shapefile of Hydrodynamic Subregions of the Upper San Francisco Estuary data package). Contaminants can also be imported to the Estuary from upstream sources. As a rule-of-thumb, water travels approximately 50 km (30 miles) in a day. Therefore I delineated a drainage area that extends 50 km upstream from the boundary of the subregions (or until reaching the watershed divide where streams drain the western slope of the Coast Ranges directly into San Francisco Bay. This buffer area does not overlap with or include the hydrodynamic subregions.
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of San Francisco map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of San Francisco map area data layers. Data layers are symbolized as shown on the associated map sheets.
--------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.
MIT Licensehttps://opensource.org/licenses/MIT
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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
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.