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.

The Priority Neighborhoods dataset is a part of the City of Oakland Department of Transportation's (OakDOT's) Geographic Equity Toolbox. The Priority Neighborhoods GIS dataset relies upon demographic data from the American Community Survey (ACS). This dataset assigns each census tract in Oakland a numerical priority value and a quantile from lowest and highest, as determined by the following seven weighted demographic factors (with weights in brackets "[XX%]"): • People of Color [25%] • Low-income Households (<50% of Area Median Income for a 4-person household) [25%] • People with Disability [10%] • Seniors 65 Years and Over [10%] • Single Parent Families [10%] • Severely Rent-Burdened Households [10%] • Low Educational Attainment (less than a bachelor's degree) [10%]

This dataset was last updated in October 2024 with data from the 2022 5-year (i.e., averaged from 2018 through 2022) American Community Survey (ACS). The ACS is managed by the United States Census Bureau; learn more about the ACS at: https://www.census.gov/programs-surveys/acs.

See the online map and read the methodology at: https://www.oaklandca.gov/resources/oakdot-geographic-equity-toolbox. This dataset is maintained by the OakDOT Race and Equity Team; learn more about the team at: https://www.oaklandca.gov/topics/oakdot-race-and-equity-team.

Field Descriptions: • TRACT: Census Tract Number • QUINTILE: Priority Quintile (calculated) • PLAN_AREA: OakDOT Planning Area • POPULATION: Population (average from 2018 through 2022) • PCT_POC: Percent People of Color • PCT_INC: Percent Low Income • PCT_SRB: Percent Severely Rent-Burdened • PCT_PWD: People with a Disability • PCT_SENIOR: Percent Seniors • PCT_SPH: Percent Single Parent Households • PCT_EDU: Percent Low Educational Attainment • RAT_POC: Ratio of People of Color (compared to Citywide average) • RAT_INC: Ratio of Low Income (compared to Citywide average) • RAT_SRB: Ratio of Severely Rent-Burdened (compared to Citywide average) • RAT_PWD: Ratio of People with a Disability (compared to Citywide average) • RAT_SENIOR: Ratio of Seniors (compared to Citywide average) • RAT_SPH: Ratio of Single Parent Households (compared to Citywide average) • RAT_EDU: Ratio of Low Educational Attainment (compared to Citywide average) • RAT_SCORE: Priority Ratio (compared to Citywide average) • ALAND: Land Area in square feet

City of Oakland, Department of Transportation (OakDOT) 250 Frank H. Ogawa Plaza, Suite 4314 | Oakland, CA 94612

These data were automated to provide an accurate high-resolution historical shoreline of Oakland, California suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

This map provides information on the major projects of the City of Oakland’s Department of Transportation (OakDOT).

Click on the links below to download data in tabular format:

Major Capital ProjectsPaving ProjectsBicycle ProjectsOther Agency ProjectsData Dictionary/Field Descriptions

See the following resources for information on additional projects:

PavingBicycle FacilitiesPublic Works Capital Projects

For information on routine maintenance requests, see SeeClickFix or visit OAK 311.

For information on how the City of Oakland prioritizes and funds transportation improvements, click here to learn about the City’s Capital Improvements Program.

How are we doing? We want to hear from you!Send us an email: OakDOT@oaklandca.gov

Disclaimer: This map and data are provided to the public for informational purposes only. The City of Oakland assumes no responsibility arising from the use of this information. The map and associated data are provided without warranty of any kind, either expressed or implied. Information on projects is subject to change without notice.Current update: 08/19/2021Previous updates: 3.17.2020, 1.14.2020, 09.17.2019, 06.04.2019, 4.06.2019, 02.15.2019, 1.14.2018

This layer is sourced from gis.acgov.org.

This data release is comprised of geospatial and tabular data developed for the HayWired communities at risk analysis. The HayWired earthquake scenario is a magnitude 7.0 earthquake hypothesized to occur on the Hayward Fault on April 18, 2018, with an epicenter in the city of Oakland, CA. The following 17 counties are included in this analysis unless otherwise specified: Alameda, Contra Costa, Marin, Merced, Monterey, Napa, Sacramento, San Benito, San Francisco, San Joaquin, San Mateo, Santa Clara, Santa Cruz, Solano, Sonoma, Stanislaus, and Yolo. The vector data are a geospatial representation of building damage based on square footage damage estimates by Hazus occupancy class for developed areas covering all census tracts in 17 counties in and around the San Francisco Bay region in California, for (1) earthquake hazards (ground shaking, landslide, and liquefaction) and (2) all hazards (ground shaking, landslide, liquefaction, and fire) resulting from the HayWired earthquake scenario mainshock. The tabular data cover: (1) damage estimates, by Hazus occupancy class, of square footage, building counts, and households affected by the HayWired earthquake scenario mainshock for all census tracts in 17 counties in and around the San Francisco Bay region in California; (2) potential total population residing in block groups in nine counties in the San Francisco Bay region in California (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma); (3) a subset of select tables for 17 counties in and around the San Francisco Bay region in California from the U.S. Census Bureau American Community Survey 5-year (2012-2016) estimates at the block group level selected to represent potentially vulnerable populations that may, in the event of a major disaster, leave an area rather than stay; and (4) building and contents damage estimates (in thousands of dollars, 2005 vintage), by Hazus occupancy class, for the HayWired earthquake scenario mainshock for 17 counties in and around the San Francisco Bay region in California. The vector .SHP datasets were developed and intended for use in GIS applications such as ESRI's ArcGIS software suite. The tab-delimited .TXT datasets were developed and intended for use in standalone spreadsheet or database applications (such as Microsoft Excel or Access). Please note that some of these data are not optimized for use in GIS applications (such as ESRI's ArcGIS software suite) as-is--census tracts or counties are repeated (the data are not "one-to-one"), so not all information belonging to a tract or county would necessarily be associated with a single record. Separate preparation is needed in a standalone spreadsheet or database application like Microsoft Excel or Microsoft Access before using these data in a GIS. These data support the following publications: Johnson, L.A., Jones, J.L., Wein, A.M., and Peters, J., 2020, Communities at risk analysis of the HayWired scenario, chaps. U1-U5 of Detweiler, S.T., and Wein, A.M., eds., The HayWired earthquake scenario--Societal consequences: U.S. Geological Survey Scientific Investigations Report 2017-5013, https://doi.org/10.3133/sir20175013.

Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. Using Sentinel-2 satellite thermal data along with on-the-ground sensors, air temperature and heat indexes are calculated for morning, afternoon, and evening time periods. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as dynamic image services.Dataset SummaryPhenomenon Mapped: heat indexUnits: degrees Fahrenheit Cell Size: 30 metersPixel Type: 32 bit floating pointData Coordinate Systems: WGS84 Mosaic Projection: WGS84 Extent: cities within the United StatesSource: NOAA and CAPA StrategiesPublication Date: September 20, 2021What can you do with this layer?This imagery layer supports communities' UHI spatial analysis and mapping capabilities. The symbology can be manually changed, or a processing template applied to the layer will provide a custom rendering. Each city can be queried.Related layers include Morning Heat Index and Evening Heat Index. Cities IncludedBoulder, CO Brooklyn, NY Greenwich Village, NY Columbia, SC Columbia, MO Columbus, OH Knoxville, TN Jacksonville, FL Las Vegas, NV Milwaukee, WI Nashville, TN Omaha, NE Philadelphia, PA Rockville, MD Gaithersburg, MD Takoma Park, MD San Francisco, CA Spokane, WA Abingdon, VA Albuquerque, NM Arlington, MA Woburn, MA Arlington, VA Atlanta, GA Charleston, SC Charlottesville, VA Clarksville, IN Farmville, VA Gresham, OR Harrisonburg, VA Kansas City, MO Lynchburg, VA Manhattan, NY Bronx, NY Newark, NJ Jersey City, NJ Elizabeth, NJ Petersburg, VA Raleigh, NC Durham, NC Richmond, VA Richmond, IN Salem, VA San Diego, CA Virginia Beach, VA Winchester, VA Austin, TX Burlington, VT Cincinnati, OH Detroit, MI El Paso, TX Houston, TX Jackson, MS Las Cruces, NM Miami, FL New Orleans, LA Providence, RI Roanoke, VA San Jose, CA Seattle, WA Vancouver, BC Canada Boston, MA Fort Lauderdale, FL Honolulu, HI Boise, ID Nampa, ID Los Angeles, CA Yonkers, NY Oakland, CA Berkeley, CA San Juan, PR Sacramento, CA San Bernardino, CA Victorville, CA West Palm Beach, FL Worcester, MA Washington, D.C. Baltimore, MD Portland, ORCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Afternoon Heat Index Observations in Floating-Point (°F)

This map shows four of these densely populated areas are in California. The San Francisco-Oakland and San Jose Urban Areas rank second and third, respectively. That the New York Metropolitan area ranks fifth on this list shows that this density ranking is greatly affected by the nature of the land area designated as urban. Census Urban Areas comprise an urban core and associated suburbs. California's urban and suburban areas are more uniform in density when compared to New York's urban core and suburban periphery which have vastly different densities. Delano ranks fourth because it has a very small land area and its population is augmented by two large California State Prisons housing 10,000 inmates.