- API data.sfgov.org | Last Updated 2017-11-01T20:34:04.000Z
Disclaimer: The Sea Level Rise (SLR) map shows the most extreme level of SLR possible. It is a very, very unlikely scenario that would only occur if no efforts to address SLR occur and both a King Tide and 100-year storm occur at the same time. The real purpose of the maps is to provide a broad net to help the City identify projects that that may be vulnerable. The data is based on what was in the ground as of 2010 and doesn’t include piers. The inundation maps and the associated analyses are intended as planning level tools to illustrate the potential for inundation and coastal flooding under a variety of future sea level rise and storm surge scenarios. The maps depict possible future inundation that could occur if nothing is done to adapt or prepare for sea level rise over the next century. The maps do not represent the exact location or depth of flooding. The maps relied on a 1-m digital elevation model created from LiDAR data collected in 2010 and 2011. Although care was taken to capture all relevant topographic features and coastal structures that may impact coastal inundation, it is possible that structures narrower than the 1-m horizontal map scale may not be fully represented. The maps are based on model outputs and do not account for all of the complex and dynamic San Francisco Bay processes or future conditions such as erosion, subsidence, future construction or shoreline protection upgrades, or other changes to San Francisco Bay or the region that may occur in response to sea level rise. For more context about the maps and analyses, including a description of the data and methods used, please see the Climate Stressors and Impacts Report: Bayside Sea Level Rise Inundation Mapping Technical Memorandum, July 2014. More information at http://onesanfrancisco.org/node/148
- API data.sfgov.org | Last Updated 2016-08-28T21:32:58.000Z
Consolidated Infant, Pre-K, and K-14 education points for facilities both public and private. Point features are intended to be located within a building footprint relevant to each site, so that they can be used to select an appropriate building footprint or parcel as seed for any required buffering. Buffering may be applied when limiting possible sites for certain businesses or specific individuals, whenever these must remain a minimum distance from school locations. Sources include: cde.ca.gov State of California Department of Education City and County Department of Technology, San Francisco Enterprise Geographic Information System Program Data current as of December 8, 2015
- API data.sfgov.org | Last Updated 2018-04-27T20:46:41.000Z
List of San Francisco Department of Public Health clinics offering flu vaccinations throughout the city in fall 2013.This dataset complies with the emerging Data Specification for Flu Shot Locations. For information about the specification, please see https://github.com/CityOfPhiladelphia/flu-shot-spec.For more information about SFDPH's Influenza Program www.sfcdcp.org/flu or call 311For more information about SFDPH's Open data Initiatives http://www.sfphes.org/resources/health-data or Contact Cyndy.email@example.com
- API data.sfgov.org | Last Updated 2018-05-01T14:37:08.000Z
These geographic designations were created to define geographic areas within San Francisco that have a higher density of vulnerable populations. These geographic designations will be used for the Health Care Services Master Plan and DPH's Community Health Needs Assessment. aov_fin - 1 = YES aov_fin - 0 = NO AOV's were defined using 2012-2016 ACS data at the census tract level and the following criteria: 1) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for persons of color OR 2) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for youth or seniors (65+) OR 3) Top 1/3rd for < 200% poverty or < 400% poverty & top 1/3rd for 2 other categories (unemployment, high school or less, limited English proficiency persons, linguistically isolated households, or disability) Tracts that had unstable data for an indicator were automatically given zero credit for that indicator. That is why two language variables are included in the bonus group, because there tend to be a high number of tracts with unstable data for language variables.
- API data.sfgov.org | Last Updated 2019-01-30T00:14:44.000Z
This data set includes the Office of the Assessor-Recorder’s secured property tax roll spanning from July 1, 2007 to June 30, 2018. It includes all legally disclosable information, including location of property, value of property, the unique property identifier, and specific property characteristics. The data is used to accurately and fairly appraise all taxable property in the City and County of San Francisco. The Office of the Assessor-Recorder makes no representation or warranty that the information provided is accurate and/or has no errors or omissions. This dataset is updated annually after the roll is closed and certified. This typically happens by August of each year.
- API data.sfgov.org | Last Updated 2019-04-19T23:24:13.000Z
Health care facilities located in San Francisco
- API data.sfgov.org | Last Updated 2016-08-28T21:33:14.000Z
Health care facilities located in San Francisco
- API data.sfgov.org | Last Updated 2016-03-15T17:42:10.000Z
This workbook provides data and data dictionaries for the SFMTA 2013 Travel Decision Survey. The 2013 Summary Report and Methodology, including the survey instrument, can be found online at https://www.sfmta.com/about-sfmta/reports/travel-decision-survey-2013. Data, methodologies, and summary report for other SFMTA travel decision surveys is available on sfmta.com. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY2018 with a 95% confidence level and MOE +/- 5% or less. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among with approximately 750 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, and Cantonese. Surveying was conducted via random digit dial (RDD) and cell phone sample. All three survey datasets incorporate respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2013: April 2014 – May 2014 (survey name of 2013 reflects the originally planned start date of Fall 2013) The margin of error is related to sample size (n). For the total sample, the margin of error is 3.5% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 767 (Total Sample). Margin of error = +/- 3.5% • n = 384. Margin of error = +/- 4.95% • n = 100. Margin of error = +/- 9.80%
- API data.sfgov.org | Last Updated 2017-12-08T00:39:18.000Z
Land use categories for every parcel in San Francisco. The land use categories are derived from a range of City and commercial databases. Where building square footages were missing from these databases they were derived from a LIDAR survey flown in 2007.<br><br>Land use categories are as follows (units are square feet):<br> CIE = Cultural, Institutional, Educational<br>MED = Medical<br>MIPS = Office (Management, Information, Professional Services)<br>MIXED = Mixed Uses (Without Residential)<br>MIXRES = Mixed Uses (With Residential)<br>PDR = Industrial (Production, Distribution, Repair)<br>RETAIL/ENT = Retail, Entertainment<br>RESIDENT = Residential<br>VISITOR = Hotels, Visitor Services<br>VACANT = Vacant<br>ROW = Right-of-Way<br>OPENSPACE = Open Space<br><br>Other attributes are:<br>RESUNITS = Residential Units<br>BLDGSQFT = Square footage data<br>YRBUILT = year built<br>TOTAL_USES = Business points from Dun & Bradstreet were spatially aggregated to the closest parcel, and this field is the sum of the square footage fields<br>The subsequent fields (CIE, MED, MIPS, RETAIL, PDER & VISITOR) were derived using the NAICS codes supplied in the Dun & Bradstreet dataset, and the previous TOTAL_USES column.<br><br>The determining factor for a parcel's LANDUSE is if the square footage of any non-residential use is 80% or more of its total uses. Otherwise it becomes MIXED.<br><br>In the case where RESIDENT use has some square footage of non-residential use, this is mainly accessory uses such as home businesses, freelancers, etc. Last updated: March, 2016
- API data.sfgov.org | Last Updated 2019-07-13T15:21:43.000Z
These routes are manually updated and have not been so in a while. Public Works is working on a new approach to digitizing these routes. These are provided as a reference. They are not accurate representations of regulations. Always refer to the posted signs. Street sweeper schedule that includes: when and where. The data is provided as is. The data in this dataset is for expected time it takes to sweep a route which usually but not always coincides with the no parking sign time posted by MTA in the street. When in doubt always refer to the sign posted by MTA in the street as the official time. Please use the data understanding the limitations.