A. SUMMARY
Location data of SFMTA Transit Vehicles. Location information includes reported location date and time, vehicle identifier, location latitude and longitude, heading and speed. This dataset will only contain data for the current calendar year and will reset to the next calendar year the first of every year. Prior years are saved as separate datasets.
B HOW THE DATASET IS CREATED
Vehicle location data is provided by the SFMTA’s computer aided dispatch and automated vehicle location system.
C. UPDATE PROCESS
Location data is published daily for the previous day, resulting in a lag, up to 24 hours.
D. HOW TO USE THIS DATASET
Location data can be used to visualize vehicle routes and city wide traffic patterns.

This file contains SFMTA transit stop and schedule data in the General Transit Feed Specification (GTFS) format, which is an open data standard. The SFMTA publishes new transit schedules in this format as soon as schedule changes are planned and finalized, which occurs at least quarterly (and usually more often).

For our legal protection, you'll need to agree to the SFMTA Transit Data License Agreement in order to use it.

Note: This is not real-time data, only scheduled service. For more regional routes and schedules (as well as real-time data) in the GTFS format please see the MTC's Portal for Open Transit Data.

A. SUMMARY
Historical location data of SFMTA Transit Vehicles for 2021. Location information includes reported location date and time, vehicle identifier, location latitude and longitude, heading and speed.
B. HOW THE DATASET IS CREATED
Vehicle location data is provided by the SFMTA’s computer aided dispatch and automated vehicle location system.
C. UPDATE PROCESS
Historical Data. This data will only be updated until the end of the year indicated.
D. HOW TO USE THIS DATASET
Location data can be used to visualize vehicle routes and city wide traffic patterns.

This workbook provides data and data dictionaries for the SFMTA 2015 Travel Decision SurveySFMTA Travel Decision Survey Data for 2015

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 762 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:
2015: August – October 2015

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 = 762(Total Sample). Margin of error = +/- 3.5%
• n = 382. Margin of error = +/- 4.95%
• n = 100. Margin of error = +/- 9.80%

This workbook provides data and data dictionaries for the SFMTA 2017 Travel Decision Survey.

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 804 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, Mandarin, Cantonese, and Tagalog. Surveying was conducted via random digit dial (RDD) and cell phone sample.
All 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:
2017: February - April 2017

The margin of error is related to sample size (n). For the total sample, the margin of error is 3.4% 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 = 804(Total Sample). Margin of error = +/- 3.4%
• n = 400. Margin of error = +/- 4.85%
• n = 100. Margin of error = +/- 9.80%

**Please refer to the downloadable XLSX attachment (http://bit.ly/SFMTATravelSurvey2019) for the complete dataset, metadata, and instructions for use.**

This workbook provides data and data dictionaries for the SFMTA 2019 Travel Decision Survey.

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 2.2: Mode Share target of 80% sustainable travel by 2030.
• 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 801 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, Mandarin, Cantonese, and Tagalog. Surveying was conducted via random digit dial (RDD) and cell phone sample.
All 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:
2019: May - August 2019

The margin of error is related to sample size (n). For the total sample, the margin of error is 3.3% 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 = 801(Total Sample). Margin of error = +/- 3.3%
• n = 400. Margin of error = +/- 4.85%
• n = 100. Margin of error = +/- 9.80%

This workbook provides data and data dictionaries for the SFMTA 2012 Travel Decision Survey.
The 2012 Summary Report, with methodology and survey instrument, is located at https://www.sfmta.com/about-sfmta/reports/travel-decision-survey-2012.
Data, methodologies, and summary report for other SFMTA travel decision surveys are 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.
This dataset incorporates 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:
2012: October 2012 – January 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%

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%

A. SUMMARY
This data shows the locations of slow streets designated as part of the SFMTA response to sheltering in place and supporting essential movement throughout San Francisco.

B. HOW THE DATASET IS CREATED
The data was created using the city's centerline (CNN) shapefile. Using the Slow Street extents, polylines from the CNN data were queried out. Additional fields were added to give the segments various attributes related to the Slow Streets program.

C. UPDATE PROCESS
As-needed.

D. HOW TO USE THIS DATASET
This data is mainly used to show the extent of Slow Streets implemented as part of the SFMTA's Slow Streets program. Each record is a block of Slow Street.

The City Survey asks residents to indicate their usage and satisfaction with city services and infrastructure like libraries, Muni, public safety, and street cleanliness. The City Survey was conducted every year from 1996 to 2004, and biennially from 2005 onward. The City Survey was not conducted in 2019 due to the COVID-19 pandemic, and resumed in 2023. Survey methodology was changed in 2015 from a mail to a phone survey, and expanded to include in-person and online options in 2023. Comparisons to previous years should be interpreted with caution.

Results should be weighted using the column "weight" in order to adjust for demographic differences between the City Survey sample and San Francisco's population. Please note that survey results were originally reported as unweighted until 1997. From 1997 onward, all City Survey results were reweighted with the exception of data from 2011. For ease of use, the column "weight" has been coded with a value of one for these years.

A code book is also attached to this dataset under About > Attachments. Neighborhood and Zip Code data have been hidden from this data set and are only available upon special request to citysurvey@sfgov.org.

For more information regarding San Francisco City Survey 1996-2023 Database, please visit the City Survey website at https://sf.gov/citysurvey or contact the San Francisco Controller's Office at citysurvey@sfgov.org.