This file README was updated on 2021-01-05 by Kristin Carlson ------------------- GENERAL INFORMATION ------------------- Title of Dataset: Block-level, non-work accessibility data for planned transitways in the Twin Cities Supporting Data for Transitway Impacts Research Program (TIRP) 2019-2020 Project titled: Addressing Accessibility and Equity along Transitways: Towards a Mixed Methods Toolkit-Part I. Author Information: Kristin Carlson, Andrew Owen Principal Investigator Contact Information Name: Andrew Owen Institution: University of Minnesota Address: Center for Transportation Studies, 2221 University Ave SE #440, Minneapolis, Minnesota 55455 Email: aowen@umn.edu Associate or Co-investigator Contact information Name: Kristin Carlson Institution: University of Minnesota Address: Center for Transportation Studies, 2221 University Ave SE #440, Minneapolis, Minnesota 55455 Email: carl4498@umn.edu ORCID: 0000-0002-4542-5294 Date of data collection: 20200101-20201231 Geographic location of data collection: University of Minnesota Information about funding sources that supported the collection of the data: This research was sponsored by the Transitway Impacts Research Program (TIRP) during the 2019-2020 award cycle. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Creative Commons Attribution license (CC-By) (https://creativecommons.org/licenses/by/3.0/us/) 2. Was data derived from another source? Input data include: General Transit Feed Spefication (GTFS), OpenStreetMap pedestrian network, Census Bureau Longitudinal Employer-Household Dynamics (LEHD) data, licensed point-of-interest data from TomTom Inc. 3. Recommended citation for the data: Carlson, Kristin; Owen, Andrew. (2021). Block-level, non-work accessibility data for planned transitways in the Twin Cities. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/95jr-dt88. --------------------- DATA & FILE OVERVIEW --------------------- 1. A. b_line.zip b_79am: B Line and route 21 scenario, 7-9 AM b_111: B Line and route 21 scenario, 11 AM-1 PM b_46: B Line and route 21 scenario, 4-6 PM b_79pm: B Line and route 21 scenario, 7-9 PM B. d_line.zip d_79am: D Line and route 5 scenario, 7-9 AM d_111: D Line and route 5 scenario, 11 AM-1 PM d_46: D Line and route 5 scenario, 4-6 PM d_79pm: D Line and route 5 scenario, 7-9 PM C. e_line.zip e_79am: E Line and route 6 scenario, 7-9 AM e_111: E Line and route 6 scenario, 11 AM-1 PM e_46: E Line and route 6 scenario, 4-6 PM e_79pm: E Line and route 6 scenario, 7-9 PM D. bde_line.zip bde_79am: B Line, D Line, E Line and routes 21, 5, 6 scenario, 7-9 AM bde_111: B Line, D Line, E Line and routes 21, 5, 6 scenario, 11 AM-1 PM bde_46: B Line, D Line, E Line and routes 21, 5, 6 scenario, 4-6 PM bde_79pm: B Line, D Line, E Line and routes 21, 5, 6 scenario, 7-9 PM E. gold_line.zip gold_79am: Gold Line scenario, 7-9 AM gold_111: Gold Line scenario, 11 AM-1 PM gold_46: Gold Line scenario, 4-6 PM gold_79pm: Gold Line scenario, 7-9 PM F. rush_line.zip rush_79am: Rush Line scenario, 7-9 AM rush_111: Rush Line scenario, 11 AM-1 PM rush_46: Rush Line scenario, 4-6 PM rush_79pm: Rush Line scenario, 7-9 PM G. goldrush_line.zip goldrush_79am: Gold Line and Rush Line scenario, 7-9 AM goldrush_111: Gold Line and Rush Line scenario, 11 AM-1 PM goldrush_46: Gold Line and Rush Line scenario, 4-6 PM goldrush_79pm: Gold Line and Rush Line scenario, 7-9 PM 2. Relationship between files: Each geopackage file corresponds with a transitway scenario and departure time intervale. The spatial data contains five travel time and travel time change (seconds) result layers corresponding to the destination types examined in this research. Grocery stores = "grocery", primary healthcare = "health", elementary schools = "es", middle schools = "ms", high schools = "hs". 3. Additional related data collected that was not included in the current data package: The report associated with this data uses aggregated summary statistics for the Twin Cities metropolitan area. The aggregated tables are not included in this data package but can be recalculated by weighting each block-level travel times by resident worker population to get a single measure for the metro. Similarly the results can be disaggregated by worker demographic features availabile in the U.S. Census Bureau's LODES dataset. -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: The methodology applied in this research uses origin block to destination point travel time matrices. The routing methods used in this research include a combination of travel by walking and transit to reach a destination. In some cases, the fastest trip to a nearby location may use only walking, and no transit travel. The travel time that is fastest, whether that is by walking or by walking plus transit, is reflected in the data. Five destination types are selected for the non-work accessibility analyses. These include grocery stores, primary healthcare facilities, high schools, middle schools, and elementary schools. The minimum travel time needed to reach one, two, three, or more of these destinations by transit for blocks in the Twin Cities are calculated under a variety of parameters. Data describing the distribution of labor and employment in the region are drawn from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics program (LEHD) for 2017. 2. Methods for processing the data: Raw data are joined to spatial data to produce the geopackage files. 3. Instrument- or software-specific information needed to interpret the data: ArcGIS, QGIS, Excel for .dbf files. 4. Describe any quality-assurance procedures performed on the data: Accessibilities and travel times are compared against annually reported accessibility data produced by the National Accessibility Evaluation. 5. People involved with sample collection, processing, analysis and/or submission: Kristin Carlson: Data collection, methodology development, analysis, reporting Andrew Owen: Methodology development, analysis, reporting ----------------------------------------- DATA-SPECIFIC INFORMATION ----------------------------------------- 1. Number of variables: 42 2. Number of cases/rows: 51,625 3. Variable List Fields: GEOID10: census block id bs_1: baseline scenario travel time to the first reachable destination updt_1: alternative scenario travel time to the first reachable destination abschg1: the difference in travel time, (updt_1 - bs_1) pctchg1: the percent change in travel time to the first reachable destination between the alternative and baseline scenario. 0.55 = 55% . . . bs_10: baseline scenario travel time to the tenth reachable destination updt_10: alternative scenario travel time to the tenth reachable destination abschg10: the difference in travel time, (alt_2 - bs_2) pctchg10: the percent change in travel time to the tenth reachable destination between the alternative and baseline scenario. 0.55 = 55%