GTFS To Public Transit Data Model (Public Transit)

Summary

Converts one or more General Transit Feed Specification (GTFS) public transit datasets to a set of feature classes and tables that represent the transit stops, lines, and schedules in the format defined by the Network Analyst public transit data model.

The transit data model feature classes and tables produced by this tool are as follows:

• Stops
• LineVariantElements
• Calendars
• CalendarExceptions
• Lines
• LineVariants
• Runs
• ScheduleElements
• Schedules

The output from this tool can be used as input to the Connect Public Transit Data Model To Streets tool to prepare all necessary inputs for a transit-enabled network dataset. The complete workflow for creating such a network dataset is described in Create and use a network dataset with public transit data.

The output from this tool can also be used as input to the Calculate Transit Service Frequency tool.

Usage

• The data from all input GTFS datasets will be combined into the same set of output tables and feature classes. The typical motivation for using multiple input GTFS datasets is to model a metropolitan area in which multiple transit service providers operate in the same geographic area.

• The tool performs some validation on each input GTFS dataset to check for common data problems. When a problem is found, the tool issues a warning and does not process that dataset. The tool output will include data from only those input GTFS datasets that were successfully processed. If some GTFS datasets are processed successfully and others are not processed because of data problems, you can fix the data problems and append the fixed GTFS datasets to the existing tool output by running the tool again with the Append to existing tables parameter checked (append = "APPEND" in Python).

• Each input GTFS dataset must contain the stops.txt, routes.txt, trips.txt, and stop_times.txt files, and either the calendar.txt or calendar_dates.txt file, or both. The frequencies.txt file will be used if it is present.

• Although GTFS allows blank values for the arrival_time and departure_time fields in the stop_times.txt file, exact times are required by the Network Analyst public transit data model for consumption by the Public Transit evaluator in the network dataset. Check the Interpolate blank stop times parameter (interpolate = "INTERPOLATE" in Python) to estimate arrival and departure times for an input GTFS dataset with a stop_times.txt file that does not have explicit values for all arrival_time and departure_time fields.

• The tool constructs the Stops feature class using the latitude and longitude values from the stop_lat and stop_lon fields in the GTFS stops.txt file.

• The stop_lat and stop_lon fields in the GTFS stops.txt file define the latitude and longitude of stops. These fields are permitted by the specification to be null if the stop's location_type field has a value of 3 or 4. However, because this tool creates geographical features to represent stops, it cannot map stops that have no latitude or longitude. Consequently, stops with location_type values of 3 or 4 that have null values for stop_lat or stop_lon will be skipped and not included in the tool's output.

• The tool constructs the LineVariantElements features by creating a straight line between each pair of stops that is directly connected by a transit trip.

  Note:

  The LineVariantElements features are not intended to represent the actual geographic paths taken by buses, trains, or other public transit vehicles but are instead representative of logical connections in the transit system. LineVariantElements features are not meant to be used for visualization. The Public Transit evaluator in the network dataset will use the public transit schedules to determine the travel time required to traverse a LineVariantElements feature, so its shape and length are irrelevant. However, you can optionally edit the shapes of the LineVariantElements features manually, but do not split or merge the features.

• If more than one GTFS route or variation of the same route provides service between the same two stops, one LineVariantElements feature will be created per route or route variation providing the service.

  For example, if GTFS route_id 10 and GTFS route_id 47 both travel between the same two stops with no other stops in between, the tool will generate two LineVariantElements features, one for route_id 10 and one for route_id 47. These two line feature will be geographically coincident.

  Similarly, if route_id 15 serves two different end stations, but all route_id 15 trips, regardless of end station connect a particular pair of stops, one LineVariantElements feature will be created per end station, resulting in two coincident LineVariantElements features. These route variations typically correspond to different shape_id values in the GTFS dataset.

• Because the public transit data model requires feature classes and tables with specific names, it is not possible to include more than one set of public transit data model feature classes and tables in the same geodatabase. Do not include the target feature dataset in a geodatabase with an existing feature dataset containing public transit data model feature classes.

• If the target feature dataset is in an enterprise geodatabase, it must not be versioned. Before running the tool, reconcile and post the data in the feature dataset and unregister it as versioned.

Parameters

Dialog

Label	Explanation	Data Type
Input GTFS Folders	One or more folders containing valid GTFS data. Each folder must contain the GTFS stops.txt, routes.txt, trips.txt, and stop_times.txt files and either the calendar.txt or calendar_dates.txt file, or both.	Folder
Target Feature Dataset	The feature dataset where the transit-enabled network dataset will be created. The Stops and LineVariantElements feature classes created by this tool will be placed in this feature dataset, and the output tables created by this tool will be placed in this feature dataset's parent geodatabase. The feature dataset can be in a file geodatabase or an enterprise geodatabase and can have any spatial reference. If the target feature dataset is in an enterprise geodatabase, it must not be versioned. Do not include the target feature dataset in a geodatabase with an existing feature dataset containing public transit data model feature classes.	Feature Dataset
Interpolate blank stop times (Optional)	Specifies whether blank values from the arrival_time and departure_time fields in the GTFS stop_times.txt file will be interpolated when creating the public transit data model tables. Checked—Blank values will be interpolated using simple linear interpolation. The original GTFS data will not be altered. If there are no blank values in the original data, no interpolation will occur. Unchecked—Blank values will not be interpolated. If blank values are found in the input GTFS data, the tool will issue a warning and will not process the GTFS dataset. This is the default.	Boolean
Append to existing tables (Optional)	Specifies whether the input GTFS datasets will be appended to existing public transit data model feature classes and tables in the target feature dataset and its parent geodatabase. This parameter will be hidden if the target feature dataset and its parent geodatabase do not contain existing public transit data model feature classes and tables. Checked—Data will be appended to the existing feature classes and tables. Unchecked—Data will not be appended. Existing feature classes and tables will be overwritten. This is the default.	Boolean

Derived Output

Label	Explanation	Data Type
Updated Target Feature Dataset	The feature dataset to which the new feature classes have been added.	Feature Dataset
Output Stops	The Stops feature class for the Network Analyst public transit data model.	Feature Class
Output Line Variant Elements	The LineVariantElements feature class for the Network Analyst public transit data model.	Feature Class
Output Calendars	The Calendars table for the Network Analyst public transit data model.	Table
Output Calendar Exceptions	The CalendarExceptions table for the Network Analyst public transit data model.	Table
Output Lines	The Lines table for the Network Analyst public transit data model.	Table
Output Line Variants	The LineVariants table for the Network Analyst public transit data model.	Table
Output Runs	The Runs table for the Network Analyst public transit data model.	Table
Output Schedule Elements	The ScheduleElements table for the Network Analyst public transit data model.	Table
Output Schedules	The Schedules table for the Network Analyst public transit data model.	Table

Python

arcpy.transit.GTFSToPublicTransitDataModel(in_gtfs_folders, target_feature_dataset, {interpolate}, {append})

Name	Explanation	Data Type
in_gtfs_folders [in_gtfs_folders,...]	One or more folders containing valid GTFS data. Each folder must contain the GTFS stops.txt, routes.txt, trips.txt, and stop_times.txt files and either the calendar.txt or calendar_dates.txt file, or both.	Folder
target_feature_dataset	The feature dataset where the transit-enabled network dataset will be created. The Stops and LineVariantElements feature classes created by this tool will be placed in this feature dataset, and the output tables created by this tool will be placed in this feature dataset's parent geodatabase. The feature dataset can be in a file geodatabase or an enterprise geodatabase and can have any spatial reference. If the target feature dataset is in an enterprise geodatabase, it must not be versioned. Do not include the target feature dataset in a geodatabase with an existing feature dataset containing public transit data model feature classes.	Feature Dataset
interpolate (Optional)	Specifies whether blank values from the arrival_time and departure_time fields in the GTFS stop_times.txt file will be interpolated when creating the public transit data model tables. INTERPOLATE—Blank values will be interpolated using simple linear interpolation. The original GTFS data will not be altered. If there are no blank values in the original data, no interpolation will occur. NO_INTERPOLATE—Blank values will not be interpolated. If blank values are found in the input GTFS data, the tool will issue a warning and will not process the GTFS dataset. This is the default.	Boolean
append (Optional)	Specifies whether the input GTFS datasets will be appended to existing public transit data model feature classes and tables in the target feature dataset and its parent geodatabase. APPEND—Data will be appended to the existing feature classes and tables. NO_APPEND—Data will not be appended. Existing feature classes and tables will be overwritten. This is the default.	Boolean

Derived Output

Name	Explanation	Data Type
updated_target_feature_dataset	The feature dataset to which the new feature classes have been added.	Feature Dataset
output_stops	The Stops feature class for the Network Analyst public transit data model.	Feature Class
output_line_variant_elements	The LineVariantElements feature class for the Network Analyst public transit data model.	Feature Class
output_calendars	The Calendars table for the Network Analyst public transit data model.	Table
output_calendar_exceptions	The CalendarExceptions table for the Network Analyst public transit data model.	Table
output_lines	The Lines table for the Network Analyst public transit data model.	Table
output_line_variants	The LineVariants table for the Network Analyst public transit data model.	Table
output_runs	The Runs table for the Network Analyst public transit data model.	Table
output_schedule_elements	The ScheduleElements table for the Network Analyst public transit data model.	Table
output_schedules	The Schedules table for the Network Analyst public transit data model.	Table

Code sample

GTFSToPublicTransitDataModel example 1 (Python window)

The following script demonstrates how to use the GTFSToPublicTransitDataModel function in the Python window.

fd_path = r"E:\TransitAnalysis\TransitNetwork.gdb\TransitNetwork"
arcpy.transit.GTFSToPublicTransitDataModel([r"E:\GTFS\Agency1", r"E:\GTFS\Agency2"], fd_path)

GTFSToPublicTransitDataModel example 2 (stand-alone script)

The following stand-alone Python script demonstrates how the GTFSToPublicTransitDataModel and ConnectPublicTransitDataModelToStreets functions can be used together to create a transit-enabled network dataset.

import os
import arcpy
arcpy.CheckOutExtension("network")

gtfs_folders = [
    r"E:\GTFS\Agency1",
    r"E:\GTFS\Agency2"
]
streets_orig = r"E:\Data\StreetData.gdb\Streets"

working_folder = r"E:\TransitAnalysis"
nd_template = os.path.join(working_folder, "TransitNetworkTemplate.xml")
gdb_name = "TransitNetwork.gdb"
out_gdb = os.path.join(working_folder, gdb_name)
fd_name = "TransitNetwork"
fd_path = os.path.join(out_gdb, fd_name)
streets = os.path.join(fd_path, "Streets")
nd_name = "TransitNetwork_ND"
nd_path = os.path.join(fd_path, nd_name)

# Create a file geodatabase and feature dataset to store the network dataset
arcpy.management.CreateFileGDB(working_folder, gdb_name)
arcpy.management.CreateFeatureDataset(out_gdb, fd_name, arcpy.SpatialReference(4326))

# Copy the streets data into the feature dataset so it can be used by the network dataset
# If the original streets are not in the same spatial reference as the feature dataset, you might
# need to use the Project tool instead of Copy.
arcpy.management.Copy(streets_orig, streets)

# Convert the GTFS dataset into public transit data model tables and feature classes
arcpy.transit.GTFSToPublicTransitDataModel(gtfs_folders, fd_path)

# Connect the transit stops to the streets and create the rest of the data model feature classes
# Use an expression to connect transit stops only to streets where pedestrians are allowed.
where = "PedestriansAllowed = 1"
arcpy.transit.ConnectPublicTransitDataModelToStreets(fd_path, streets, "100 meters", where)

# Create the network dataset from a template
arcpy.na.CreateNetworkDatasetFromTemplate(nd_template, fd_path)

# Build the network dataset
arcpy.na.BuildNetwork(nd_path)

Environments

This tool does not use any geoprocessing environments.

Licensing information

• Basic: Yes
• Standard: Yes
• Advanced: Yes