Deprecation notice: This tool is deprecated because this functionality is now available with out-of-the-box tools in ArcGIS Pro. The tool author will no longer be making further enhancements or fixing major bugs.Use Add GTFS to a Network Dataset to incorporate transit data into a network dataset so you can perform schedule-aware analyses using the Network Analyst tools in ArcMap.After creating your network dataset, you can use the ArcGIS Network Analyst tools, like Service Area and OD Cost Matrix, to perform transit/pedestrian accessibility analyses, make decisions about where to locate new facilities, find populations underserved by transit or particular types of facilities, or visualize the areas reachable from your business at different times of day. You can also publish services in ArcGIS Server that use your network dataset.The Add GTFS to a Network Dataset tool suite consists of a toolbox to pre-process the GTFS data to prepare it for use in the network dataset and a custom GTFS transit evaluator you must install that helps the network dataset read the GTFS schedules. A user's guide is included to help you set up your network dataset and run analyses.Instructions:Download the tool. It will be a zip file.Unzip the file and put it in a permanent location on your machine where you won't lose it. Do not save the unzipped tool folder on a network drive, the Desktop, or any other special reserved Windows folders (like C:\Program Files) because this could cause problems later.The unzipped file contains an installer, AddGTFStoaNetworkDataset_Installer.exe. Double-click this to run it. The installation should proceed quickly, and it should say "Completed" when finished.Read the User's Guide for instructions on creating and using your network dataset.System requirements:ArcMap 10.1 or higher with a Desktop Standard (ArcEditor) license. (You can still use it if you have a Desktop Basic license, but you will have to find an alternate method for one of the pre-processing tools.) ArcMap 10.6 or higher is recommended because you will be able to construct your network dataset much more easily using a template rather than having to do it manually step by step. This tool does not work in ArcGIS Pro. See the User's Guide for more information.Network Analyst extensionThe necessary permissions to install something on your computer.Data requirements:Street data for the area covered by your transit system, preferably data including pedestrian attributes. If you need help preparing high-quality street data for your network, please review this tutorial.A valid GTFS dataset. If your GTFS dataset has blank values for arrival_time and departure_time in stop_times.txt, you will not be able to run this tool. You can download and use the Interpolate Blank Stop Times tool to estimate blank arrival_time and departure_time values for your dataset if you still want to use it.Help forum

The Intelligent Road Network dataset provided by the Transport Department includes traffic directions, turning restrictions at road junctions, stopping restrictions, on-street parking spaces and other road traffic data for supporting the development of intelligent transport system, fleet management system and car navigation etc. by the public.

Esri China (HK) has prepared this File Geodatabase containing a Network Dataset for the Intelligent Road Network to support Esri GIS users to use the dataset in ArcGIS Pro without going through long configuration steps. Please refer to this guideline to use the Road Network Dataset in ArcGIS Pro for routing analysis. This network dataset has been configured and deployed the following restrictions:

Speed LimitTurnIntersectionTraffic FeaturesPedestrian ZoneTraffic Sign of ProhibitionVehicle RestrictionThe coordinate system of this dataset is Hong Kong 1980 Grid.The objectives of uploading the network dataset to ArcGIS Online platform are to facilitate our Hong Kong ArcGIS users to utilize the data in a spatial ready format and save their data conversion effort.For details about the schema and information about the content and relationship of the data, please refer to the data dictionary provided by Transport Department at https://data.gov.hk/en-data/dataset/hk-td-tis_15-road-network-v2.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.Dataset last updated on: 2021 July

This is a tutorial on how to use GIP data for the ESRI ArcGIS Network Analyst.

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

The data has been automatically extracted from OSM and transformed to a full functional Network Dataset with a tool written by Eva Peters. For more information on the tool and Evas thesis click here (German) or here (English). Check out all functions like routing, service area, cost matrix etc. Get further Information on Network Analyst in the ArcGIS Desktop Help.

In dieser StoryMap stellen wir Euch den ArcGIS Network Analyst vor und zeigen Euch in einem beispielhaften Workflow, wie Ihr in ArcGIS Pro für eine Standortsuche Daten vorbereiten und Analysen mit dem ArcGIS Network Analyst durchführen könnt.Was ist der ArcGIS Network Analyst?Unternehmen, der öffentliche Dienst und andere Organisationen profitieren von der ArcGIS Network Analyst Erweiterung, weil der Betrieb effizienter abgewickelt und bessere strategische Entscheidungen getroffen werden können. Unternehmen können so ein besseres Verständnis der dynamischen Märkte entwickeln, sowohl der aktuellen Märkte als auch zukünftiger Märkte, nachdem sie ermittelt haben, wer Zugang zu ihren Waren oder Dienstleistungen hat. Transportkosten können gesenkt werden, indem Stopps optimal geplant und die kürzesten Wege zwischen den Stopps ermittelt werden, wobei verschiedene Einschränkungen wie Zeitfenster, Fahrzeugkapazitäten und maximale Fahrzeiten berücksichtigt werden. Der Kundendienst kann mithilfe von kürzeren Reaktionszeiten oder kundenfreundlicheren Standorten verbessert werden. Die ArcGIS Network Analyst Erweiterung erleichtert die Ermittlung und Lösung von Problemen dieser Art. Forscher und Analysten profitieren gleichermaßen von der Fähigkeit der Erweiterung zum Bestimmen der kostengünstigsten Netzwerkrouten zwischen verschiedenen Start- und Zielorten. Die Start-Ziel-Kostenmatrizen, die von der ArcGIS Network Analyst Erweiterung erstellt werden, dienen häufig als Eingabe für umfangreichere Analysen. Bei Vorhersagen des Reiseverhaltens werden z. B. in vielen Fällen die Entfernungen verwendet, die Personen zum Erreichen bestimmter Reiseziele zurücklegen müssen. Diese Netzwerkentfernungen werden in mathematischen Ausdrücken angewendet, um Vorhersagen für Reisen treffen zu können.

Download In State Plane Projection Here. ** The Street Centerline feature class now follows the NG911/State of Illinois data specifications including a StreetNameAlias table. The download hyperlink above also contains a full network topology for use with the Esri Network Analyst extension ** These street centerlines were developed for a myriad of uses including E-911, as a cartographic base, and for use in spatial analysis. This coverage should include all public and selected private roads within Lake County, Illinois. Roads are initially entered using recorded documents and then later adjusted using current aerial photography. This dataset should satisfy National Map Accuracy Standards for a 1:1200 product. These centerlines have been provided to the United States Census Bureau and were used to conflate the TIGER road features for Lake County. The Census Bureau evaluated these centerlines and, based on field survey of 109 intersections, determined that there is a 95% confidence level that the coordinate positions in the centerline dataset fall within 1.9 meters of their true ground position. The fields PRE_DIR, ST_NAME, ST_TYPE and SUF_DIR are formatted according to United States Postal Service standards. Update Frequency: This dataset is updated on a weekly basis.

InputData DirectoryThis network dataset is an example of a network to which paths from other networks (i.e. Networks A and B) can be compared.Contains two directories:a) NetworkCb) NetworkPaths'NetworkC' Directory- This network is based upon a subset of the Missouri Department of Transportation (MoDOT) July 2016 road dataset listed in the references.- NetworkC contains an ESRI .gdb (NetworkCdata.gdb) in which the arcs and nodes for Network C can be found as well as an ArcGIS ND Network Analyst configuration file. - Featuredataset: NetworkCsub - Network arcs: NetworkCsub - Network file: NetworkCsub_ND - Network junctions: NetworkCsub_ND_Junctions'NetworkPaths' contains ESRI .gdbs representing:a) A collection of routes between OD pairs in each network (InputPaths.gdb) - The densified routes used in the application (densified at 10m): (Net_A_routelines; Net_B_routelines; Net_C_routelines) - The original routes with original set of vertices (non densified): (Net_A_routes; Net_B_routes; Net_C_routes)b) The origin and destination points for the paths (ODNodes.gdb) - These were used to generate the shortest paths for each network, serving as the paths to be compared - origins: originLocations - destinations: destinationLocations_'OutputData' DirectoryContains the comparisons of paths to networks:NetAToB: comparison of paths from network A to network BNetAToC: comparison of paths from network A to network CNetBToA: comparison of paths from network B to network ANetBToC: comparison of paths from network B to network CNetCToA: comparison of paths from network C to network ANetCToB: comparison of paths from network C to network BInside each directory is a collection of ESRI .gdb which contains the individual paths used in the analysis as inputa) NetworkAPaths.gdbb) NetworkBPaths.gdbc) NetworkCPaths.gdbInside each directory is a collection of ESRI .gdb which contains the vertices of the individual paths used in the analysis as inputa) NetworkAPathPoints.gdbb) NetworkBPathPoints.gdbc) NetworkCPathPoints.gdbAlso included is a collection of ESRI .gdb that represent the original path nodes that could be assigned to the comparison network. In this case, only nodes that were within 20m of the comparison network could be assigned. Each path node is attributed with the distance to its counterpart node in the comparison. a) Nodes in Network A paths assigned to Network B (PathANodesAssignedtoNetB.gdb)b) Nodes in Network A paths assigned to Network C (PathANodesAssignedtoNetC.gdb)c) Nodes in Network B paths assigned to Network A (PathBNodesAssignedtoNetA.gdb)d) Nodes in Network B paths assigned to Network C (PathBNodesAssignedtoNetC.gdb)e) Nodes in Network C paths assigned to Network A (PathCNodesAssignedtoNetA.gdb)f) Nodes in Network C paths assigned to Network B (PathCNodesAssignedtoNetB.gdb)Inside each directory is a collection of ESRI .gdb which contain solutions to the SCPPOD with the following naming convention:a) comparing paths in Network A to Network B SCCPODarcsPathAtoNetB.gdb for arc elements and SCCPODnodesPathAtoNetB.gdb for node elements) - The naming convention for the node solutions for path id X is ('SN_routeX_X') - The naming convention for the arc solutions for path id X is ('routX_Rt' for single polyline counterpart path; and 'routeX_Rtsplit' for a polyline representation of the counterpart path based upon the SCPPOD node output).b) comparing paths in Network A to Network C SCCPODarcsPathAtoNetC.gdb for arc elements and SCCPODnodesPathAtoNetC.gdb for node elements)c) comparing paths in Network B to Network A SCCPODarcsPathBtoNetA.gdb for arc elements and SCCPODnodesPathBtoNetA.gdb for node elements)d) comparing paths in Network B to Network C SCCPODarcsPathBtoNetC.gdb for arc elements and SCCPODnodesPathBtoNetC.gdb for node elements)e) comparing paths in Network C to Network A SCCPODarcsPathCtoNetA.gdb for arc elements and SCCPODnodesPathCtoNetA.gdb for node elements)f) comparing paths in Network C to Network B SCCPODarcsPathCtoNetB.gdb for arc elements and SCCPODnodesPathCtoNetB.gdb for node elements)The counterpart paths that were identified were then linked to the full network C to summarize the frequency with with arcs were associated with paths - Can be found in: 1. PathARepresentationinNetC.gdb 2. PathARepresentationinNetC.gdb - important attributes: a) vcntarc: number of paths utilizing arc b) ptCnt: number of path vertices associated with each arc c) AvgDist: average distance of path vertices from network arcs d) MinDist: minimum distance of path vertices from network arcs e) MaxDist: minimum distance of path vertices from network arcs

ArcGIS tool and tutorial to convert the shapefiles into network format. The latest version of the tool is available at http://csun.uic.edu/codes/GISF2E.htmlUpdate: we now have added QGIS and python tools. To download them and learn more, visit http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

INFP, CRMD and UCL have developed a framework capable of analyzing the implications of natural hazards on transportation networks, also in a time-dependent manner. This is currently embedded into an ArcGIS toolbox entitled Network-risk, which has been successfully tested for Bucharest, contributing to an insightful evaluation of emergency intervention times for ambulances and firefighters, in the case of an earthquake. The files and the user manual allow a replication of our recent analysis in Toma-Danila et al. (2022) and a download of results (such as affected roads and unaccesible areas in Bucharest), in various formats. Some of the results are also presented in an ArcGIS Online app, called "Riscul seismic al Bucurestiului" (The seismic risk of Bucharest), available at https://tinyurl.com/yt32aeyx. In the files you can find: - the Bucharest road network used in the article; - facilities for Bucharest and Ilfov, such as hospitals, firestations, buildings with seismic risk or tramway lines accesible by emergency vehicles - results of the analysis: unaccesible roads and areas, service areas around facilities, closest facilities for representative points - Excel calculator for Z elevation from OpenStreetMap data - the user manual and a ArcGIS toolbox.

Main citation: - Toma-Danila D., Tiganescu A., D'Ayala D., Armas I., Sun L. (2022) Time-Dependent Framework for Analyzing Emergency Intervention Travel Times and Risk Implications due to Earthquakes. Bucharest Case Study. Frontiers in Earth Science, https://doi.org/10.3389/feart.2022.834052

Previous references: - Toma-Danila D., Armas I., Tiganescu A. (2020) Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania. Natural Hazards and Earth System Sciences, 20(5): 1421-1439, https://doi.org/10.5194/nhess-20-1421-2020 - Toma-Danila D. (2018) A GIS framework for evaluating the implications of urban road network failure due to earthquakes: Bucharest (Romania) case study. Natural Hazards, 93, 97-111, https://link.springer.com/article/10.1007/s11069-017-3069-y

The Street layer contains all streets, roads, drives and highways for Sarasota County. The layer is segmented by subtype, speed limit, address range, and maintenance entity. The layer can support both ESRI Network Analyst datasets and Address Locators.

This dataset contains a simplified network representation of bike paths across City of Melbourne. The dataset can be used to create a digital bicycle network with route modelling capabilities that integrated existing bicycle infrastructure. The network has been created to be used with ArcGIS network analyst. The resulting network was connected to the City of Melbourne property layer through centroids created for this project: The network can assist in multiple modelling tasks including catchment analysis and route analysis. The download is a zip file containing compressed .json files Please see the metadata attached for further information.

To calculate the California’s Proposed Network Standards on the Potential MediCAL Population DHCS used the Network Analysis Tool from ESRI OD Cost Matrix.

This data contains general information about Pedestrian Network in Hong Kong. Pedestrian Network is a set of 3D line features derived from road features and road furniture from Lands Department and Transport Department. A number of attributes are associated with the pedestrian network such as spatially related street names. Besides, the pedestrian network includes information like wheelchair accessibility and obstacles to facilitate the digital inclusion for the needy. Please refer to this video to learn how to use 3D Pedestrian Network Dataset in ArcGIS Pro to facilitate your transportation analysis.The data was provided in the formats of JSON, GML and GDB by Lands Department and downloaded via GEODATA.GOV.HK website.

The original data files were processed and converted into an Esri file geodatabase. Wheelchair accessibility, escalator/lift, staircase walking speed and street gradient were used to create and build a network dataset in order to demonstrate basic functions for pedestrian network and routing analysis in ArcMap and ArcGIS Pro. There are other tables and feature classes in the file geodatabase but they are not included in the network dataset, users have to consider the use of information based on their requirements and make necessary configurations. The coordinate system of this dataset is Hong Kong 1980 Grid.

The objectives of uploading the network dataset to ArcGIS Online platform are to facilitate our Hong Kong ArcGIS users to utilize the data in a spatial ready format and save their data conversion effort.

For details about the schema and information about the content and relationship of the data, please refer to the data dictionary provided by Lands Department at https://geodata.gov.hk/gs/download-datadict/201eaaee-47d6-42d0-ac81-19a430f63952.

For details about the data, source format and terms of conditions of usage, please refer to the website of GEODATA STORE at https://geodata.gov.hk.Dataset last updated on: 2022 Oct

The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making.

   BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions.


   Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself.


   For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise.


   Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. 


   This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery.


   See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt


   See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

Inspired by "Add GTFS to a Network Dataset" tool by Melinda Morang, I have generated this tool to use GTFS public transit data in ArcGIS so you can run schedule-aware analyses without using the Network Analyst.

The abundant access is the first in series of tools I am developing for ArcGIS to analyse the GTFS data. Simplicity is the main objective here, therefore all the analysis will be done in-fly.

The term "abundant access" is borrowed from Jarrett Walker's book, Human transit. You can use the abundant access to perform transit/pedestrian accessibility analyses, controlling for the number of transfers, walking between transfers, walking to transit and walking from transit. My aim is to develop a method that is useful for practitioners and decision-makers to make day-to-day decisions.

Note: No installation is necessary. This tool is only available for ArcGIS 10.4 or higher. It also works with ArcGIS Pro. This tool is still under development so please feel free to contact me if you encounter bugs or other problems or you simply have ideas or suggestions.For more information and updates, visit www.spatialanalyst.ir.

Please see the Data Summary sheet on MDOT's website: https://www.mdot.maryland.gov/OPCP/MDOT_Walksheds_Summary_Sheet.pdfThese walkshed areas were built in ESRI Network Analyst using jurisdictional sidewalk and trail data (hand-digitized as needed) and state roadway centerline data. Roadways were restricted to only allow travel along those suitable for pedestrians. (This is a hosted feature view).The network modeling uses actual station entrance/exit locations and covers a one-half mile walking distance.

** The Street Centerline feature class now follows the NG911/State of Illinois data specifications including a StreetNameAlias table. The download hyperlink above also contains a full network topology for use with the Esri Network Analyst extension ** These street centerlines were developed for a myriad of uses including E-911, as a cartographic base, and for use in spatial analysis. This coverage should include all public and selected private roads within Lake County, Illinois. Roads are initially entered using recorded documents and then later adjusted using current aerial photography. This dataset should satisfy National Map Accuracy Standards for a 1:1200 product. These centerlines have been provided to the United States Census Bureau and were used to conflate the TIGER road features for Lake County. The Census Bureau evaluated these centerlines and, based on field survey of 109 intersections, determined that there is a 95% confidence level that the coordinate positions in the centerline dataset fall within 1.9 meters of their true ground position. The fields PRE_DIR, ST_NAME, ST_TYPE and SUF_DIR are formatted according to United States Postal Service standards. Update Frequency: This dataset is updated on a weekly basis.

Polygons showing road miles from roadway intersected points to the URL in 5, 10, 15, 20, and 25 mile increments for San Luis Obispo County.

This data was created using the "Calculate Service Area" function in the Network Analyst Extension and available ESRI Road Network. The Service Area function requires points so points were generated by intersecting the URL boundary with the road network.

The Coordinates for this dataset are State Plane Coordinate System, Zone 5, NAD 1983 Feet.

Criteria and weights for time intervals of the accessibility of social services being evaluated using TOPSIS.