Transport Data

Kenya - Infrastructure assessment for health facilities

Description: 

Health facilities in Kenya were acquired from a local consultant through the KEMRI Wellcome Trust Research Programme. These facilities were used to assess hospital preparedness based on available infrastructure data (GSM coverage, electrification, access (drive time)) and demographics (population and vulnerability to CoVID). Additionally summary statistics were generated at the ward level.

Type: 
Geospatial

Hanoi, Vietnam - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification for Hanoi, Vietnam. Contains GTFS files for morning (AM), midday (MD) and afternoon (PM).

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications

Type: 
Geospatial

Harare, Zimbabwe - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) file for Harare. Includes GTFS for Kombis and City Shuttle. Data feed from 2017-2020.

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications

Type: 
Geospatial

Accra, Ghana - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) for Accra, Ghana. The information included in this data was collected in May and June of 2015 as part of a data collection campaign on Accra’s transport.

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications

Type: 
Geospatial

Douala, Cameroon - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) files for Douala, Cameroon covering Yellow Taxis and Socatur Bus. Feed was from 2017 - 2020.

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications.

Type: 
Geospatial

Sao Paulo, Brazil - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) for Sao Paulo.
Contains data from EMTU (Metropolitan Bus System). Data included in the download file is for 2017. See the link to original data sources for latest data.

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications.

Type: 
Geospatial

Porto Alegre, Brazil - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) file for Portlo Alegre

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications

Type: 
Geospatial

Belo Horizonte, Brazil - General Transit Feed Specification (GTFS)

Description: 

General Transit Feed Specification (GTFS) file for Belo Horizonte in Brazil.
The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data in a format that can be consumed by a wide variety of software applications

Type: 
Geospatial

Argentina - Road Network (primary, secondary and tertiary roads)

Description: 

Argentina road network shapefiles with basic attributes for primary (national), secondary (province) and tertiary (rural) roads. Data derived from datasets provided by Argentina’s Ministry of Transport and National’s Road Directorate, modified by cleaning and ensuring compatibility across data files.

Type: 
Geospatial

Argentina - Rail Network

Description: 

Shapefiles for rail network in Argentina (nodes and lines) with basic attributes including station and line names, operator and line length.
Derived from Argentina’s Ministry of Transport and National’s Road Directorate dataset (cleaned and compatibilized to be simultaneously used).

Type: 
Geospatial

Global Airports

Description: 

Airport locations were extracted and mapped from a repository of air traffic flow, and international airports were extracted. Airports were attributed with total seats from the most recent year reported; most recent year for any airport is 2019. Licensing rectrictions means we cannot define the year of reported flows, but the data can be used and disseminated as needed.

Type: 
Geospatial

Djibouti Public Transport Routes

Description: 

The following surveys were carried out:
• GIS mapping of bus routes, carried out by survey staff travelling bus routes with GPS enabled phones, using GPS Essantials

The objective of these surveys was to develop a comprehensive picture of the urban transport sector, including, on the supply side, the financing and provision of vehicles and the incomes in the sector, and on the demand side, the needs of passengers and identification of the level of the number of passengers on different routes.
The first phase of data gathering was in May 2019. This was entirely within...

Type: 
Geospatial

Kigoma (Tanzania) - Transport Infrastructure (ESA EO4SD-Urban)

Description: 

The Transport Infrastructure information product shows the classification of three road types: Arterial Roads, Collector Roads and Local Roads. The Transport Infrastructure dataset is based on Very High Resolution (VHR) satellite imagery (Quickbird-2 (2005)) / Pleiades (2016) by means of manual classification processing techniques.

Type: 
Geospatial

Karachi (Pakistan) - Transport Network (ESA EO4SD-Urban)

Description: 

The products over Karachi (Pakistan) contain spatial explicit information about the transport network and nodes within the transport network and their typology as identified from Open Street Map and updated by interpretation of VHR satellite imagery. The level of detail for the classification scheme mainly relies on the input data sources.

Type: 
Geospatial

Fallujah (Iraq) - Transport Network (ESA EO4SD-Urban)

Description: 

The product over Fallujah (Iraq) contains spatial explicit information about the transport network and nodes within the transport network and their typology as identified from Open Street Map and updated by interpretation of VHR satellite imagery. The level of detail for the classification scheme mainly relies on the input data sources.

Type: 
Geospatial

Mbeya (Tanzania) - Transport Infrastructure (ESA EO4SD-Urban)

Description: 

The Transport Infrastructure information product shows the classification of three road types: Arterial Roads, Collector Roads and Local Roads. The Transport Infrastructure dataset is based on Very High Resolution (VHR) satellite imagery (Quickbird-2 (2004)) / (Worldview-2, GeoEye-1 (2015, 2017)) by means of manual classification processing techniques

Type: 
Geospatial

Mtwara (Tanzania) - Transport Infrastructure (ESA EO4SD-Urban)

Description: 

The Transport Infrastructure information product shows the classification of three road types: Arterial Roads, Collector Roads and Local Roads. The Transport Infrastructure dataset is based on Very High Resolution (VHR) satellite imagery (Quickbird-2 (2008) / Worldview-2: 2017) ) by means of manual classification processing techniques.

Type: 
Geospatial

Dodoma (Tanzania) - Transport Infrastructure (ESA EO4SD-Urban)

Description: 

The Transport Infrastructure information products show the classification of three road types: Arterial Roads, Collector Roads and Local Roads. The Transport Infrastructure datasets are based on Very High Resolution (VHR) satellite imagery (Quickbird-2 (2006, 2009) and Pleiades (2016)) by means of manual classification processing techniques.

Type: 
Geospatial

Mwanza (Tanzania) - Transport Infrastructure (ESA EO4SD-Urban)

Description: 

The Transport Infrastructure information product shows the classification of three road types: Arterial Roads, Collector Roads and Local Roads. The Transport Infrastructure dataset is based on Very High Resolution (VHR) satellite imagery (Quickbird-2 (2005)) / (Pleiades, GeoEye-1 (2015, 2010)) by means of manual classification processing techniques

Type: 
Geospatial