wb_transportdata

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

Dhaka (Bangladesh) - Transport Network (ESA EO4SD-Urban)

Description: 

The product over Dhaka (Bangladesh) contains spatial explicit information about the transport network and nodes within the transport network and its 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

Ramadi (Iraq) - Transport network Maps (ESA EO4SD-Urban)

Description: 

The product over Ramadi (Iraq) contains spatial explicit information about the nodes within the transport network and its 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

Tanga (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 (2007 / 2018)) by means of manual classification processing techniques.

Type: 
Geospatial

Bamako (Mali) - Transportation Network (ESA EO4SD-Urban)

Description: 

Transportation network - nodes and network products over Bamako (Mali) contain spatial explicit information transport network nodes and network 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

Arusha (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) and Worldview-2, GeoEye-1 (2015, 2016)) by means of manual classification processing techniques.

Type: 
Geospatial

Semarang (Indonesia) - 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 in 2006 and 2015. The Transport Infrastructure dataset is based on Very High Resolution (VHR) satellite imagery (QuickBird-2 (2006, 2008) and Pleiades (2015)) by means of manual classification processing techniques.

Type: 
Geospatial

Saint Louis (Senegal) - Transport Network Map (ESA EO4SD-Urban)

Description: 

The product over Saint Louis (Senegal) contains spatial explicit information about transport network and its 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

Denpasar (Indonesia) - 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 and WorldView-2: 2017) by means of manual classification processing techniques.

Type: 
Geospatial

Dakar (Senegal) - Transport Network Maps (ESA EO4SD-Urban)

Description: 

The product over Dakar (Senegal) contains spatial explicit information about transport network and its 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

Abidjan (Ivory Coast) - Transport Network 2005 & 2018 Maps (ESA EO4SD-Urban)

Description: 

The product over Abidjan (Ivory Coast) contains spatial explicit information about transport network and its 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

Afghanistan - Road Network

Description: 

The dataset provides existing and planned road infrastructure in Afghanistan. Data Source: The World Bank Group. Open Street Maps have been used as a complementary source. Latest update: 2012 Comment: Many of the roads that are characterized as under construction, or planned, may now be completed.

Type: 
Other

BRI Database, Reed and Trubetskoy 2019

Description: 

Replication files and instructions for Reed, Tristan; Trubetskoy, Alexandr. 2019. Assessing the Value of Market Access from Belt and Road Projects (English). Policy Research working paper; no. WPS 8815.

Type: 
Other

Democratic Republic Congo (COD) - Transportation Prices (2016)

Description: 

This dataset is the result of a geospatial model that simulates how individuals and traded goods are moved in COD, taking both roads and navigable rivers into account. The Highway Development and Management Model was used to estimate the cost of the road network. The points of origin for the analysis were created by dividing the territory into more than 27,000 cells of approximately 10 kilometers on a side and estimating their centroid. Then, transport cost to the local market was estimated by calculating every possible transport route from every cell centroid to every possible market, and...

Type: 
Geospatial

GRIP (Global Roads Inventory Dataset) -2018: Road Density

Description: 

The Global Roads Inventory Project is a harmonized global dataset of aproximately 60 geospatial datasets on road infrastructure. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets.

The road density raster layers (road length per unit of area) are produced at a resolution of 5 arcminutes (approximately 8×8km at the equator). The road vector dataset was overlaid with a global 5 arcminute 'fishnet' vector dataset with unique cell identifiers...

Type: 
Geospatial

GRIP (Global Roads Inventory Project) - 2018

Description: 

The Global Roads Inventory Project is a harmonized global dataset of aproximately 60 geospatial datasets on road infrastructure. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets.
This dataset is split into 5 road types: highways/ primary/ secondary/ tertiary/ local roads

For more information, please visit:
http://www.globio.info/download-grip-dataset
...

Type: 
Geospatial

Belt and Road Initiative Trade Costs Database

Description: 

This paper studies the impact of transport infrastructure projects of the Belt and Road Initiative on shipment times and trade costs. Based on a new data on completed and planned Belt and Road transport projects, Geographic Information System analysis is used to estimate shipment times before and after the Belt and Road Initiative. Two sets of data are computed to address different research questions: a global database based on an analysis of 1,000 cities in 191 countries and 47 sectors and a regional database that focuses on more granular information (1,818 cities) for Belt and Road...

Type: 
Other