TRIPI: A global dataset of the total resources in our roads, rail, and parking

This post was prepared by Martijn van Engelenburg, based on his research work with his colleagues at Leiden University Sebastiaan Deetman, Tomer Fishman, Paul Behrens and Ester van der Voet

It is known that global infrastructure is one of the most material-consuming sectors of the world. What is less known is where these materials exactly end up. With the publication of our data article on global transportation infrastructure. We want to give access to everyone interested in infrastructure to this data. In this blog, we explain briefly what’s in the database, and we hope this will be useful in your work or research.

What is in TRIPI?

There’s data on most major construction materials such as steel, concrete, asphalt and aggregates in road, rail and parking infrastructure with more coverage than has been previously possible. We’ve done this by extracting highly detailed data from OpenStreetMaps and filling in the data gaps with the help of disaster.ninja. Resulting in a database where most roads and railways of the world are represented, and with the codebase we provide it is possible to extract data for your region of choice. But what might be most convenient is that for 175 countries and regions, we have prepared this data in easy-to-use Excel files available on our GitHub.

 

A stepping stone for circular measures

With TRIPI we want to have a solid foundation on which we can base future scenarios where we explore the potential of circularity measures reducing material demand for infrastructure. As there is still a  growing demand for new roads and maintenance demand for infrastructure is demanding more materials in developed countries, we see a high need for more circular strategies in infrastructure. This is what we will continue working on within CIRCOMOD.

Get in touch

With the publication of TRIPI we provide a good baseline for transportation infrastructure. But as always more data is needed. Reach out if you have ideas for improvement or want to collaborate!

You can find the Data in Brief paper here: https://www.sciencedirect.com/science/article/pii/S2352340924003561

And the TRIPI github here:

https://github.com/MvEngelenburg/TRIPI/tree/main

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