M9. COLOURING LEBANON - colouring-cities/manual GitHub Wiki

colouring beirut

Colouring Beirut was the first platform to reproduce Colouring London code. The site is temporarily unable to be activated owing to problems affecting Lebanon as a whole.

Academic institution/department or academic consortium

The American University of Beirut. Urban Lab

Host link


National research institution verification link


City/Cities selected for initial testing


Platform link

Awaiting relaunch April 27th 2023 at the Women in Data Science Conference 2023 hosted by AUB

Social media links

Please add

Articles, publications and events links

Please add to the group pagehere

CCRP membership start date

Involvement in Colouring London from 2019

Anticipated launch date

  • Demonstration model: Launched 2019 but currently paused owing to resource shortages in Beirut
  • National rollout: Not known

Academic Team

(Please record significant contributions adding from/to date where appliacble)**

  • Principal Investigator: Dr Sara Najem

Multidisciplinary expertise

Urban analytics, machine learning, urban infrastructure risk and resilience analysis, mathematics of cities, physics

Key Collaborators

National Center for Remote Sensing (CNRS) of the Conseil National de Recherche Scientifique (CNRS-Lebanon)

Additional partners, advisors and consultees



Grant 1: Date (from/to)

  • Amount:
  • Funder: American University of Beirut
  • Purpose:

Open building footprint source

Description of footprint source, any restrictions, plans for updating, level of accuracy, issues arising etc

Primary research interest/s in reproduction of platform code

Secondary research interest/s for reproduction of platform code

What are the most useful aspects of the Colouring Cities Research Programme for you?

What are the greatest challenges you anticipate during platform set up e.g. open footprint access, engineering support funding etc?

What could we add/do that would be of use? (e.g add features, new data categories, joint papers, joint funding applications etc.

Key Advisors and consultees

Colouring Lebanon/Beirut citations, articles etc.

Relevant publications by academic team

Krayem, Alaa, Aram Yeretzian, Ghaleb Faour, and Sara Najem. ‘Machine Learning for Buildings’ Characterization and Power-Law Recovery of Urban Metrics.’ PLOS ONE 16, no. 1 (January 28, 2021): e0246096.

Plan of action 2022


Please add all publicity/publication links here