M9. COLOURING LEBANON - colouring-cities/manual GitHub Wiki
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
xx
City/Cities selected for initial testing
Beirut
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
xx
Funding
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.