Annex and Method Notes
Below is a brief summary of various methods used in the analysis. For further detail, see the method note.
In order to understand the impact of the blast, up to date population figures are required. In absence of a census, we used Facebook Data for Good World Population dataset, which is generated in collaboration with the Center for International Earth Science Information Network (CIESIN). The population figures are available at the country level, at the sub-regional level, and, most importantly, at the neighborhood level.
The dataset provided the population density for the whole of Lebanon in a gridded format. This was processed into usable data points, which were then overlaid against the boundaries of municipal Beirut. These data points were first aggregated against municipal Beirut’s official administrative boundaries. These points were also calculated against boundaries derived from the natural clusters of neighborhoods found within the city to juxtapose the population distribution.
The urban morphology aims to understand how neighborhoods in Beirut are structured. To derive these neighborhoods, the city’s road network was taken into consideration. Here, open-source data from OpenStreetMap was used to allow reproducibility of the results. Areas that contain a high density of road intersections within a specified distance were considered as individual neighborhoods. This allows the city to be divided into a way that may be considered more true to Beirutis’ lived- experience.
With the understanding of Beirut’s population distribution, we look at how equitable essential urban facilities are distributed within the city. In particular, the ease of reach to health and education facilities are taken into account with respect to the average time required for Beirutis to walk to any given facility. The proportion of Beirutis required to walk more than 10 minutes to a hospital or school was taken to better understand the equity of distribution of these facilities. Subsequently, a spatial interaction model was formulated to understand the movement of populations within the city to take into account the size (and, therefore, attractiveness) of different hospitals. This model allows to estimate areas within Beirut that attract the most commuters, with the highest flows considered more accessible.
Leave No One Behind (LNOB)
The LNOB presents the results of a qualitative study consisting of desk reviews and field observations, which included interviews with inhabitants and discussions with local and international NGOs.
|A process that is people-centered and data-driven, rather than building-centered and reconstruction-based; thus, a process that secures temporary shelters, safe spaces, and essential infrastructural and health services for multiple categories ofvulnerable groups;|
|A process that prioritizes keeping-in-place dwellers and businesses, and seeks to reverse/mitigate inequalities that have displaced many inhabitants; thus, a process that directly addresses property tenure matters in ways that address the needs ofboth landlords and tenants;|
|A process that identifies the institutional frameworks that produce inequalities and vulnerabilities, and that seeks to change them or mitigate their impacts on the variety of vulnerable groups they target; A process that recognizes and tackles theextreme and structural gender inequalities in Lebanon;|
|A process that identifies the barriers to return from the perspective of each of the social groups and addresses them effectively; accordingly, participatory decision-making mechanisms must be put in place and include members of the concerned social groupsthey want to affect;|
|A process that is centered on human rights, that focuses on identifying and analyzing the needs of rights holders, and the obligations of duty bearers - whether local, national orinternational - to ensure respect, protection and fulfillment of these rights;|
|A process that is grounded in accountability; articulated around mechanisms that monitor and ensure that the most vulnerable are in fact benefitting from recovery interventions; that guarantees that judicial and non-judicial recourses for rights violations are accessibleand effective;|
|A process that is national in scale and not just Beirut centric, that takes into account the high levels of uneven geographical development of Lebanon and is informed from mistakes in earlier recovery experiences; in other words, a process that represents a oncein a generation opportunity to lay the groundworks for a more inclusive and just Lebanon|
Page 38-39 Leave No One Behind UNDP report 2020
Further to the framework described above, the report presents results of a qualitative study consisting of desk reviews and field observations, which included interviews with inhabitants and discussions with local and international NGOs.
Key vulnerabilities identified in the report:
- Unemployment - 32% of the Lebanese workforce is jobless (May 2020) which has implication on furthering brain drain and no support for remaining talent
- Income status- 86% of households in Greater Beirut rely on less than $1.33 per day
- Insecure tenancy contracts - Tenants often remain in structurally unsound homes due to fear of losing old rent contracts, while some landlords evicted tenants out of fear of not receiving aid
- Risk of no or little compensation - Unlikely insurance compensation is leaving many owners unable to pay for repairs
- Affordability of necessities - Devaluation of the currency coupled with constrained supply of building materials exacerbates people’s inability to afford rehabilitation and living expenses
- Insecure housing options - Crowding, which could exacerbate COVID risks and has been shown to increase gender based violence
- Access to support networks - Households without access to support networks, such as migrant groups or refugees, have fewer options to lean on
- Gender - Lebanon ranks 145 / 153 in the WEF Gender Equality Index, a score that is likely to deteriorate as women are more likely to be unemployed, lack social protection, have no legal residence or adequate shelter, making them less resilient to shocks
- Legal status - Livelihoods of migrants and refugees have significantly deteriorated in recent months; for example, the Karantina public hospital, one of the few health care institutions that catered to these groups, was destroyed from the blast and has since been prioritised by UNDP Lebanon to receive support for rehabilitation
- Youth and children - Up to 100,000 children were directly affected by the blast, compounding existing traumas and vulnerabilities caused by parallel economic and health crises.
- Elderly - The currency devaluation has slashed savings while the lack of social security and reduced employability have left many elderly individuals without financial means or support
- LGBTIQ+ - The neighborhoods closest to the blast also has some of the safest spaces for the LGBTIQ+ community, many of whom were displaced as a result of the explosion
- People with physical or mental disabilities
- People with mental illness and PTSDs
|Data scientists commissioned; producing MVI and report findings using different spatial data processing techniques such as population analysis, urban morphology, and accessibility analysis.|
Melda is a doctoral researcher at the Centre for Advanced Spatial Analysis, UCL, London and the co-founder of Open Map Lebanon and. Her research is focused on extracting economic insights from satellite data. Melda is also a consultant at the World Bank where she’s been assessing global population exposure to flood risk. She’s also involved with ColouringLondon.org, a crowdsourcing project to get data on the urban built environment. Previously, Melda was a management consultant at Monitor Deloitte Middle East. She has a BA in Economics (Wellesley College), an MSc in Urban Economic Development (UCL), and an MRes in Spatial Data Science and Visualization (UCL).
Matthew is a postdoctoral researcher specialising in spatial data science at the City Futures Research Centre, University of New South Wales. He specialises in modelling urban processes and dynamics, as well as network analysis. His interests lie in the intersection of spatial data and its application in policy design and recommendations for the science of cities. He has worked in providing data analytics services and consultancy for several NGOs and national administrations. He has a BSc (Hons) in Biology. He obtained his doctorate from The Bartlett's Centre for Advanced Spatial Analysis at University College London.
SEIA design and MVI outline;
Webpage Production Specialist
Head of Solutions Mapping, UNDP Lebanon Accelerator Lab