Lebanon

Data as of June 11, 2015. The "Syria Border Crossings" dataset contains verified data about the geographic location (point geometry) and name of border crossings for Syria. Compiled by the U.S. Department of State, Humanitarian Information Unit (https://hiu.state.gov/), each attribute in the dataset is verified against multiple sources. Locations are only accurate down to the city level. The data contained herein is entirely unclassified and is current as of 16 April 2015. The data is updated as needed. This dataset is primarily hosted on the State GeoNode, the open geographic data platform of the U.S. Department of State.

InterAction is an alliance of international NGOs, all working to make the world a more peaceful, just, and prosperous place. NGO Aid Map highlights the work of InterAction Member NGOs around the globe.

This dataset contains historical data from WHO's data portal.

This dataset contains data from WHO's data portal covering the following categories: Air pollution, Antimicrobial resistance (AMR), Assistive technology, Child mortality, Dementia diagnosis, treatment and care, Dementia policy and legislation, Environment and health, Foodborne Diseases Estimates, Global Dementia Observatory (GDO), Global Health Estimates: Life expectancy and leading causes of death and disability, Global Information System on Alcohol and Health, HIV, Health Inequality Monitor, Health financing, Health systems, Health taxes, Health workforce, Hepatitis, Immunization coverage and vaccine-preventable diseases, International Health Regulations (2005) monitoring framework, Malaria, Maternal and reproductive health, Mental health, Neglected tropical diseases, Noncommunicable diseases, Nutrition, Oral Health, Priority health technologies, Resources for Substance Use Disorders, Road Safety, SDG Target 3.8 | Achieve universal health coverage (UHC), Sexually Transmitted Infections, Tobacco control, Tuberculosis, Vaccine-preventable communicable diseases, Violence against women, Violence prevention, Water, sanitation and hygiene (WASH), Women and health, World Health Statistics. For links to individual indicator metadata, see resource descriptions.

Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

This is the underlying data for a manuscript published in the Journal of Diabetes & Metabolic Disorders (DOI : 10.1007/s40200-020-00638-6). The manuscript presents findings from a 2015 survey of Syrian refugees and Lebanese host communities to characterize care-seeking, health service utilization and spending, and medication prescribing and adherence for hypertension and diabetes.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

UNOSAT code: FR20191016LBN This map illustrates satellite-detected fire hotspots based on the analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) accessed via NASA FIRMS, between October 15-16, 2019. 30 hotspots were detected in Lebanon and 121 hotspots were detected in three analysed Governorates (i.e. Homs, Lattakia and Tartous) in Syria. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Al-Haffa and Al-Qardaha Districts, Lattakia Governorate, Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 433 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Akkar, Tartous and Homs Governorates, in Lebanon and Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 549 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Aley and Chouf districts, in Lebanon, based on SPOT-6 imagery acquired on 19 October 2019. Approximately 1275 ha of potentially burned areas were detected by Copernicus-EMS as of 17 October 2019 (orange) and additional 92 ha of burned were detected by UNOSAT as of 19 October 2019 (red), which is equivalent to approximately 7% increase in affected surface area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in South and El Nabatieh Governorates, in Lebanon, based on SPOT-6 imagery acquired on 19 October 2019. Approximately 80 ha of potentially burned area were detected by UNOSAT as of 19 October 2019 (red), This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

This dataset contains agency- and publicly-reported data on sexual violence and abuse against aid workers between January 2015 and December 2017. Please get in touch if you are interested in curated datasets: info@insecurityinsight.org

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

INFORM Lebanon was developed by the Lebanon Joint Analysis Unit, which supports the Resident/Humanitarian Coordinator and is a collaboration of humanitarian, development and governmental partners that supports cross sectoral planning at the national level. INFORM Lebanon is being embedded in regional processes and coordination mechanisms to help all partners quantify and prioritise humanitarian and disaster risks in Lebanon in the context of the regional Syrian Crisis Response.

This dataset presents a list of Localities in Lebanon for the use of humanitarian actors. Central Administration of Statistics. The official governmental institutions for statistics. Cadastral Boundaries: Represent the geographic divisions of Lebanon as per the government. In total Lebanon holds 1623 Cadastral Boundaries. Each boundary could includes 1 or more villages or municipalities; or 1 or more cadastral boundaries could represent one municipality. P_code This column illustrates the agreed codes of the villages in Lebanon as per the UNICEF and UNHCR IM joint work. Location_Name_En This column illustrates the agreed names of the villages in Lebanon as per the UNICEF and UNHCR IM joint work. Location_Name_Arabic This column illustrates the name of the location in arabic based on the "Real estate areas , cities and villages in Lebanon guide" in 2005 from the ACS for the most of the location Latitude, Longitude Geographical Coordinates in Decimal Degrees. Geographical Projection WGS 1984. Elevation This column has the elevation of the location GPS coordinates. Google Webservices was used to populate this field using location GPS coordinates Governorate This column illustrates the Mohafazas (Governorates) as per the Lebanese Government divisions. In total, the no. of Mohafazas is 8. as per decree "522 dated 16/7/2003", in English Governorate_Ar This column illustrates the Mohafazas (Governorates) as per the Lebanese Government divisions. In total, the no. of Mohafazas is 8. as per decree "522 dated 16/7/2003", in Arabic UN_Area Of Operation This column illustrates the Mohafazas (Governorates) in Lebanon as per UNHCR operation areas. Noting that Nabatiyeh and South Lebanon Mohafazas were merged into one Mohafaza that is "South"also for Bekaa and Baalbek-El Hermel Mohafazas were merged into one Mohafaza that is "Bekaa" In total, the no. of Mohafazas as per UNHCR is 5.in English UN_AreaOfOperation_Ar This column illustrates the Mohafazas (Governorates) in Lebanon as per UNHCR divisions. Noting that Nabatiyeh and South Lebanon Mohafazas were merged into one Mohafaza that is "South"also for Bekaa and Baalbek-El Hermel Mohafazas were merged into one Mohafaza that is "Bekaa" In total, the no. of Mohafazas as per UNHCR is 5.in Arabic District This column illustrates the cazas (Districts) in Lebanon as per Lebanese Government divisions. In total, the no. of Cazas amounts for 26. District_Ar This column illustrates the cazas (Districts) in Lebanon as per Lebanese Government divisions. In total, the no. of Cazas amounts for 26. in Arabic CAS_CODE This column illustrates the agreed codes of the cadastral boundaries* in Lebanon as per the Lebanese Government. CAS_CODE_UN This column illustrates the agreed codes of the cadastral boundaries in Lebanon as per the Lebanese Government. The codes holds in its beginning the Lebanese acronyme LBN for international use. CAS_NAME This column illustrates the names of the cadastral boundaries in Lebanon as per the Lebanese Government in English. CAS_NAME_Ar This column illustrates the names of the cadastral boundaries in Lebanon as per the Lebanese Government in Arabic. CAS_MaxElevation This column has the elevation of the highest village in the same cadastral zone Municipality Name_EN This column illustrates the names of the Municipalities in Lebanon in English. Data Source: UNHCR Municipality Name_AR This column illustrates the names of the Municipalities in Lebanon in Arabic. Data Source: UNHCR Municipality Phone This column illustrates the Phone number of the Municipalities in Lebanon. Data Source: MoIM website Municipality Address This column illustrates the Available Address of the Municipalities in Lebanon. Data Source: UNDP/Arabia GIS UNION_ID This column illustrates the codes given for to the union of Municipalities in Lebanon. Data Source: UNHABITAT Union_Full This column illustrates the names of the union of Municipalities in Lebanon in English. Data Source: UNHABITAT UOM_Name This column illustrates the abbreviation name of the union of Municipalities in Lebanon in English. Data Source: UNHABITAT

This is a complete list of all Lebanon public schools and UNRWA schools for Palestine refugees with the geographic coordinates

Lebanon Social Development Centers (SDCs)

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Lebanon 1km Pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00616

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Lebanon 1km Births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00565

This is the underlying data for a manuscript published in PLOS: Currents Disasters (see PDF provided). the manuscript reports results from longitudinal cohort study implemented from January 2015 through August 2016 that sought to evaluate the effectiveness of treatment guidelines and an mHealth application on quality of care and health outcomes for patients with hypertension and type 2 diabetes in primary health care facilities in Lebanon serving Syrian refugees and host communities.

This dataset contains data about the number of people reached with food assistance in emergency settings. The data is collected from external WFP situation reports and emergency dashboards.

List of the Lebanon Secondary Health Care centers