Gender based violence gbv Gazetteer Humanitarian Datasets | Find Crisis Data

Somalia - Subnational Population Statistics

COD 8500+ Downloads

Time Period of the Dataset [?]: January 01, 2005-September 17, 2024 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: COD - Subnational Population Statistics

The United Nations Population Fund (UNFPA) partnered with donors and UN agencies and took up the lead role to support the Somali authorities in undertaking the Population Estimation Survey (PESS) for Somalia in October 2013- March 2014. UNFPA investigated replacement or projection of this dataset in 2021. Only ADM0 (national) data was available. No better alternative is currently available. PESS gathered basic critical information on the Somalis living in urban, rural and nomadic areas (interviewed at water points during the peak of the long, dry season), and in settlements for internally displaced persons. One standard questionnaire was used in selected enumeration areas or pre-identified areas. Data was collected in three main phases: cartographic field mapping, household listing in the sampled areas, and the interviewing of households using the standard questionnaire. PESS report by UNFPA had only the population estimate at regional level (Admin level 1). With the demand to get this data disaggregated to district level to enhance assessment and in particular assessments of people in food insecure by FAO-FSNAU, the district data was interpolated using FSNAU livelihood information embedded in the 2005 UNDP district level population data The data collected in 2024 has now been endorsed for use.

XLSX
CSV

Ukraine Situation Protection Profiling and Monitoring - July - October 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: July 01, 2024-October 31, 2024 ... More

This dataset updates: Never

This dataset presents findings from Protection Profiling and Monitoring conducted by UNHCR and partners between July and October 2024 across Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia. The objective of this regional exercise is to strengthen evidence-based protection responses by regularly collecting and analyzing data on the profiles, protection risks, legal needs, displacement patterns, and basic needs of refugees from Ukraine. Data was gathered through household-level interviews conducted face-to-face at border crossing points, reception and transit centers, collective sites, and assistance locations in major cities. The structured questionnaire was administered by trained enumerators from UNHCR and partner organizations using digital data collection tools. Although respondents were selected to reduce bias, the sample follows a non-probability design and results should be interpreted as indicative rather than statistically representative of the refugee population.

Web App
PDF

Ukraine Situation Protection Profiling and Monitoring - October 2023 - April 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: October 01, 2023-April 30, 2024 ... More

This dataset updates: Never

This dataset presents findings from Protection Profiling and Monitoring conducted by UNHCR and partners between October 2023 and April 2024 across Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia. The objective of this regional exercise is to strengthen evidence-based protection responses by regularly collecting and analyzing data on the demographics, protection risks, legal needs, displacement patterns, and basic needs of refugees from Ukraine. Data was gathered through household-level interviews conducted face-to-face at border crossing points, reception and transit centers, collective sites, and assistance locations in major cities. The structured questionnaire was administered by trained enumerators from UNHCR and partner organizations using digital data collection tools. Although respondents were selected to reduce bias, the sample follows a non-probability design and results should be interpreted as indicative rather than statistically representative of the refugee population.

Web App
PDF

Myanmar - Subnational Administrative Boundaries

OCHA Field Information Services Section (FISS)

COD 1100+ Downloads

Time Period of the Dataset [?]: March 11, 2024-March 31, 2024 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Myanmar administrative level 0-5 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. This COD-AB was most recently reviewed for accuracy and necessary changes in March 2024. The COD-AB requires improvements. Sourced from Myanmar Information Management Unit (MIMU) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Myanmar COD-PS. An edge-matched (COD-EM) version of this COD-AB is available on HDX here. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is ""State/Region"". Administrative level 2 contains 80 feature(s). The normal administrative level 2 feature type is ""District"". Administrative level 3 contains 330 feature(s). The normal administrative level 3 feature type is ""Township"". Administrative level 4 contains 14,174 feature(s). The normal administrative level 4 feature type is ""Town / Village tract"". Recommended cartographic projection: Asia South Albers Equal Area Conic This metadata was last updated on January 9, 2025.

Benin - Subnational Population Statistics

UNFPA

COD+ 2200+ Downloads

Time Period of the Dataset [?]: July 01, 2023-July 31, 2024 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Population Statistics

Benin administrative level 0-2 sex and age disaggregated 2024 projected population statistics REFERENCE YEAR: 2024 These tables are suitable for database or GIS linkage to the Benin - Subnational Administrative Boundaries or the Benin - Subnational Edge-matched Administrative Boundaries layers using the ADM0, ADM1, and ADM2-PCODE fields.

Ecuador - Subnational Administrative Boundaries

OCHA Latin America and the Caribbean (ROLAC)

COD+ 4100+ Downloads

Time Period of the Dataset [?]: May 30, 2017-January 09, 2025 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Ecuador administrative level 0-3 boundaries (COD-AB) dataset. These administrative boundaries were established in: 2017 NOTE: ADM4 feature names are not yet availalble. (Currently ADM4_PCODE is copied into ADM4_ES as a proxy.) No lines layer is yet availalbe. The live geoservices do not reflect the new ADM4 level. This COD-AB was most recently reviewed for accuracy and necessary changes in December 2024. The COD-AB does not require any update. Sourced from INEC - Instituto Nacional de Estadística y Censos Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Ecuador COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 26 feature(s). The normal administrative level 1 feature type is ""currently not known"". Administrative level 2 contains 223 feature(s). The normal administrative level 2 feature type is ""currently not known"". Administrative level 3 contains 1,044 feature(s). The normal administrative level 3 feature type is ""currently not known"". Recommended cartographic projection: South America Albers Equal Area Conic This metadata was last updated on January 9, 2025.

SHP
XLSX

Romania - Socio-Economic Insights Survey (SEIS) - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: May 20, 2024-July 27, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

The 2024 Socio-Economic Insights Survey (SEIS) in Romania is a comprehensive regional assessment conducted from May to July 2024, focusing on the needs of refugees in Romania, particularly those from Ukraine. This multi-sectoral survey aims to capture key data on refugees' socio-economic integration, access to national systems, and their priorities for the coming year, providing valuable insights to inform the 2025 Refugee Response Plan (RRP). The survey employs a stratified random sampling method and involves face-to-face and online interviews with refugees, covering topics such as health, education, protection, food security, and livelihoods. The collected data is anonymized and cleaned for use in policy planning and intervention development. The findings highlight gaps in services and provide crucial information on the changing trends in refugees’ needs, contributing to a more targeted and effective response to refugee challenges in Romania.

Web App
PDF

Czechia - Socio-Economic Insights Survey (SEIS) - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: May 30, 2024-July 14, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

The 2024 SEIS in Czechia provides a comprehensive assessment of the needs and vulnerabilities of refugees from Ukraine. Conducted as part of the annual interagency regional process led by UNHCR, the survey supports the Regional Refugee Response Plan (RRP) for the Ukraine Situation. By addressing key areas such as protection, health, education, shelter, livelihoods, and food security, it delivers essential data to inform evidence-based planning and ensure the diverse needs of refugee groups are met. Data collection took place from May to July 2024 and followed a purposive sampling approach. While not random, the methodology was designed to reflect the geographical and gender distribution of the refugee population using Temporary Protection (TP) data from the Ministry of Interior. Enumerators worked within these parameters, using the snowball method to identify respondents who matched the criteria. The survey was a collaborative effort by UNHCR and the International Organization for Migration. Its findings will inform strategic planning and resource allocation to improve the welfare and resilience of refugees in Czechia.

Web App
PDF

Socio-Economic Insights Survey (SEIS) - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: May 10, 2024-October 29, 2024 ... More

This dataset updates: Never

The 2024 Regional Socio-Economic Insights Survey (SEIS) provides critical data to inform the 2025 Regional Refugee Response Plan (RRP), supporting strategic planning and funding allocation to address regional needs. This consolidated dataset includes comprehensive information from Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia, covering essential topics such as demographics, protection, education, socio-economic inclusion and livelihoods, health, and accommodation. By synthesizing data from these ten countries, the SEIS offers a detailed view of key areas impacting refugee and host communities, supporting evidence-based decisions for targeted interventions and resource mobilization across the region.

Web App
PDF

Congo - Results Monitoring Survey (RMS) - 2023

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: January 17, 2023-February 09, 2023 ... More

This dataset updates: Never

The 2023 Results Monitoring Survey (RMS) in the Republic of Congo aimed to monitor key impact and outcome indicators related to education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation for refugees and asylum seekers. The survey was conducted between January 17 and February 9, 2023, targeting 1,900 households across Brazzaville, Pointe-Noire, Likouala, and Cuvette. The survey achieved interviews with 1,473 households (77.53% coverage), with data collected through Computer-Assisted Personal Interviews (CAPI). The results contribute to an evidence base for UNHCR’s multi-year strategies in the country.

Web App
PDF

Slovakia - Socio-Economic Insights Survey (SEIS) - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: May 21, 2024-July 27, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

The 2024 Socio-Economic Insights Survey (SEIS) in Slovakia provides a comprehensive assessment of the needs and vulnerabilities of refugees from Ukraine. Conducted as part of an annual interagency regional process led by UNHCR, this assessment supports the Regional Refugee Response Plan (RRP) for the Ukraine Situation. Covering topics such as protection, health, education, shelter, livelihoods, and food security, the survey offers critical data to inform evidence-based planning and prioritization, ensuring the specific needs of different refugee groups are addressed. Data collection was conducted through face-to-face interviews from May to July 2024 with a probability-based random sample of refugee households, managed collaboratively by UNHCR and the International Organization for Migration. Findings will guide strategic interventions and resource allocation to enhance the welfare and resilience of the refugee population in Slovakia.

Web App
PDF

South Sudan - Results Monitoring Survey (RMS) - 2022

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: December 01, 2022-January 23, 2023 ... More

This dataset updates: Never

The Results-Monitoring Survey (RMS) was conducted by UNHCR South Sudan in the last quarter of 2022 to serve as a pilot tool for measuring country operations' results regarding internally displaced persons (IDPs). Using computer-assisted personal interviews, around 4,634 questionnaires were carried out proportionally across eight states. The target was IDPs in camps and non-camp settings, including hard-to-reach areas. A simple random sampling method was used to allow generalizability and minimize bias. The questionnaire was tailored to the local context while drawing from the standard RMS instrument. Sample sizes were calculated for states and counties based on displacement figures and partner presence. A 95% confidence level and 5% margin of error determined the state samples. The county samples used 90% confidence and 5% margins given the need for greater precision at lower administrative levels. Total target was 5,309 households, allocated proportionally. High response rate (97%) exceeded targets in some counties. The pilot provides baseline data on results indicators to track over time. Key aspects were representative sampling, localized questionnaire, sufficient sample size, and community access enabling quality data for ongoing monitoring.

Web App
PDF

Mozambique - Results Monitoring Survey (RMS) - 2023

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: February 27, 2023-April 07, 2024 ... More

This dataset updates: Never

The UNHCR Results Monitoring Survey (RMS) in Mozambique, conducted from February 27, 2023, to April 7, 2024, by CS Research and the United Nations High Commissioner for Refugees, assessed the impact in areas such as Health and Nutrition, Water Sanitation Hygiene, Protection, and Education among refugees, asylum-seekers, and IDPs. Covering regions like Cabo Delgado and Nampula, the survey employed mixed sampling methods, including phone surveys (CATI) for widespread geographical coverage, excluding Nampula City and Maratane Camp, and face-to-face interviews (CAPI) in specified areas. This approach, integrating non-probabilistic and probabilistic techniques, and stratified by gender, provided comprehensive data, crucial for UNHCR’s strategic planning and reporting in Mozambique.

PDF
Web App

Poland - Multi-Sector Needs Assessment (MSNA) - 2023

UNHCR - The UN Refugee Agency

10+ Downloads

Time Period of the Dataset [?]: July 13, 2023-August 21, 2023 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

A multi-sectoral needs assessment was conducted in Poland between July 13, 2023 and August 25, 2023, surveying 5,645 households comprising 13,421 individuals. The assessment aimed to capture the needs of refugees in Poland, understand their level of access to basic services, how their needs are currently being met, gaps in services, and priorities for the refugee response in the coming year. Key findings will inform the 2024 Regional Refugee Response Plan for Poland, providing critical data on priorities and funding requirements to support refugees. With 5,645 households surveyed across multiple sectors, the assessment provides a robust evidence base to shape a more effective, responsive refugee program in Poland.

Web App
PDF

Republic of Moldova - Socio-Economic Insights Survey (SEIS) - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: June 02, 2024-July 12, 2024 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

The 2024 Socio-Economic Insights Survey (SEIS) in Moldova, conducted by UNHCR in partnership with REACH, provides essential data on the needs of refugees and third-country nationals displaced from Ukraine. Building on the 2023 Multi-Sectoral Needs Assessment (MSNA), this household-level survey collected insights on protection, food security, education, livelihoods, health, and socio-economic inclusion to inform humanitarian planning and decision-making. A total of 622 in-person interviews were conducted across Moldova (excluding the Transnistrian region) between June 3 and July 12, 2024. The survey used purposive and respondent-assisted sampling to capture household and individual-level data on living conditions, access to services, and integration challenges. This anonymized dataset supports stakeholders in addressing the needs of displaced populations and promoting integration and access to essential services in Moldova.

Web App
PDF

Angola - Subnational Administrative Boundaries

OCHA Regional Office for Southern and Eastern Africa (ROSEA)

COD+ 5600+ Downloads

Time Period of the Dataset [?]: August 30, 2018-March 06, 2025 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Angola administrative level 0-3 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. NOTE: See COD-PS caveats about two special ADM2 records. The shapefile zipfile in the HDX dataset was corrected in March 2025. It previously excluded the ADM1 layer. This COD-AB was most recently reviewed for accuracy and necessary changes in January 2025. The COD-AB requires improvements. Sourced from OCHA Regional Office for Southern and Eastern Africa (ROSEA) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. USERS SHOULD BE AWARE that changes to COD-AB datasets on HDX since February 2025 will NOT be reflected in the live geoservices. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Angola COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is 'Province'. Administrative level 2 contains 161 feature(s). The normal administrative level 2 feature type is 'Municipality'. Administrative level 3 contains 539 feature(s). The normal administrative level 3 feature type is 'currently not known'. Recommended cartographic projection: Africa Albers Equal Area Conic This metadata was last updated on March 06, 2025.

Dominican Republic - Subnational Administrative Boundaries

OCHA Field Information Services Section (FISS)

COD+ 3100+ Downloads

Time Period of the Dataset [?]: September 06, 2017-February 28, 2025 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Dominican Republic administrative level 0-4 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. NOTE: This COD-AB was updated by OCHA FIS in March 2025 without the most complete quality control processes. The live geoservices have not been similarly updated. The accompanying COD-EM has not been similarly updated. The COD-PS extends only to ADM2 This COD-AB was most recently reviewed for accuracy and necessary changes in February 2025. The COD-AB does not require any update. Sourced from OCHA Field Information Services Section (FISS) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. USERS SHOULD BE AWARE that changes to COD-AB datasets on HDX since February 2025 will NOT be reflected in the live geoservices. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Dominican Republic COD-PS. An edge-matched (COD-EM) version of this COD-AB is available on HDX here. Please see the COD Portal. Administrative level 1 contains 10 feature(s). The normal administrative level 1 feature type is 'region'. Administrative level 2 contains 32 feature(s). The normal administrative level 2 feature type is 'province or national district (distrito nacional)'. Administrative level 3 contains 158 feature(s). The normal administrative level 3 feature type is 'municipio'. Administrative level 4 contains 383 feature(s). The normal administrative level 4 feature type is 'dm(?)'. Recommended cartographic projection: North America Albers Equal Area Conic This metadata was last updated on March 04, 2025.

South Sudan - Community-Based Assessment - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: May 13, 2024-September 26, 2024 ... More

This dataset updates: Never

The Community-Based Assessment (CBA) in South Sudan, 2024 evaluates the capacity of high-return locations in South Sudan to absorb additional populations. This assessment employed a mixed-methods approach, including quantitative household surveys, qualitative assessments, and infrastructure evaluations. Data collection was conducted between May and September 2024 through face-to-face interviews in selected payams across Northern Bahr el Ghazal, Eastern Equatoria, Central Equatoria, and Western Bahr el Ghazal. The dataset comprises anonymized household and infrastructure survey data, with stratified random sampling used to ensure representation across returnees, host communities, internally displaced persons (IDPs), and refugees. The study explores key humanitarian themes, including health, water sanitation and hygiene (WASH), education, and housing, land, and property (HLP). The collected data aims to inform operational planning, self-reliance programs, and service provision strategies for displaced and returning populations. The dataset provides valuable insights to support evidence-based decision-making and improve response strategies for communities affected by displacement in South Sudan.

Web App
PDF

Global Violent Deaths (GVD) database 2004-2021, 2023 update, version 1.0

Small Arms Survey

60+ Downloads

Time Period of the Dataset [?]: January 01, 2004-May 20, 2025 ... More

This dataset updates: Every year

The Global Violent Deaths (GVD) database integrates indicators on the major causes of lethal interpersonal and communal violence—intentional and unintentional homicides, killings in legal interventions, and direct conflict deaths—and combines them in a single violent deaths indicator. These indicators are also reported in a disaggregated format by the sex of the victim and perpetration mechanism, namely firearm killings. The GVD database tracks this information across 222 countries and territories worldwide yearly from 2004 and reports both crude counts and rates per 100,000 population. The input data is retrieved from reliable sources, such as governments, national and international organizations, trusted non-governmental organizations, and verified media outlets. Missing data points are estimated using the methods described in this document. The GVD database is updated annually by the Small Arms Survey, an associated programme of the Geneva Graduate Institute, which strengthens the capacity of governments and practitioners to reduce illicit arms flows and armed violence. This is done through three mutually reinforcing activities: the generation of policy-relevant knowledge, the development of authoritative resources and tools, and the provision of training and other services. The GVD database benefits from financial support from governments and organizations, and notably its core donors, who are publicly disclosed online. The Small Arms Survey follows rigorous procedures to ensure that the input data, the applied methods, and the results are of reasonable quality. If the user encounters apparent errors, they should contact us via email at media@smallarmssurvey.org. Regions, sub-regions, countries, and territories are defined based on the classification system used by the UN Statistical Division (2013 revision), except for Kosovo, England and Wales, Northern Ireland, and Scotland. The names and designations reported in the database do not imply any sort of endorsement by the Small Arms Survey.

CSV

Mozambique: Survey for Inclusive Rapid Assessment (SIRA)

Light for the World

40+ Downloads

Time Period of the Dataset [?]: May 01, 2024-May 01, 2024 ... More

This dataset updates: As needed

SIRA Dataset for disability and older age - Cabo Delgado, Mozambique Background The Survey for Inclusive Rapid Assessment (SIRA) Dataset for disability and older age was collected in May 2024 in Pemba (urban) and Metuge (rural) localities of Cabo Delgado, Mozambique, as part of the Data that Matters project funded by Elrha. Stratified clustered random sampling was used in this survey, the aim of which is to assess the barriers and enablers people face in accessing humanitarian assistance, in particular persons with disabilities and older persons. The Data The dataset consists of: * SIRA Dataset #1. Household-level data: locality, household size, displacement status, registration * SIRA Dataset #2. Individual-level data: sex, age, education, health, employment * SIRA Dataset #3. Individual-level data: Washington Group (WG) questions taken from short (WG_SS), extended (WG-ES) of questions and child functioning modules (0-4 and 5-17 years). Questions include functioning domains associated with mental health. * SIRA Dataset #4. Individual-level data: barriers in accessing humanitarian assistance for i) distributions, ii) services, iii) livelihood opportunities, iv) sexual, maternal and reproductive health, v) safety and security. The datasets can be merged via the respondent identifier "indID", with "hhID" allowing to group individuals linked to a common household.

XLSX

Afghanistan - Subnational Administrative Boundaries

geoBoundaries

2700+ Downloads

Time Period of the Dataset [?]: January 01, 2007-December 31, 2014 ... More

This dataset updates: Live

This dataset is part of the data series [?]: geoBoundaries - Subnational Administrative Boundaries

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

GeoJSON
SHP

Marshall Islands - Subnational Population Statistics

OCHA Regional Office for Asia and the Pacific (ROAP)

COD 1600+ Downloads

Time Period of the Dataset [?]: August 01, 2021-August 31, 2021 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: COD - Subnational Population Statistics

Marshall Islands administrative level 0 sex and age disaggregated population statistics REFERENCE YEAR: 2021 This .CSV table is suitable for database or GIS linkage to the Marshall Islands - Subnational Administrative Boundaries administrative level 0 shapefile using the ADM0_PCODE field.

XLSX
CSV

Honduras - Subnational Administrative Boundaries

OCHA Latin America and the Caribbean (ROLAC)

COD+ 4600+ Downloads

Time Period of the Dataset [?]: July 01, 2010-July 01, 2010 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Honduras administrative level 0-2 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. This COD-AB was most recently reviewed for accuracy and necessary changes in November 2024. The COD-AB does not require any update. Sourced from Sistema Nacional de Información Territorial (SINIT), Secretaria Técnica de Planificación y Cooperación Externa (SEPLAN), 2010 Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Honduras COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is ""currently not known"". Administrative level 2 contains 298 feature(s). The normal administrative level 2 feature type is ""currently not known"". Recommended cartographic projection: North America Albers Equal Area Conic This metadata was last updated on January 13, 2025.

Somalia - Subnational Administrative Boundaries

OCHA Field Information Services Section (FISS)

COD+ 9500+ Downloads

Time Period of the Dataset [?]: June 23, 1984-December 31, 2024 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries

Somalia administrative level 0-2 boundaries (COD-AB) dataset.Boundaries established: 1984 NOTE: In addition to administrative levels 0-2, this dataset includes ""level 1 Operational Zones"" (OPZ1) and ""level 2 Operational Zones"" (OPZ2). 17 OPZ1 features within the Banadir administrative level 1 feature are now (as of the January 2025 update) coincident with individual administrative level 2 features. Two further OPZ1 features within the Banadir administrative level 1 polygon are excluded from the administrative structure and must be named and P-coded as 'unspecified'. All Operational Zones are not administrative boundaries and are not identified as administrative level 3 features. The six Federal member states (Somaliland, Puntland, Galmudug, Hirshabelle, South West, and Jubaland) are NOT integrated into the administrative structure. (Their boundaries cannot be constructed even from administrative level 2 features.) This COD-AB was most recently reviewed for accuracy and necessary changes in December 2024. The COD-AB does not require any update. Sourced from OCHA Somalia Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Somalia COD-PS. An edge-matched (COD-EM) version of this COD-AB is available on HDX here. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is 'Region'. Administrative level 2 contains 91 feature(s). The normal administrative level 2 feature type is 'District'. Recommended cartographic projection: Africa Albers Equal Area Conic This metadata was last updated on January 23, 2025.

Niger - Subnational Population Statistics

UNFPA

COD+ 4300+ Downloads

Time Period of the Dataset [?]: January 01, 2022-July 31, 2024 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Population Statistics

Niger administrative level 0-3 sex disaggregated 2024 population statistics This dataset also contains historical data for: 2022, 2023. REFERENCE YEAR: 2024 These CSV tables are suitable for database or GIS linkage to the Niger - Subnational Administrative Boundaries using the ADM0, ADM1, and ADM2_PCODE fields. NOTE The COD-AB live geoservices will be updated to be compatible in January 2024.