Search for a Dataset - Humanitarian Data Exchange

The Philippines schools mapping by OpenStreetMap

200+ Downloads

Time Period of the Dataset [?]: October 23, 2021-October 23, 2021 ... More

This dataset updates: As needed

This project is a portmanteau of OSM + Map + Paaralan - to collaboratively map public schools (paaralan) in the Philippines, on OpenStreetMap. Documentation available at https://wiki.openstreetmap.org/wiki/Philippines/OSMaPaaralan

TSV
CSV

Tracking Seagrass, the Philippines

Globhe Drones

50+ Downloads

Time Period of the Dataset [?]: May 20, 2020-May 20, 2020 ... More

This dataset updates: Never

Drone seagrass mapping, Panglao, the Philippines conducted with Crowddroning by GLOBHE. More maps and data available on demand upon request from locations globally at https://globhe.com/ MORE CROWDDRONING BY GLOBHE Webb: https://globhe.com/ Facebook: https://www.facebook.com/Crowddroning Twitter: https://twitter.com/globhedrones Instagram: https://www.instagram.com/globhedrones/ LinkedIn: https://www.linkedin.com/company/globhedrones/

GeoTIFF

Survey on Gender Equality At Home

Data for Good at Meta

4300+ Downloads

Time Period of the Dataset [?]: September 21, 2020-September 21, 2020 ... More

This dataset updates: As needed

This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home

XLSX

Philippines administrative level 2 capital cities

OCHA Field Information Services Section (FISS)

COD 100+ Downloads

Time Period of the Dataset [?]: December 23, 2021-July 25, 2024 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Populated Places - Settlements

Point shapefile of capital cities of Philippines administrative level 2 features. Excludes the four districts of the National Capital Region. P-coded in accordance with their administrative 2 feature.

SHP

Current IATI aid activities in Philippines

International Aid Transparency Initiative

20+ Downloads

Time Period of the Dataset [?]: January 01, 2019-July 25, 2024 ... More

This dataset updates: Live

This dataset is part of the data series [?]: IATI - Current IATI aid activities

Live list of active aid activities for Philippines shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org

CSV

Philippines Population Projection 2020 to 2025 by Admin3

OCHA Philippines

300+ Downloads

Time Period of the Dataset [?]: March 01, 2021-July 01, 2025 ... More

This dataset updates: As needed

This data is about the Philippines population projection count 2020 to 2025 by city/municipality (admin3) based on 2015 Census

XLSX

Global Food Prices Database (WFP)

WFP - World Food Programme

10000+ Downloads

Time Period of the Dataset [?]: January 01, 1990-August 15, 2021 ... More

This dataset updates: Never

This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

CSV

Philippines : COVID-19 Operational Presence Risk Communication and Community...

OCHA Philippines

1500+ Downloads

Time Period of the Dataset [?]: March 16, 2020-June 03, 2020 ... More

This dataset updates: As needed

This data is about the Risk Communication and Community Engagement on COVID-19 related humanitarian activities in the Philippines.

XLSX

Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco

Global Shelter Cluster

200+ Downloads

Time Period of the Dataset [?]: December 08, 2020-February 15, 2021 ... More

This dataset updates: As needed

Shelter Cluster 4W report (Who does What, Where, and When) for typhoon Goni (Rolly) and Vamco (Ulysses) in the Philippines

XLSX

Humanitarian Access Indicators

HDX

400+ Downloads

Time Period of the Dataset [?]: November 20, 2020-November 20, 2020 ... More

This dataset updates: As needed

Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.

CSV

COVID-19 High-Frequency indicators

World Bank Group

700+ Downloads

Time Period of the Dataset [?]: December 01, 2020-February 19, 2021 ... More

This dataset updates: As needed

The dataset contains 93 harmonized indicators on 14 topics (demographic, food security, education, labor, health..) on households and individuals in 44 countries across all developing regions.

XLSX

Philippines: Pre-Disaster Indicators

OCHA Philippines

COD 3500+ Downloads

Time Period of the Dataset [?]: September 01, 2015-September 01, 2015 ... More

This dataset updates: Never

This datasets contains a collection of pre-disaster indicators for the Philippines.

XLSX

PHILIPPINES: 2020 Significant events

OCHA Philippines

300+ Downloads

Time Period of the Dataset [?]: January 07, 2021-July 25, 2024 ... More

This dataset updates: Never

Consolidated information of different events happened in the Philippines in 2020 such, Taal volcano eruption, COVID-19, earthquakes, and typhoons.

XLSX

Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco

Global Shelter Cluster

80+ Downloads

Time Period of the Dataset [?]: December 08, 2020-December 08, 2020 ... More

This dataset updates: As needed

Shelter Cluster 4W report (Who does What, Where, and When) for typhoon Goni (Rolly) and Vamco (Ulysses) in the Philippines

XLSX

Philippines: Poverty statistics

OCHA Philippines

2700+ Downloads

Time Period of the Dataset [?]: July 10, 2019-July 10, 2019 ... More

This dataset updates: As needed

Based on Republic Act 8425, otherwise known as Social Reform and Poverty Alleviation Act, dated 11 December 1997, the poor refers to individuals and families whose income fall below the poverty threshold as defined by the government and/or those that cannot afford in a sustained manner to provide their basic needs of food, health, education, housing and other amenities of life. It may be estimated in terms of percentages (poverty incidence) and total number of poor families (magnitude of poor families). Also, this dataset has been generated by combining Philippine Standard Geographic Codes (PSGC) and poverty estimates from Philippine Statistics Authority (PSA). For more details, please refer to the following documents: https://psa.gov.ph/poverty-press-releases/references https://psa.gov.ph/poverty-press-releases/technotes https://psa.gov.ph/poverty-press-releases/glossary https://psa.gov.ph/sites/default/files/Technical%20Notes%20on%202015%20SAE.pdf

XLSX

AI + OSM buildings in Camarines Sur (1-nov-2020)

Netherlands Red Cross - 510

70+ Downloads

Time Period of the Dataset [?]: November 01, 2020-November 01, 2020 ... More

This dataset updates: Never

OpenStreetMap buildings of Camarines Sur (as of 1-nov-2020) and AI predictions on Bing Maps images (approximately 2016-2019). Produced in support of Philippines Red Cross for typhoon Goni (1-nov-2020) Coordinate reference system: WGS 84 / EPSG:4326

GeoJSON

Philippines - Zamboanga Home Based IDP Re-Profiling 2016

UNHCR - The UN Refugee Agency

10+ Downloads

Time Period of the Dataset [?]: July 01, 2016-August 31, 2016 ... More

This dataset updates: Never

In April 2016, following a series of consultations between the United Nations High Commissioner for Refugees, the City Social Welfare and Development Office and other partners in Zamboanga, a profiling exercise for home-based internally displaced persons (IDPs) was conceptualized. The main purpose was to validate the relevance of existing lists and obtain up-to-date information from home-based IDPs who decided to take part in the exercise so that the government, as well as other humanitarian and development actors, can make informed and consultative decisions while designing and targeting their assistance programs, including protection interventions. Following a piloting phase in June 2016, the full-blown profiling was conducted in July-August 2016 and reached 6,474 families from 66 barangays in Zamboanga. Of these, 1,135 families were assessed to be potential home-based IDPs based on the documents they presented. The profiling revealed that most home-based IDPs are living in barangays of Sta. Catalina, Sta. Barbara, Talon-Talon and Rio Hondo.

Web App
PDF

Philippines - Population Counts

WorldPop

300+ Downloads

Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: World Pop - Population Counts

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

GeoTIFF

Philippines - Profiling Internally Displaced Persons of the Marawi Conflict

UNHCR - The UN Refugee Agency

40+ Downloads

Time Period of the Dataset [?]: June 04, 2018-June 14, 2018 ... More

This dataset updates: Never

This report presents the findings of the profiling activities conducted from June to August 2018 in communities hosting internally displaced persons (IDPs) of the Marawi conflict and return communities in the provinces of Lanao del Sur, Lanao del Norte, Misamis Oriental and Bukidnon. Data was collected through structured interviews with IDP households using the kobo™ tool. Primary respondents were heads of households and in their absence, any person of legal age in the family. A total of 34,785 heads of households were interviewed in the profiling activity, representing 97,126 IDPs in 56 municipalities and 3 cities. This report presents data on demographic makeup of the IDPs such as age, sex, number of households, and family size, as well as protection information relating to displacement location, place of origin, resettlement, integration; various vulnerabilities of persons with special needs; educational attainment; income livelihood and skills; access to assistance; access to information; civil documentation; property ownership; intent to return; access to information, assistance received, and sources of assistance. Special focus is given on children and women in separate sections of this report. A significant number of IDPs continue to experience gaps in assistance related to health, education, shelter and long-term livelihood support. Also, IDPs continue to experience protection risks due to lack of civil documentation due to loss or destruction of birth certificates. A more nuanced and targeted approach that will address specific protection needs of IDPs is needed.

Web App
PDF

Humanitarian Access Constraints due to COVID-19 Pandemic

OCHA HQ

400+ Downloads

Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More

This dataset updates: As needed

The new and emerging access constraints that people are currently experiencing because of the COVID-19 outbreak.

XLSX

COVID19 Humanitarian Access Constraints, Impacts and Mitigation

OCHA HQ

100+ Downloads

Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More

This dataset updates: Every two weeks

This dataset contains scores for humanitarian access constraints into country, constraints within country, impacts the constraints have led to as well as the mitigation strategies in place to limit the impact. The scores have the following interpretations: 0 = NA, 1 = No or open, 2 = partially open/closed, 3 = Yes or closed

XLSX

HOTOSM Philippines (south) Buildings (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

200+ Downloads

Time Period of the Dataset [?]: March 03, 2023-March 03, 2023 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Buildings

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: addr:city office name building:levels addr:housenumber addr:full building addr:street source building:materials This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Philippines (south) Points of Interest (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

100+ Downloads

Time Period of the Dataset [?]: March 03, 2023-March 03, 2023 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Points of Interest

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: addr:city name opening_hours addr:housenumber tourism beds shop addr:full rooms addr:street source man_made amenity This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Philippines (south) Waterways (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

400+ Downloads

Time Period of the Dataset [?]: March 03, 2023-March 03, 2023 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Waterways

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: width name natural tunnel water depth waterway layer blockage source covered This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Philippines (south) Roads (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

500+ Downloads

Time Period of the Dataset [?]: March 03, 2023-March 03, 2023 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Roads

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: highway width name lanes smoothness surface layer source bridge oneway This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.