OCHA Philippines

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

Philippines administrative level 0-4 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. NOTE: See COD-PS caveat about treatment of National Capital (Manila) data. OCHA acknowledges PSA and the National Mapping and Resource Information Authority (NAMRIA) as the sources. LMB is the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. Its updated to reflect the new areas within BARMM; It uses the new 10-digit pcode consistent with government PSGC as of 2023 This COD-AB was most recently reviewed for accuracy and necessary changes in April 2024. The COD-AB does not require any update. Sourced from National Mapping and Resource Information Authority (NAMRIA), Philippines Statistics Authority (PSA) 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 Philippines COD-PS. As this is an island country, no edge-matched (COD-EM) version of this COD-AB is required. Please see the COD Portal. Administrative level 1 contains 17 feature(s). The normal administrative level 1 feature type is ""currently not known"". Administrative level 2 contains 88 feature(s). The normal administrative level 2 feature type is ""currently not known"". Administrative level 3 contains 1,642 feature(s). The normal administrative level 3 feature type is ""currently not known"". Administrative level 4 contains 42,048 feature(s). The normal administrative level 4 feature type is ""currently not known"". Recommended cartographic projection: Asia South Albers Equal Area Conic This metadata was last updated on January 13, 2025.

River system in 250km scale. Projection is WGS84. Some segments contain names in the attribute.

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

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

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

Total Population by Single-Year Age, Sex, Region, Province, City/Municipality and Barangay (admin 4) Census 2020. It uses the new 10-digit pcode consistent with [Philippines - Subnational Administrative Boundaries] (https://data.humdata.org/dataset/cod-ab-phl).

2020 Census Population by sex, age group and municipality (admin3)

Housing Units by Construction Materials of the Outer Walls and Roof Census 2020

Philippines: Household Population 5 Years Old and Over by Functional Difficulty, Severity, Age Group, Sex, and City/Municipality Census 2020

Philippines - Households by Kind of Toilet Facility and City/Municipality (Admin 3) Census 2020

2020 Census Total Population by Barangay (admin4) with new 10-digit pcode with Maguindanao del Sur and Norte; Missing barangays in R12 that moved to BARMM

Philippines - Typhoon Rai (Odette) Who does What Where

Philippines - Households by Main Source of Drinking Water by City/Municipality (Admin3) Census 2020

The dataset contains location and classification of airports complied from Civil Aviation Authority of the Philippines, Department of Transportation.

The data covers all registered Pantawid IP beneficiaries regardless of their program status. The Modified Conditional Cash Transfer Program (MCCT) is a sub-component of Pantawid Pamilyang Pilipino Program which is uses modified approach in implementing the CCT program for poor families including homeless, Indigenous People and Families in Need of Special Protection (FNSP).

This data is about the key figures of the severely affected areas on the 6.6 earthquake in Tulunan, Cotabato (North Cotabato).

This data refers to the cumulative number of health workers by profession and by type of facility ownership from 2010 to June 2018, based on the available data from National Database of Human Resources for Health Information System (NDHRHIS) of the Department of Health as of 30 June 2018. Data are reflective of hospitals, clinical laboratories that have self-registered in the NDHRHIS and covered 60% of licensed private and public hospitals and laboratories. Municipalities without data on public/government owned facilities does mean that there are no government-owned facilities rather that no such facilities was captured in the NDHRHIS.

Natural disasters data on affected and displaced people in 2019.

The data is coming from Philippines Institute of Volcanology and Seismology (DOST-PHIVOLCS).

Shapefile (WGS 84) of thirty-three lakes of the Philippines with corresponding local name, based on the country shapefile from the Philippine Statistics Authority.

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

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