Philippines GIS data
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# EOS-RS Flood Proxy Map: Philippines, Floods, 22 July 2024, v0.9 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Cagayan, Philippines due to heavy rainfall from Typhoon Carina (Gaemi). This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (01 Nov 2023 to 10 Jul 2024) and during (22 Jul 2024) the event. The map covers an area indicated by the white polygon. The preliminary map shows areas which are likely flooded (shown by light blue pixels of approximately 30m in size) in Cagayan, Philippines due to heavy rainfall from Typhoon Carina (Gaemi). Preliminary validation was conducted using news reports, images, and videos of flooding in selected areas. This map should be used as a guide to identify areas that are likely flooded, and may be less reliable over urban and vegetated areas. The product contains modified Copernicus Sentinel data (2023-2024), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2023-2024)
# Philippines Earthquake: Damage Proxy Maps, Nov 2023 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage proxy maps for Philippines Earthquake (Nov 2023) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.9 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.9 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.9** - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.9** - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.5 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.5 ** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 23 Nov 2023, v0.5 ** (superseded) **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2023)
# EOS-RS Flood Proxy Map: Philippines Typhoon Doksuri, 28 Jul 2023, v0.5 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Philippines due to Typhoon Doksuri. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (16 Jul 2023) and after (28 Jul 2023) the event. The image covers an area indicated by the white polygon. Each light blue pixel measures about 30 meters across. Preliminary validation was done in selected areas by comparing with media reports. This map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. The product contains modified Copernicus Sentinel data (2023), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), using the Advanced Rapid Imaging and Analysis (ARIA) system originally developed at NASA's Jet Propulsion Laboratory, California Institute of Technology, and modified at EOS-RS. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region. **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Contains modified Copernicus Sentinel data (2023)
# EOS-RS Flood Proxy Map: Philippines, Storm Nalgae (Paeng), 27 Oct 2022, v0.4 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Mindanao, Philippines due to heavy rains brought about by Tropical Storm Nalgae (Paeng). This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (15 Oct 2022) and during (27 Oct 2022) the event. The image covers an area indicated by the large white polygon. Each light blue pixel measures about 30m across. Preliminary validation was done by comparing with media reports. This flood proxy map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. The product contains modified Copernicus Sentinel data (2022), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), using the Advanced Rapid Imaging and Analysis (ARIA) system originally developed at NASA's Jet Propulsion Laboratory, California Institute of Technology, and modified at EOS-RS. **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Contains modified Copernicus Sentinel data (2022)
# Philippines Earthquake: Damage Proxy Maps, Oct 2022 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage proxy maps for Philippines Earthquake (Oct 2022) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 25 Oct 2022, v0.8** - **EOS-RS Damage Proxy Map: Philippines, Earthquake, 25 Oct 2022, v0.8** **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Contains modified Copernicus Sentinel data (2022)
# EOS-RS Flood Proxy Map: Philippines, Typhoon Noru, 27 Sep 2022, v0.5 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in Luzon, Philippines due to Typhoon Noru (Karding) which made landfall on 25 Sep 2022. This map was derived from synthetic aperture radar (SAR) images acquired by the ALOS-2 satellites operated by the Japan Aerospace Exploration Agency (JAXA) before (17 Mar 2020) and during (27 Sep 2022) the event. The image covers an area indicated by the large white polygon. Each light blue pixel measures about 25 meters across. Preliminary validation was done in selected areas using optical imagery. This flood proxy map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. Data were provided by Sentinel Asia and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Original data ALOS-2 PALSAR-2 Product - JAXA (2020-2022)
# Philippines Earthquake: Damage Proxy Maps, Jul 2022 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage proxy maps for Philippines Earthquake (Jul 2022) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Philippines, Lindol, 7 Agosto 2022, v0.9** - **EOS-RS Damage Proxy Map: Philippines, Lindol, 7 Agosto 2022, v0.9** **More map details and files:** **Kredito:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Advanced Rapid Imaging and Analysis (ARIA), NASA-JPL/Caltech, Naglalaman ng binagong Copernicus Sentinel data (2022)
# Philippines Cyclone Agaton: Damage and Flood Proxy Maps, Apr 2022 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage and flood proxy maps for Philippines Cyclone Agaton (Apr 2022) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Philippines, Bagyong Agaton (Megi), Abril 2022, v0.4 wbd** - **EOS-RS Damage Proxy Map: Philippines, Bagyong Agaton (Megi), Abril 2022, v0.4** (superseded) - **EOS-RS Flood Proxy Map: Philippines, Bagyong Agaton (Megi), Abril 2022, v0.4** **More map details and files:**
# Philippines Typhoon Odette: Damage and Flood Proxy Maps, Dec 2021 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage and flood proxy maps for Philippines Typhoon Odette (Dec 2021) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9 wbd** - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.5 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.5** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.9** - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.5 wbd** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.5** (superseded) - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.4 wbd** - **EOS-RS Damage Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.4** (superseded) - **EOS-RS Flood Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.3** - **EOS-RS Flood Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.35** - **EOS-RS Flood Proxy Map: Philippines, Typhoon Odette, Dec 2021, v0.3** (superseded) **More map details and files:** **More map details and files:**
# Philippines Typhoon Goni: Damage Proxy Maps, Nov 2020 The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech, in collaboration with the Earth Observatory of Singapore (EOS), produced these damage proxy maps for Philippines Typhoon Goni (Nov 2020) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **ARIA-SG Damage Proxy Map: Philippines, Typhoon Goni, 1 Nov 2020, v0.8** - **ARIA-SG Damage Proxy Map: Philippines, Typhoon Goni, 1 Nov 2020, v0.4 ** - **ARIA-SG Damage Proxy Map: Philippines, Typhoon Goni, 1 Nov 2020, v0.4 ** (superseded) **More map details and files:**
# Philippines Earthquake: Damage Proxy Maps, Aug 2020 The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech, in collaboration with the Earth Observatory of Singapore (EOS), produced these damage proxy maps for Philippines Earthquake (Aug 2020) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **ARIA-SG Damage Proxy Map: Philippines, Earthquake, 20 Aug 2020, v0.4 ** - **ARIA-SG Damage Proxy Map: Philippines, Earthquake, 20 Aug 2020, v0.4 ** **More map details and files:**
# ARIA-SG Damage Proxy Map: Philippines Taal Volcano Eruption, 15 Jan 2020, v1.0 Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (9 Jan) and after (15 Jan) the onset of the event. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS) in collaboration with NASA-JPL and Caltech. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). **More map details and files:**
# ARIA-SG Flood Proxy Map: Philippines, Typhoon Tisoy, 7 Dec 2019, v0.1 Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (23 Apr) and during (7 Dec) the event. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS) in collaboration with NASA-JPL and Caltech. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). **More map details and files:**
# ARIA-SG Damage Proxy Map: Philippines Earthquake, 25 Dec 2019, v1.0 Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (13 Dec) and after (25 Dec) the event. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS) in collaboration with NASA-JPL and Caltech. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). **More map details and files:**
# Philippines Earthquake: Damage Proxy Maps, Oct 2019 The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech, in collaboration with the Earth Observatory of Singapore (EOS), produced these damage proxy maps for Philippines Earthquake (Oct 2019) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **Philippines - ARIA Damage Proxy Map v0.4** (superseded) - **Philippines - ARIA Damage Proxy Map v0.4** **More map details and files:** **Copyright:** Contains modified Copernicus Sentinel data (2019) processed by ESA, the ARIA team at NASA-JPL and Caltech, and EOS.
# EOS-RS Damage Proxy Map: Philippines, Taal Volcanic Eruption, 12 October 2026, v1.1 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Damage Proxy Map (DPM) depicting areas that are likely damaged in Batangas, Philippines, due to a volcanic eruption from the Taal volcano on 08 October 2026. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (01 June 2026 to 17 September 2026) and after (11 October 2026) the event. The map covers an area indicated by the white polygon. Damage is shown by colored pixels of 30m in size, where yellow to red indicates increasingly significant ground surface change before and after the event. Preliminary validation was conducted using news reports in selected areas. This map should be used as a guidance to identify damaged areas, and may be less reliable over vegetated or mountainous areas. Scattered pixels over vegetated or mountainous areas may be false positives, and a lack of colored pixels over such areas may not mean no damage. This product contains modified Copernicus Sentinel data (2026), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2026)
Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT
Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT
Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT
Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT
Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT
Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, healthcare - Part of the country exports on HDX by HOT
Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: tourism, amenity, historic, heritage - Part of the country exports on HDX by HOT
Points of interest: public-facing amenities, shops, tourist attractions, and landmarks tagged via `amenity`, `shop`, `tourism`, or `man_made`. Useful for general POI reference, urban analysis, and basemap detail. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, shop, tourism, man_made - Part of the country exports on HDX by HOT
Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT
Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT
Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).
GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.
Extent of the following river basins over the study area of Mindanao island of Philippines: Rio Grande de Mindanao Basin, Agus Basin, Cagayan Basin, Tagoloan Basin, Agusan Basin, Tagum-Libuganon Basin, Davao Basin, Buayan-Malungon Basin. **Data publication:** 2020-01-01 **Contact points:** Metadata Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) Resource Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Data lineage:** Data quality information not available **Resource constraints:** copyright **Online resources:**
OECMs complement protected areas through sustained, positive conservation outcomes, even though they may be managed primarily for other reasons. In 2018, the governments of the world adopted the following definition of an OECM: _“A geographically defined area other than a Protected Area, which is governed and managed in ways that achieve positive and sustained long-term outcomes for the insitu conservation of biodiversity, with associated ecosystem functions and services and where applicable, cultural, spiritual, socio–economic, and other locally relevant values” (CBD, 2018)_ Because this definition was only recently adopted, most countries have not yet provided data to the World Database on OECMs. Importantly, this does not mean that no OECMs exist in those countries. OECMs will often be pre-existing measures that have not historically been recognised for their conservation values, ranging from Sacred Natural Sites to some military zones. The challenge for governments and other stakeholders will be in identifying OECMs, and supporting them to maintain their conservation benefits in the long term. IUCN's World Commission on Protected Areas (WCPA) has provided guidance on recognising OECMs. **Supplemental Information:** Users should note the following points before using the WD-OECM: * The WD-OECM can be combined with the World Database on Protected Areas (WDPA) to provide a more comprehensive picture of the world’s conservation network; * The WDPAID is the unique identifier for both the WD-OECM and WDPA. It remains unique even when the two databases are combined; * When the two databases are combined, the PA_DEF field can be used to distinguish protected areas (1) from OECMs (0); * The WD-OECM has two fields not present in the WDPA: - CONS_OBJ (conservation objectives): this field refers to the primacy of conservation objectives. The field provides an indication of whether an OECM is managed with biodiversity conservation as a primary objective, secondary objective, or without conservation as an explicit objective. It should not be considered binding, and the primacy of conservation objectives may change over time without affecting an OECM’s status. A move to conservation as a primary objective may, however, coincide with an OECM being reclassified as a protected area, with the consent of the governance authority. - SUPP_INFO (supplementary info): link or reference to information supporting the categorization of the site as an OECM. **Citation:** UNEP-WCMC (2026). Protected Area Profile for Philippines from the World Database on Protected Areas, September 2026. Available at: [www.protectedplanet.net](www.protectedplanet.net) **Contact points:** Resource Contact: [UNEP](mailto:oecm@unep-wcmc.org) **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:**
geoBoundaries ADM0 boundaries for Philippines: 1 units, representing 2020. Source: OCHA Philippines, National Mapping and Resource Information Authority.