HOTOSM Turkey Destroyed Buildings (OpenStreetMap Export)

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

Humanitarian OpenStreetMap Team (HOT) conducted a pilot of Crowdsourced Damage Assessment (CDA) with local mappers from the Myanmar OpenStreetMap Community (myOSM) to identify and map damaged buildings in priority affected townships from the March 2025 Myanmar earthquake. Through the CDA, mappers will review damaged buildings by comparing pre- and post-disaster satellite imageries (from Maxar and Planet) to identify signs of damages. These were reviewed, mapped, and validated with open-source tools MapSwipe, HOT Tasking Manager, and MapRoulette. Damage assessments were conducted in 20 townships, including: Bago, Magway, Aungmyaythazan, Chanayethazan, Mahaaungmyay, Chanmyathazi, Pyigyitagon, Amarapura, Sintgaing, Kyaukse, Meiktila, Thazi, Patheingyi, Za Bu Thi Ri, Det Khi Na Thi Ri, Pyinmana, Poke Ba Thi Ri, Oke Ta Ra Thi Ri, Lewe, and Sagaing. This dataset includes all OpenStreetMap features (nodes, ways, and relations) within Myanmar that contain any tag key related to “damage”.) Features may have these attributes: - name - building - damage - damage:event - source:damage - source:damage:date - addr:street - addr:city - source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

This dataset contains OpenStreetMap data exported from the HOTOSM disaster mapping response to the earthquake in Colombia in August 2026 (Glide: EQ-2026-000146-COL). On Monday, August 10, 2026, a 7.4-magnitude earthquake struck western Colombia, the strongest earthquake recorded in the country in over a century. The quake was centered in the Chocó department and was felt across much of the country, as well as in parts of neighbouring Ecuador and Panama, causing widespread destruction in Cali, Pereira, Manizales, Quibdó, and other cities. HOT worked with OSM Colombia, UNGRD (Colombian National Disaster Risk Management Unit), UN Maps, UNDP and IGAC to define priority areas and features. The data has been contributed by volunteers through the Humanitarian OpenStreetMap Team's Tasking Manager and represents buildings and roads. See the list of projects in the Tasking Manager here. For more information see the HOTOSM activation page. As of 8 September 2026: over 450 contributors.

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

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

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