
HDX · 实时热榜
- 01Philippines - Tropical depression on Aug 04 2026
**ADAM ID: **[1001298\_8](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001298) Tropical depression during the period Aug 04 2026-Aug 06 2026 in Philippines. The center of the storm was located near latitude 16.7 longitude 122.9. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
最高第 1 名05:28 达到05:28 首次观测上榜19:04 观测离榜累计约13小时36分 - 02Democratic Republic of the Congo - CERF Allocations
This dataset lists project funding allocations from OCHA's Central Emergency Response Fund (CERF) for Democratic Republic of the Congo. CERF allocations are made to ensure a rapid response to sudden-onset emergencies or to rapidly deteriorating conditions in an existing emergency and to support humanitarian response activities within an underfunded emergency.
最高第 1 名17:12 达到14:16 首次观测上榜22:48 观测离榜累计约8小时32分 - 03Philippines - GLIDE Disaster Events
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.
最高第 1 名22:48 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约6小时32分 - 04Venezuela (Bolivarian Republic of) - CERF Allocations
This dataset lists project funding allocations from OCHA's Central Emergency Response Fund (CERF) for Venezuela (Bolivarian Republic of). CERF allocations are made to ensure a rapid response to sudden-onset emergencies or to rapidly deteriorating conditions in an existing emergency and to support humanitarian response activities within an underfunded emergency.
最高第 1 名14:16 达到14:16 首次观测上榜22:48 观测离榜累计约8小时32分 - 05Venezuela - M 7.5 Earthquake - June 2026 - OSM & Overture Data
This dataset contains OpenStreetMap data exported from the HOTOSM disaster mapping response to the magnitude 7.5 Earthquake that struck Venezuela in June 2026, Glide: EQ-2026-000093-VEN. On Wednesday, June 24, 2026, Venezuela was struck by two of the most powerful earthquakes the country has seen in over a century. The back-to-back tremors caused widespread destruction, particularly in the capital and along the northern coast. Both earthquakes caused widespread damage across the country, particularly in La Guaira and the capital, Caracas. This dataset bundles nine layers from two sources: * OpenStreetMap layers: buildings, roads, points of interest, health facilities, education facilities, airports, sea ports. * Overture Maps layers: buildings (machine-derived footprints that fill gaps where OSM is sparse) and emergency facilities (hospitals, pharmacies, fire, police, ambulance/EMS). It covers the area affected by the M7.5 earthquake in Venezuela, including the epicentral region and the urban areas of Caracas and La Guaira (bounding box: 69.76°W–65.78°W, 8.70°N–11.51°N). OSM layers have been updated by volunteers through the Humanitarian OpenStreetMap Team's Tasking Manager. It is…
最高第 1 名17:44 达到17:44 首次观测上榜22:48 观测离榜累计约5小时4分 - 06Global - GLIDE Disaster Events
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.
最高第 1 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约19小时20分 - 07Airports of Uganda
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 1 名18:00 达到18:00 首次观测上榜22:48 观测离榜累计约4小时48分 - 08Health Facilities of Venezuela
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 1 名18:16 达到18:16 首次观测上榜22:48 观测离榜累计约4小时32分 - 09GDACS RSS Information
GDACS alerts are issued for earthquakes and possible subsequent tsunamis, tropical cyclones, floods and volcanoes. Earthquake, tsunami and tropical cyclones calculations and assessments are done automatically, without human intervention. Floods and volcanic eruptions are currently manually introduced. Research and development is continuous to improve the global monitoring.
最高第 1 名01:12 达到01:12 首次观测上榜18:32 观测离榜累计约17小时20分 - 10Airports of Lebanon
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 1 名18:32 达到18:32 首次观测上榜22:48 观测离榜累计约4小时16分 - 11Health Facilities of Lebanon
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 1 名18:48 达到18:48 首次观测上榜22:48 观测离榜累计约4小时 - 12FAO Data in Emergencies Monitoring System (DIEM)
The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). Data are collected through Computer-Assisted Telephone Interviews (CATI) and in-person surveys where the circumstances allow for field access. As the system is developed, the information collected and analyzed is being used to guide strategic decisions, to design programmes and to inform analytical processes such as the Integrated Phase Classification (IPC) and the Humanitarian Needs Overview (HNO). At the core of the system is a standardized household questionnaire administered to around 150,000 households per year across the 26 countries. Standardization permits comparisons across time and space, considerably enhancing the utility of the data for decision makers. At minimum the household data are representative at Admin 1 level (e.g. province, or region) and in frequent cases at Admin 2 l…
最高第 1 名10:16 达到10:16 首次观测上榜22:48 观测离榜累计约12小时32分 - 13Airports of Venezuela
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 1 名19:04 达到19:04 首次观测上榜22:48 观测离榜累计约3小时44分 - 14State of Palestine - GLIDE Disaster Events
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.
最高第 2 名22:48 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约6小时32分 - 15USGS Magnitude 2.5+ Earthquakes
This data lists events with magnitude 2.5+ which have been located by the USGS and contributing agencies within the last day and last week. To see these events in an interactive map, see the [USGS map](https://earthquake.usgs.gov/earthquakes/map/?extent=32.00808,23.99414&extent=44.2924,47.59277). For more information, see the [USGS site](https://www.usgs.gov/programs/earthquake-hazards/earthquakes).
最高第 2 名17:28 达到17:28 首次观测上榜22:48 观测离榜累计约5小时20分 - 16Health Facilities of Congo, The Democratic Republic of the
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 2 名18:32 达到18:32 首次观测上榜22:48 观测离榜累计约4小时16分 - 17South Africa - GLIDE Disaster Events
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.
最高第 2 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约19小时20分 - 18Marshall Islands - Category 2 on Jul 27 2026
**ADAM ID: **[1001297\_48](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001297) Category 2 during the period Jul 27 2026-Aug 07 2026 in Marshall Islands, Japan, China. The center of the storm was located near latitude 26.6 longitude 126.5. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
最高第 2 名05:28 达到05:28 首次观测上榜18:48 观测离榜累计约13小时20分 - 19Health Facilities of Uganda
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 3 名17:28 达到17:28 首次观测上榜22:48 观测离榜累计约5小时20分 - 20Yemen - GLIDE Disaster Events
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.
最高第 3 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约19小时20分 - 212019 Tropical Cyclone Pawan Path
This layer shows movement path of 2019 Tropical Cyclone Pawan in Somalia. A Tropical Storm initially named 06A formed in the northern Indian Ocean and later developed into a Tropical Cyclone named Pawan after sustaining wind speeds of more than 39mph (48kph) and heavy rain for two days. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia. It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland (Bossaso, Garowe). The worst hit areas by 2019 TC Pawan included Nugaal Region (Eyl and Dangorayo Districts), Karkaar (Qardho District) and Bari Region (Alula, Iskushuban, and Baargaal Districts) who are under Garowe Somalia Red Crescent Society (SRCS) Branch) and the Coastal villages of Hafun, Iskushuban, Baargaal, Quandala and Alula Districts in Bari Region (under Bosasso SRCS Branch). Other areas affected include the coastal villages in Bari Region including Hafun, Iskushuban, Baargaal, Quandala and Alula districts. Most affected households needed urgent humanitarian assistance as they were already living in dire conditions prior to the crisis. The destruction and flooding caused by TC Pawan increased the vulnerability of communities…
最高第 3 名18:32 达到18:32 首次观测上榜22:48 观测离榜累计约4小时16分 - 22Uganda - GLIDE Disaster Events
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.
最高第 3 名22:48 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约19小时4分 - 23Airports of Congo, The Democratic Republic of the
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 4 名17:28 达到17:28 首次观测上榜22:48 观测离榜累计约5小时20分 - 24Health Facilities of Myanmar
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](https://www.openstreetmap.org), a free, collaborative world map - Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare) - Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)
最高第 4 名18:32 达到18:32 首次观测上榜22:48 观测离榜累计约4小时16分 - 25Pakistan - GLIDE Disaster Events
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.
最高第 4 名22:48 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约2小时16分 - 26Venezuela (Bolivarian Republic of) - GLIDE Disaster Events
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.
最高第 4 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约19小时4分 - 27Nigeria - GLIDE Disaster Events
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.
最高第 5 名22:48 达到22:48 首次观测上榜23:04 观测离榜累计约16分钟 - 28Tajikistan - GLIDE Disaster Events
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.
最高第 6 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约18小时48分 - 29Togo - GLIDE Disaster Events
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.
最高第 6 名23:04 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约18小时32分 - 30Chad - GLIDE Disaster Events
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.
最高第 7 名23:04 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约18小时32分 - 31Niger - GLIDE Disaster Events
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.
最高第 7 名22:48 达到22:48 首次观测上榜23:04 观测离榜累计约16分钟 - 32Namibia - GLIDE Disaster Events
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.
最高第 8 名22:48 达到22:48 首次观测上榜23:04 观测离榜累计约16分钟 - 33South Sudan - GLIDE Disaster Events
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.
最高第 9 名23:04 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约15小时20分 - 34Syrian Arab Republic - GLIDE Disaster Events
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.
最高第 9 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约18小时32分 - 35Somalia - GLIDE Disaster Events
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.
最高第 10 名23:04 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约15小时20分 - 36Sudan - GLIDE Disaster Events
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.
最高第 12 名00:00 达到当日首次采集时已在榜当日结束时仍在榜上榜 2 次(重入 1 次)累计约11小时20分 - 37Myanmar - GLIDE Disaster Events
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.
最高第 14 名22:48 达到22:48 首次观测上榜23:04 观测离榜累计约16分钟



































