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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.

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.

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.

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.

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.

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.

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.

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.

**ADAM ID: **[1001335\_38](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001335) Tropical depression during the period Oct 07 2026-Oct 16 2026 in México. The center of the storm was located near latitude 21.5 longitude -110.3. 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.

**ADAM ID: **[sm\_us6000u2y1](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000u2y1) Magnitude 5.7 earthquake at 10.0 depth occurred on Oct 17 2026 44km W of Kuzdar Tehsil. The epicentre of the earthquake was located at latitude 28.0179 longitude 66.1708. It impacted 114531 people within 50km. 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.

**ADAM ID: **[1001339\_4](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001339) Category 1 during the period Oct 16 2026-Oct 17 2026 in Cook Islands. The center of the storm was located near latitude -14.8 longitude -163.2. 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.

**ADAM ID: **[1001337\_17](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001337) Category 2 during the period Oct 13 2026-Oct 17 2026 in México. The center of the storm was located near latitude 16.6 longitude -103.9. 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.

**ADAM ID: **[sm\_us6000u2mq](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000u2mq) Magnitude 6.9 earthquake at 143.176 depth occurred on Oct 16 2026 76 km NE of Ozernovskiy, Russia. The epicentre of the earthquake was located at latitude 52.0066 longitude 157.2499. It impacted 154 people within 50km. 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.

The DIEM Events Visualization in Emergencies (EVE) system provides resources to enhance the understanding of flood events and their impact on different land cover types, with a particular focus on agricultural areas. EVE provides a flood persistence analysis as well as an estimation of the population exposed to such events. EVE utilizes satellite-derived data from the NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) at a 375-meter resolution, alongside land cover data from the European Space Agency’s WorldCover 10m 2021 dataset. Covering approximately 40 countries, the system offers daily and biweekly insights, providing a continuously updated view of flood dynamics and their effects. Access the [FAO EVE user guide](https://data-in-emergencies.fao.org/documents/3335ee769a4e45708e27d2ee25d13bef/about) to learn more. The platform presents results through interactive maps, charts, and tables, supporting decision-making in disaster management, agricultural planning, and environmental monitoring. Most resources are publicly accessible, though downloading aggregated data at the admin2 level requires a [DIEM account](https://hqfao.maps.arcgis.com/sharing/rest/oauth2/signup?client_id…

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…

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.

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.

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.

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.

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.

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.

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.

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.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR934. On 09 October at 17:56 UTC (12:56 Local Time) Panama was struck by a 7.7M earthquake. The epicentre was 12 km west-southwest of Pitaloza Arriba, Panama (inland). Copernicus EMS Rapid Mapping is requested to provide earthquake damage assessment emergency mapping. GDACS ID: EQ1570339. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR934 **Product types present in this dataset's resources:** **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

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).

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…

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR929. On August 31, 2026, at 16.00 UTC, in Trapezitsa Mountain, near the city of Konitsa, Ipirus Region, Greece, a fire started due to a lightning, which mainly burned underground. At the time the fire was ongoing, burning a forest of black pine. A large number of firefighters and aerial means were used for fire suppression, assisted by municipality vehicles/machinery and volunteer organisations.Copernicus EMS Rapid Mapping was requested to provide initial rough estimation, fire extent and damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR929 **Product types present in this dataset's resources:** **DEL (Delineation)**: maps the extent of the event itself (eg. flood, fire, landslide boundary). **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR932. On the 15 September 2025 at 13:00 UTC, an active fire was reported to have affected anthropic forestry land in Huelva Province. Copernicus EMS Rapid Mapping was requested to provide initial rough estimation, fire extent and damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR932 **Product types present in this dataset's resources:** **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR928. On the 28 August 2026, a severe storm was reported to have affected the province of Cremona, Italy, causing damage to public and private buildings, to infrastructures and roads, as well as fallen trees. Copernicus EMS Rapid Mapping was requested to provide damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR928 **Product types present in this dataset's resources:** **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR931. On the 10 September 2026 at 20:15, a forest fire was reported to have affected the Island of Brac in Croatia and was spreading towards the settlements of Milna and Nerežišća. Copernicus EMS Rapid Mapping was requested to provide initial rough estimation, fire extent and damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR931 **Product types present in this dataset's resources:** **DEL (Delineation)**: maps the extent of the event itself (eg. flood, fire, landslide boundary). **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR927. On the 26 August 2026, a flash flood reportedly triggered by a Glacial Lake Outburst Flood (GLOF) in Nepal has caused significant damage in Rasuwa District. Copernicus EMS Rapid Mapping was requested to provide flood extent and damage assessment emergency mapping. GDACS ID: FL1104124. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR927 **Product types present in this dataset's resources:** **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR922. Starting from 14 August at 22:00 UTC a wildfire started to spread on different areas. The event is ongoing and the most serious fires are currently near Herceg Novi (Bijela and Baošići) and Ulcinj, where strong winds have helped the fires spread. Several homes were threatened, and some residents were temporarily evacuated as a precaution. Additional fires have been reported near Bar, Nikšić, Kolašin, and Cetinje. Firefighters, volunteers, military , and AFFF with planes and helicopters are actively engaged. Copernicus EMS Rapid Mapping is requested to provide burnt area delineation and damage assessment emergency mapping **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR922 **Product types present in this dataset's resources:** **DEL (Delineation)**: maps the extent of the event itself (eg. flood, fire, landslide boundary). **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - p…

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR933. On 01 October 2026, a severe rainfall and flooding event was reported to have affected Crete, Greece. The event was ongoing and intensifying, with damage reported to have affected buildings, critical infrastructure, transportation networks, agricultural areas and private properties. Copernicus EMS Rapid Mapping was requested to provide flood extent and damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR933 **Product types present in this dataset's resources:** **DEL (Delineation)**: maps the extent of the event itself (eg. flood, fire, landslide boundary). **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.

This dataset contains Copernicus EMS Rapid Mapping products for activation EMSR930. On the 2 September 2026, at 13:00 UTC a storm was reported to have affected the cities of Policoro and Scanzano Jonico, in the Basilicata region, Italy. The storm hit the cities, the coast and the countryside, downing trees, damaging beach establishments, structures and greenhouses, ripping off roofs and causing power outages. Copernicus EMS Rapid Mapping is requested to provide damage assessment emergency mapping. **Citation:** Copernicus Emergency Management Service (© 2026 European Union), EMSR930 **Product types present in this dataset's resources:** **GRA (Grading)**: assesses damage to individual features (eg. buildings, infrastructure). Where a GeoPackage download is available for an Area of Interest/round, it already contains every layer with its official Copernicus styling and colours - prefer it in GIS software over the zipped shapefile download.