Geodata Humanitarian Datasets | Find Crisis Data

Flooding in the Philippines on October 28, 2022

Time Period of the Dataset [?]: October 28, 2022-October 28, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of October 28, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on October 19, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: October 19, 2022-October 19, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of October 19, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on October 14, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: October 14, 2022-October 14, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of October 14, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on September 28, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: September 28, 2022-September 28, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of September 28, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on August 27, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: August 27, 2022-August 27, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of August 27, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on August 25, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: August 25, 2022-August 25, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of August 25, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on August 24, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: August 24, 2022-August 24, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of August 24, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Flooding in the Philippines on August 05, 2022

The Philippine Space Agency

Time Period of the Dataset [?]: August 05, 2022-August 05, 2022 ... More

This dataset updates: As needed

This dataset shows the actual extent of flooding in the Philippines caused by typhoons or tropical cyclones as of August 05, 2022, as observed through available satellite imagery. The dataset can be used to track the progression of floods over time, identify areas at risk, and assess the impact of these natural disasters on infrastructure, agriculture, and local populations.

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Damage Assessment in Mandalay & Sagaing Districts, Myanmar as of 03 April 2025

United Nations Satellite Centre (UNOSAT)

Time Period of the Dataset [?]: April 10, 2025-April 10, 2025 ... More

This dataset updates: Never

UNOSAT code: EQ20250328MMR, GDACS ID: 1474477 This map illustrates the density of damaged buildings affected by the March 28, 2025, earthquake in Mandalay. The analysis focuses on Mandalay & Sagaing Districts. Within the map extent of about 2,100 km², UNOSAT, Copernicus EMS and ICube-SERTIT observed a total of 4,764 destroyed and damaged structures & 4,369 potentially damaged structures. Within Mandalay City boundary of about 110km², a total of 1,076 structures are observed as destroyed and damaged, & a total of 519 structures are observed as potentially damaged. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

Ethiopia NightTime Light

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

This dataset presents high-resolution satellite-derived Nighttime Lights (NTL) imagery of Ethiopia,a resolution of approximately 5000 mettres , acquired from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS). NTL data captures the intensity and distribution of artificial lighting, serving as a proxy for human settlements, infrastructure development, and economic activity. No information provided

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Ethiopia Livelihood zones

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

Livelihood zone maps define geographic areas of a country where people generally share similar options for obtaining food and income and similar access to markets. An understanding of geographic livelihood systems is a key component in Vulnerability Assesment for both Drought and Floods - The livelihood zones of resolution approximately 5000 metres ( 0.05×0.05) Referenced September 2019 No information provided

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Ethiopia _Livestock_Density

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

This dataset contains the most up to date version of GLW 4 for the reference year 2020 for the following species: buffalo, cattle, sheep, goats, pigs and chicken,at the resolution of 0.05 ×0.05 , The fourth version of GLW, compared to the previous ones, reflects the most recently compiled and harmonized subnational livestock distribution data No information provided

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Ethiopia Aridity

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

Aridity index (AI) is an effective estimator of drought status, and spatiotemporally continuous long-term AI dataset is critical for drought assessment and applications.This dataset offers valuable support for research on dryland ecosystems, agriculture, and climate change, offering critical insights to address global environmental and sustainability challenges. Resolution ;0.05 × 0.05 in the resolution ( referenced year 2022) No information provided

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Myanmar Populated Places (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

200+ Downloads

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: Every day

This dataset is part of the data series [?]: HOTOSM Populated Places

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city') OR tags['landuse'] IN ('residential') Features may have these attributes: name name:en place landuse population is_in source name:my This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Myanmar Education Facilities (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

100+ Downloads

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: Every day

This dataset is part of the data series [?]: HOTOSM - Education Facilities

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university') Features may have these attributes: name name:en amenity building operator:type capacity:persons addr:full addr:city source name:my This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Ethiopia Rangeland Mask

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

This dataset provides a spatial mask of Ethiopia rangelands, identifying areas dominated by grasslands, shrublands, and sparse vegetation that are primarily used for grazing and pastoral livelihoods. The rangeland mask for Ethiopia delineates regions where pastoralism and agro-pastoralism are prevalent, helping distinguish these land systems from croplands, forests, or urban areas. The dataset is derived from a combination of remote sensing data and land cover classifications, ensuring consistency across ecological zones- No information provided

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Ethiopia population Density -

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 09, 2025-April 09, 2025 ... More

This dataset updates: As needed

This dataset represents the estimated population density of Ethiopia in the year 2020 , expressed as the number of people per square kilometer. It is intended to support spatial analysis and decision-making in areas such as disaster risk reduction, resource allocation, development planning, and vulnerability assessment Source - WORLDPOP Relationship to Exposure- (Positive)- The higher the population, the higher the exposure No information provided

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Somalia _Livelihood Zones

IGAD Climate Prediction and Applications Center (ICPAC)

Time Period of the Dataset [?]: April 07, 2025-April 07, 2025 ... More

This dataset updates: As needed

No abstract provided No information provided

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Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected countries)

ETH Zürich - Weather and Climate Risks

3500+ Downloads

Time Period of the Dataset [?]: January 02, 1980-December 25, 2020 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: ETH Zürich - Weather and Climate Risks

Tropical cyclone wind footprints (m/s) at 150 arcsec (approx 4 kilometers at equator) resolution. Available as global files and per country; available for historically observed records, and synthetically created, probabilistic events, from various modelling sources, for present and future climate scenarios.

CSV

Wildfire: Humanitarian Response Plan (HRP) Countries Hazard Data for...

ETH Zürich - Weather and Climate Risks

2800+ Downloads

Time Period of the Dataset [?]: January 01, 2001-January 01, 2020 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: ETH Zürich - Weather and Climate Risks

Global wildfire dataset at 4km resolution, based on MODIS satellite data 2000-2021 (cf https://firms.modaps.eosdis.nasa.gov).

CSV

Global airports

WFP - World Food Programme

3900+ Downloads

Time Period of the Dataset [?]: October 06, 2015-October 06, 2015 ... More

This dataset updates: As needed

This layer contains airports locations. This dataset brings together various public sources such as OpenStreetMap or ourairports.com with WFP logistics information. It is updated regularly with inputs from WFP aviation unit but also from many partners through the Logistics Cluster and the Logistics Capacity Assessment (LCA: dlca.logcluster.org). The information is compiled at a global level by the Emergency and Preparedness Geospatial Information Unit at the World Food Programme (WFP) Headquarters in Rome, Italy. This dataset is at a global scale and is updated country by country. The last update date can be retrieved from the data of the country of interest.

GeoJSON

Second-level administrative divisions (admin2)

UNHCR - The UN Refugee Agency

1200+ Downloads

Time Period of the Dataset [?]: June 23, 2022-April 22, 2025 ... More

This dataset updates: Live

This layer shows the different administrative boundaries (levels: 2) used in the UNHCR GIS system. It is mostly from governments and official sources but also other UN bodies or NGOs. The OCHA CODs and Pcodes are examined and considered. The boundaries and names do not imply official endorsement or acceptance by the United Nations.

UNHCR Population Reference Points (PRP)

UNHCR - The UN Refugee Agency

200+ Downloads

Time Period of the Dataset [?]: June 07, 2021-April 22, 2025 ... More

This dataset updates: Live

Point layer that represents populated places locations (e.g., capitals/ cities/ towns) and of administrative units (Level 1, 2 and 3 depending on availability).

Damage Assessment in Sagaing and Mandalay, Myanmar as of 30 March 2025

United Nations Satellite Centre (UNOSAT)

40+ Downloads

Time Period of the Dataset [?]: April 03, 2025-April 03, 2025 ... More

This dataset updates: Never

UNOSAT code: EQ20250328MMR, GDACS ID: 1474477 This map illustrates the number of affected buildings within specific Towns/Village Tracts boundaries of interest in Sagaing and Mandalay, Myanmar, as of 30 March 2025. Within the analyzed area—52 Towns/Village Tracts covering approximately 340 km², UNOSAT identified 1,095 damaged structures and 1,325 potentially damaged ones. The analysis represents areas where more than 50% of each Village Tract has been assessed for impact. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

Damage Assessment in Sagaing Township, Sagaing District, Sagaing Region,...

United Nations Satellite Centre (UNOSAT)

10+ Downloads

Time Period of the Dataset [?]: April 03, 2025-April 03, 2025 ... More

This dataset updates: Never

UNOSAT code: EQ20250328MMR, GDACS ID: 1474477 This map illustrates the potentially damaged structures/buildings affected by the March 28, 2025, earthquake in Mandalay. The analysis focuses on a part of Sagaing Township, Sagaing District, Sagaing Region, where damage was detected using a Pleiades very high-resolution satellite image acquired on March 30, 2025, at 11:01 local time. UNOSAT identified 233 damaged structures and 557 potentially damaged ones. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).