Mozambique GIS data

uav imagery by INGD, acquired 2025-09-24 to 2025-09-24, 5.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-02-02 to 2026-02-02, 34.8 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-06 to 2025-09-06, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-06 to 2025-09-06, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-22 to 2025-09-22, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-21 to 2025-12-12, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-02-08 to 2026-02-08, 34.2 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-06 to 2025-09-06, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD_Cenoe, acquired 2025-09-22 to 2025-09-22, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-21 to 2025-12-12, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-21 to 2025-12-13, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-21 to 2025-12-12, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-12-09 to 2025-12-10, 5.0 cm per pixel, published on OpenAerialMap.

geoBoundaries ADM0 boundaries for Mozambique: 1 units, representing 2017. Source: OpenStreetMap, Wambacher. Open Data Commons Open Database License 1.0

geoBoundaries ADM1 boundaries for Mozambique: 10 units, representing 2017. Source: OpenStreetMap, Wambacher. Open Data Commons Open Database License 1.0

This data relates to an aerial survey conducted of Mozambique from the 24-29 March 2019 following tropical cyclone Idai. Data was collected by INGC (National Disaster Management Authority of Mozambique), IFRC, UNDAC, MSF, DFID, Save the Children, and MapAction. Enumerators flew in squirrel helicopters over priority areas (usually at 500 feet) and some fixed wing aircraft for confirmation on outlying areas. Data contains location, points of interest, severity and estimated population. The survey used Kobo for data collection. Processing was conducted in R and then imported into ArcGIS for final map products. Data is presented in .xlsx (with and without hxl tags) and .geojson formats.

Dataset contains windspeeds in miles per hour.

**ADAM ID: FL-20230301-MOZ-00** Flood covering 502890.0 sq m on Mar 01 2023 in Mozambique. It impacted 401099 people.

Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

Data produced under the ADRF Sub Saharan Africa Risk Profiles project. The project provides also risk data produced, exposure and hazard data used in the analyses.

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2, ADM3. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

Layer provides distribution of landslide hazard, describing by an index of very low to very high hazard. Data produced under the ADRF Sub Saharan Africa Risk Profiles project. The project provides also risk data produced, exposure and hazard data used in the analyses.

A 100 m spatial resolution geotiff of walking travel time in seconds to nearest health facility in Mozambique. The data was generated using the Child Poverty and Access to Services (CPAS) software (10.5281/zenodo.4638563) and was created as part of the CPAS project within the Data for Children Collaborative. The travel time is calculated assuming walking speeds on all roads, tracks, paths and land cover types. A full description is available here a video description of the data is also available here Projection system is: GCS_WGS_1984 EPSG 4326 for all

**ADAM ID: **FL-20250318-MOZ-00 A flood occurred on Mar 18 2025 in Mozambique. It affected an estimated 566438 people and 62684 ha of cropland. 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: **FL-20250315-MOZ-01 A flood occurred on Mar 15 2025 in Mozambique. It affected an estimated 436040 people and 49593 ha of cropland. 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: **FL-20250312-MOZ-00 A flood occurred on Mar 12 2025 in Mozambique. It affected an estimated 155410 people and 13982 ha of cropland. 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: **FL-20260120-MOZ-00 A flood occurred on Jan 20 2026 in Mozambique. It affected an estimated 243419 people and 118342 ha of cropland. 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 FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Mozambique Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2018

Mozambique Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2020

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Mozambique Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2019

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Mozambique Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2019

Mozambique Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2021

Mozambique Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2022

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Mozambique Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2018

Mozambique Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2020

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Mozambique Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2018