Zimbabwe GIS data

Point locations of educational facilities across Zimbabwe, including primary schools, secondary schools and other learning institutions. Each feature records the facility name, type and administrative location. Use this layer to map education access, identify underserved areas, plan school placement, and analyse catchment areas and travel distances to schools.

A 1 km population raster for Zimbabwe published by Orion Terrametrics. Each cell holds a population value for the year 2020.

Locations of seaports, harbours and maritime infrastructure in Zimbabwe. Includes commercial ports, fishing harbours and ferry terminals. Use this layer for maritime transport planning, trade logistics analysis, coastal zone management, and shipping route mapping.

Railway and rail transport network of Zimbabwe showing the extent and classification of rail infrastructure. Includes passenger and freight lines. Use this layer for rail transport planning, freight logistics analysis, infrastructure assessment, and multimodal transport mapping.

Third-level administrative divisions of Zimbabwe such as sub-districts or wards. Use this layer for fine-grained spatial analysis, community health planning, and detailed humanitarian response.

Zimbabwe administrative level 0-3 boundaries (COD-AB) dataset version 01. This dataset is structured into 3 levels: - Admin 1: 10 Province - Admin 2: 91 District - Admin 3: 1961 Ward Dates associated with this dataset: - 28 January 2025: dataset reviewed for accuracy and completeness - 11 September 2018: valid for use by the humanitarian community - 31 August 2018: last edit to the dataset before publishing - 31 August 2018: boundaries created by the source Contributed by [OCHA Regional Office for Southern and Eastern Africa (ROSEA)](https://data.humdata.org/organization/ocha-rosea). Quality assured, configured, and published by [OCHA Field Information Services (FIS)](https://data.humdata.org/organization/ocha-fiss) and [HDX](https://data.humdata.org/organization/hdx). Part of the dataset: [Global Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-global)

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

This map illustrates the satellite detected surface waters in Masvingo Province, Zimbabwe, as observed from the Sentinel-1 data imageries acquired on 12 and 24 March 2019. Within the analysis extent, over Manicaland Province, 84,500 ha of surface waters were observed the 12 March 2019. and about of 288,500 ha of surface waters were observed the 24 March 2019. It represents an icrease of 29 %. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data (pre-event) : Sentinel-1 Imagery date: 12 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Satellite data (post-event) : Sentinel-1 Imagery date: 24 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Boundary data: OCHA ROSEA Water body & waterway: COD Analysis : UNITAR-UNOSAT Production: UNITAR - UNOSAT

This map illustrates the satellite detected surface waters in Mashonaland East Province, Zimbabwe, as observed from the Sentinel-1 data imageries acquired on 12 and 24 March 2019. Within the analysis extent, over Manicaland Province, 108,780 ha of surface waters were observed the 12 March 2019. and about of 469,680 ha of surface waters were observed the 24 March 2019. It represents an icrease of 23 %. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data (pre-event) : Sentinel-1 Imagery date: 12 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Satellite data (post-event) : Sentinel-1 Imagery date: 24 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Boundary data: OCHA ROSEA Water body & waterway: COD Analysis : UNITAR-UNOSAT Production: UNITAR - UNOSAT

This map illustrates the satellite detected surface waters in Manicaland Province, Zimbabwe, as observed from the Sentinel-1 data imagery acquired on 12 and 24 March 2019. Within the analysis extent, over Manicaland Province, 164,130 ha of surface waters were observed the 12 March 2019. and about of 406,600 ha of surface waters were observed the 24 March 2019. It represents an increase of 40 %. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data (pre-event) : Sentinel-1 Imagery date: 12 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Satellite data (post-event) : Sentinel-1 Imagery date: 24 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Boundary data: OCHA ROSEA Water body & waterway: COD Analysis : UNITAR-UNOSAT Production: UNITAR - UNOSAT

Zimbabwe Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2022

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The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Zimbabwe Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2015

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Zimbabwe Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2015

Zimbabwe Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2021

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Zimbabwe Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2012

Artisanal mining site visits in the Runde river valley, Zimbabwe

The ICA is a process of consultations supported by mapped-out data that produces a strategic plan describing where different combinations of programme themes are appropriate to achieve goals of reducing food insecurity and climate related shock risk. The ICA combines multi-year food security trends with natural shock risk data to highlight sub-national areas where different programme strategies make sense. Food security trend maps shows areas where safety nets can address regular food insecurity, and others where shocks make recovery more important. Climate-related natural shock risk maps show where DRR, preparedness and early warning efforts can complement food-security objectives. Atop this core foundation, mapped data on subjects including nutrition, gender, livelihoods and resilience can enrich theme-level strategic planning in which all pieces work together. The full group of ICA partners discuss these analytical results to arrive at strategic programmatic directions.

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic 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: amenity - Part of the country exports on HDX by HOT