Mozambique GIS data

Data produced under hydrological forecasting strategy where National Directorate of Water Resource Management (DNGRH) is one of the main actors of the Disaster Risk Reduction system, whose fundamental and prime task is the monitoring, forecasting and issuing early warnings about the risks ahead, resulting in the safeguarding of lives and property

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.

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates cumulative satellite-detected water using VIIRS in Mozambique between 27 to 31 March 2023. Within the cloud-free analyzed areas of about 600,000 km², a total of about 12,000 km² of land appear to be affected by flood waters. Water extent appears to have decreased by about 6,300 km2 since 21-25 March 2023. Based on Worldpop population data and the maximal flood water extent, ~650,000 people are potentially exposed or living close to flooded areas mainly located in Zambezia province with ~220,000 people and Sofala province with ~140,000 people. This preliminary analysis has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates cumulative satellite-detected water using VIIRS in Mozambique between 15 to 19 March 2023. Within the cloud free analyzed areas of about 600,000 km², a total of about 21,000 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the maximal flood water extent ~1,400,000 people are potentially exposed or living close to flooded areas. 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).

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates cumulative satellite-detected water using VIIRS in Mozambique between 21 to 25 March 2023. Within the cloud free analyzed areas of about 620,000 km², a total of about 18,300 km² of lands appear to be affected with flood waters. Water extent appears to have decreased of about 2,700 km2 since the 15-19 March 2023. Based on Worldpop population data and the maximal flood water extent, ~1,300,000 people are potentially exposed or living close to flooded areas mainly located in Zambezia province with ~480,000 people, Nampula province with ~210,000 people and Sofala province with ~ 210,000 people. 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).

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates satellite-detected surface waters in Zambezia Provinces, Mozambique as observed from a Sentinel-1 image acquired on 24 March 2023 at 05:00 local time and using an automated analysis with a machine learning method. Within the analyzed area of about 20,000 km2, about 330 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Maganja Da Costa, with ~10,000 people, Cidade De Quelimane with ~4,500 people, Inhassunge with ~ 3,500 people and Maquival with ~ 3,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Data produced under Thematic National Mapping and Cartographic updating Project at 1/250 000 scale implemented by National Cartography and Tele-detection Centre, Mozambique (CENACARTA).

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates satellite-detected surface waters in Sofala and Zambezia Provinces, Mozambique as observed from an RCM-2 image acquired on 13 Mar. 2023 at 05:01 local time. Within the analyzed area of about 24,000 km2, about 900 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in Zambezia province, including the district of Namacurra, with ~27,200 people, Nicoadala with ~22,500 people, and Cidade De Quelimane with ~ 15,600 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.

**UNOSAT code TC20230221MOZ, GDACS Id: 1000961** This map illustrates satellite-detected surface waters in Vilankulo Town, Inhambane Province, Mozambique as observed from a WorldView-3 image acquired 13 March 2023 at 09:40 local time and Pleiades image acquired 10 March 2023 at 09:48 local time. Within the analysis extent of about 2,800 hectares, approximately 35 hectares of land appear to be flooded. Based on Worldpop population data and the detected surface waters within the analysis extent, approximately 350 people are potentially exposed to or living close to flooded areas along with 71 structures and potentially affected road 290 meter by flooding. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is.

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.

**UNOSAT code: TC20220311MOZ** This map illustrates satellite-detected surface waters in Nante, Macuze & Namacurra posto, Zambezia Province, Mozambique as observed from a TerraSAR-X image acquired on 16 March 2022 at 05:10 local time. Within the analyzed area of about 12,400 ha, about 3,180 ha of lands appear to be flooded. Based on GRID3 settlement extent data and the detected surface waters, about 60 ha of the urban area is potentially exposed to floodwaters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: TC20220126MWI** This map illustrates satellite-detected surface waters in Malawi and Mozambique as observed from a Sentinel-1 image acquired on 26 January 2021 at 05:16 local time and using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 42,000 km2, about 610 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the districts of Chikwawa and Nsanje, Southern region, Malawi with respectively ~ 33,000 people and ~14,300 people, & in Cidade De Tete, Tete province, Mozambique with ~8,200 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: TC20220311MOZ** Este mapa ilustra água superficias detectadas por satélite nos distritos de Mossuril, Mogincual e Liúpo, Província de Nampula em Moçambique, no dia 13 de março, 2022, as 17:44 hora local. Dentro da área analisada de cerca de 14,000 km2, um total de 110 km2 aparece inundada. Baseado nos dados de população do Worldpop e na águas superficiais, cerca de 12,000 pessoas estão potencialmente expostos ou vivem perto das áreas inundadas. Esto sao análises preliminar e ainda não foram verificados no terreno. Por favor, envie comentários United Nations Satellite Centre (UNOSAT). Nota importante: Análises de inundaçãoes a partir de imagens radar podem subestimar a presença de águas acumuladas em áreas construídas e áreas de vegetação densa devido às propriedades de retrodifusão do sinal radar.

The Tropical Cyclone Dineo-17, is approaching Mozambique coasts and is expected to make landfall The 16 February 2017 in the central province of Inhambane. Potential heavy rainfall are also expected according microwave satellite sensors and might induce flooding in the affected areas. This report provides an analysis on the potentially exposed population per wind speed zones in Mozambique. According to our analysis approximately 250,000 people in Mozambique may be exposed to over 120km/h sustainable wind speeds and 59,000 people might be exposed to 90km/h wind speed. About 1,160,000 people might be exposed to moderate winds of 60km/h.

This data illustrates the satellite detected surface waters in Manica, Sofala, and Tete Provinces in Mozambique, as observed from Sentinel-1 imagery acquired on 13, 14, 19 and 20 March 2019.

This map illustrates satellite-detected surface waters in Tete and Zambezia province, Mozambique as observed from Sentinel-1 imagery acquired on 7 April 2019. Within the analysed extent of about 7,800 sq km, a total about 100 sq km of lands appear to be flooded as of 7 April 2019. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite Data (Post): Sentinel-1 Imagery Date (1): 7 April 2019 Imagery Date (2): 20 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA

This map illustrates the cumulative satellite-detected surface waters in central provinces of Mozambique and particularly the Sofala province and its surroundings, as observed from the Sentinel-1 imagery acquired between 13 & 26 March 2019. Within the analysis extent. over Sofala and Manica provinces, a total of 170,000 km2 of surface imagery were analyzed and about 10,000 km2 of lands experienced floods within this period. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data : Sentinel-1 Imagery date: 13-14-19-20-26 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 satellite-detected flood waters over Save River in Mozambique as observed from the Radarsat-2 images acquired on 17 February 2017 and 05 February 2017. A decrease of surface waters was observed in the 17 February 2017 image compared to the 05 February 2017 image along the Save river. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Gaza and Maputo provinces, Mozambique, as observed from a Sentinel-1 images acquired on 16 March 2024 at 05:19 local time (03:19 UTC). Within the analyzed areas of about 5000 km², a total of about 67 km² of lands appear to be flooded. 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).

**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Maputo province, Mozambique, as observed from a Sentinel-1 images acquired on 23 March 2024 at 05:19 local time (03:19 UTC). Within the analyzed areas of about 950 km², a total of about 10 km² of lands appear to be flooded. 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).

**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Maputo province, Mozambique, as observed from a Sentinel-1 images acquired on 27 March 2024 at 18:23 local time (16:23 UTC). Within the analyzed areas of about 2,000 km², a total of about 45 km² of lands appear to be flooded. 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). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: TC20220311MOZ** Este mapa ilustra água superficias detectadas por satélite nos distritos de Mossuril, Mogincual e Liúpo, Província de Nampula em Moçambique, no dia 15 de março, 2022, as 05:10 hora local. Dentro da área analisada de cerca de 1485 km2, um total de 237 km2 aparece inundada. Baseado nos dados de população do Worldpop e na águas superficiais, cerca de 22,620 pessoas estão potencialmente expostos ou vivem perto das áreas inundadas. Esto sao análises preliminar e ainda não foram verificados no terreno. Por favor, envie comentários para o Centro de Satélites das Nações Unidas (UNOSAT). Nota importante: Análises de inundaçãoes a partir de imagens radar podem subestimar a presença de águas acumuladas em áreas construídas e áreas de vegetação densa devido às propriedades de retrodifusão do sinal radar.

**UNOSAT code: TC20220124MOZ** This map illustrates satellite-detected surface waters in Malawi and Mozambique as observed from a Sentinel-1 image acquired on 02 February 2022 at 10:04 local time. The flood analysis were carried out by using an automated analysis with Artificial Intelligence based methods. Within the analyzed area of about 145,978 km2, about 859 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the districts of Mutarara, Cidade de Quelim and Morrumbala with respectively ~ 33,000 people, ~ 11,000 people, and with ~16,600 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: TC20241212MOZ, GDACS ID: 1001131** This map illustrates affected structures in Murrebue Posto, Mecufi District, Cabo Delgado Province as observed from a Pleiades satellite image acquired on 16 December 2024 at 07:58 Local Time. Within the analysed area, UNOSAT identified 3,367 destroyed structures and 613 damaged structures amongst a total of 3,982 structures observed. 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).

**UNOSAT code: TC20241212MOZ, GDACS ID: 1001131** This map illustrates affected structures in Mecufi Posto, Mecufi District, Cabo Delgado Province as observed from a Pleiades satellite image acquired on 17 December 2024 at 07:51 Local Time. Within the analysed area, UNOSAT identified 2,433 destroyed structures and 1,684 damaged structures amongst a total of 4,118 structures observed. 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).

**UNOSAT code: FL20250121MOZ** Este mapa ilustra a água detectada por satélite nos Distritos de Mossuril e Ilha de Moçambique, Província de Nampula, usando imagens satélite tirada no dia 18 de janeiro de 2025 às 09:34, horário local. Dentro da área analisada de aproximadamente 4.600 km², estima-se que 60 km² de terra tenham sido afetados pelas águas das enchentes. Com base nos dados demográficos espaciais do WorldPop, aproximadamente 9.000 pessoas estão expostas ou morando perto das áreas inundadas. Essa é uma análise preliminar e ainda não foi validada em campo. Envie comentários sobre o solo para o Centro de Satélites das Nações Unidas (UNOSAT).

**UNOSAT code: TC20250308MOZ, GDACS ID: 1001154** This map shows the locations where damage was detected based on a very high resolution satellite image collected 18 March 2025 when compared to very high resolution imagery by Airbus from October 2023 and February 2024 (south only), available through Google Earth Pro. Between October 2023 and March 2025, multiple cyclones have passed over Île de Mozambique. Across the Île de Mozambique, 78 damaged buildings were detected and accumulations of sand indicative of prior flooding were observed on roads and in public spaces. 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).

A 100 m spatial resolution geotiff of motorised 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 driving speeds of local public transport options on all-weather roads/asphalt roads and walking speeds on all other 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

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 2015

Mozambique Current Situation 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 Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2014

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 2013