Democratic Republic of the Congo GIS data

This dataset is showing the health boundaries data of the Democratic Republic of Congo.

This database shows sea and air entry points of Kinshasa city. This data was updated by Maluku commune Red Cross volunteers during the training on the usage of OSMTracker, an opensource mobile phone GPS application for the CP3/IFRC program.

This dataset shows the schools facilities in the target CP3 program health areas of the DRC Red Cross. CP3 program is deployed in 4 health zones find in 2 provinces, Kinshasa and Kongo Central province.

Les 26 divisions provinciales de la santé (DPS) de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The 26 provincial health divisions of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.

Les limites "sanitaires" des 145 territoires et 19 villes de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The "health" limits of the 145 territories and 19 cities of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.

Communes urbaines (58) de 11 villes de la République démocratique du Congo, extraites de la base de données OpenStreetMap. Urban communes (58) from 11 cities of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.

Territoires et villes principales des provinces du Sud et du Nord-Kivu, en République démocratique du Congo, extraits de la base de données OpenStreetMap. Territories and main cities of South and North Kivu provinces, in the Democratic Republic of the Congo, extracted from the OpenStreetMap database.

Formations sanitaires (FoSa) de la ville de Goma et du territoire de Nyiragongo répertoriées dans OpenStreetMap au 27 mai 2021. Health structures in Goma city and Nyiragongo territory , in the Democratic Republic of the Congo, extracted from the OpenStreetMap database, as of May 27th, 2021.

Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap et converties suivant le schéma attributaire du Référentiel Géographique Commun de la RDC dans la mesure du possible. Cette page inclut actuellement les limites des cellules d'animation communautaire et une sélection de points d'intérêt localisés dans l'aire de santé Butsili. Les données étant en cours de mise à jour, elles sont donc susceptibles de connaître des modifications fréquentes. Elles sont publiées en version provisoire avec l'accord de la zone de santé en raison de la résurgence de la maladie à virus Ebola dans la région.

Tout le réseau des 44 routes nationales de la République démocratique du Congo, extrait de la base de données OpenStreetMap. Les données sont disponibles dans un jeu de données reprenant les 44 relations (chaque route nationale correspondant à un objet), ou reprenant chacun des segments de chacune des routes nationales avec ses propriétés spécifiques.

Localités Les localités de la RDC sont issues au de la comparaison de deux bases pour lesquelles les doublons ont été supprimés. Des relevés GPS ainsi que des numérisation sur images satellites ont été réalisés par différentes acteurs présent en RDC et viennent compléter le fichier initial. Des ajouts se font régulièrement (2010). Sourced from Référentiel Géographique Commun

Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap, pour la province du Nord-Kivu. Ce dossier reprend actuellement des données publiées dans un contexte de formation et révision.

Les 519 zones de santé (ZS) de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The 519 health zones of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.

Cette première version des coulées de lave résultant de l'éruption du volcan Nyiragongo du 22 mai 2021 sont des données approximatives. Elles ont été numérisées sur base des données Sentinel-1 du 25 mai 2021. [UPDATE 27/05/2021] Une version légèrement adaptée au niveau de l'extrémité Sud de la coulée ayant atteint Buhene est désormais disponible. La mise à jour à été effectuée sur base d'une image Maxar haute-résolution du 25 mai 2021.

**UNOSAT code FL20221125COD** Cette carte illustre l'étendue des eaux de surface détectées par satellite en utilisant de l'imagerie satellite VIIRS au-dessus des provinces de l'Equateur, du Nord-Ubangi et du Sud-Ubangi (République Démocratique du Congo) entre le 1er et le 28 novembre 2022. Dans la zone analysée d'environ 210 000 km², un total d'environ 6 800 km² de terres semblent être inondées. L'étendue des eaux de surface semble être plus petite d'environ 4 000 km² comparé à la période du 1er au 30 novembre 2019. D'après les données démographiques de Worldpop et les eaux de surface détectées par satellite, environ 245 000 personnes sont potentiellement exposées ou vivent à proximité de zones inondées. Prière de bien vouloir noter que ceci est une analyse préliminaire qui n'a pas été validée sur le terrain. Merci d'envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

**UNOSAT code FL20221125COD** Cette carte illustre l'étendue des eaux de surface détectées par satellite en utilisant de l'imagerie satellite VIIRS dans la province de Tshopo (République Démocratique du Congo) entre le 24 novembre et le 05 décembre 2022. Dans la zone analysée d'environ 200 000 km², un total d'environ 1 600 km² de terres semblent être inondées. L'étendue des eaux de surface semble être du même niveau qu'entre les dates du 25 novembre au 05 décembre 2019. D'après les données démographiques de Worldpop et les eaux de surface détectées par satellite, environ 70 000 personnes sont potentiellement exposées ou vivent à proximité de zones inondées. Prière de bien vouloir noter que ceci est une analyse préliminaire qui n'a pas été validée sur le terrain. Merci d'envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

**UNOSAT code FL20230508COD, GDACS Id: 1101981** This map illustrates satellite-detected landslides/mudflow-related impact in Kalehe Territory, Sud-Kivu Province, Democratic Republic of the Congo as observed from a Sentinel-2 image acquired on 7 May 2023. Within the analysed area of about 9,000 ha, 90 ha of landslide scars were 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).

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 FL20230508COD, GDACS Id: 1101981** Cette carte illustre l'étendue des glissements de terrain le 07 mai 2023 en Territoire de Kalehe, Province du Sud-Kivu, République Démocratique du Congo. Dans la zone analysée de 9,000 ha, environ 90 ha d'escarpements de glissements de terrain sont visibles. Ceci est une analyse préliminaire et n'a pas été validée sur le terrain. Merci d'envoyer vos commentaires au Centre Satellitaire des Nations Unies (UNOSAT).

**UNOSAT code FL20230508COD, GDACS Id: 1101981** This map illustrates the potentially damaged structures/buildings affected by landslides in Chabondo village, Kalehe Territory, Sud-Kivu Province, DR. of the Congo as detected from a Pleiades image acquired on the 09th May 2023. Within the extent of this map, at least 544 structures appear to be affected or potentially affected by landslides. 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: FL20231229COD** This map illustrates satellite-detected surface waters and landslide location in Kinshasa Province, Democratic Republic of The Congo, as observed from a WorldView-3 image acquired on 13 January 2024, at 10:36 local time. Within the analysed area of 130km2, approximately 4 km2 of land appear to be flooded and a landslide location observed. Within the analysed area 9,352 buildings are identified as potentially affected by the floods and landslide. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code: FL20211008COD** This map illustrates satellite-detected surface waters in Muvaramu village, Ituri province as observed from a Sentrinel-2 acquired on 04 October 2021. Within the analyzed area, waters appear to have slightly progressed inland since 27 January 2021. 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: FL20231229COD** This map illustrates satellite-detected surface waters and landslides in Kinshasa Province, Democratic Republic of The Congo, as observed from a Sentinel-2 image acquired on 28 December 2023, at 10:21 local time. Within the analysed area of 44,000 ha, approximately 3 ha of landslide scars are observed and about 460 ha of land appear to be flooded. Based on Worldpop population data, the detected surface waters and the landslide scar extent, about 25,000 people are potentially exposed or living close to landslide and flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230508COD, GDACS Id: 1101981** This map illustrates the potentially damaged structures/buildings affected by landslides in Nyabibwe Town, Kalehe Territory, Sud-Kivu Province, DR. of the Congo as detected from a Pleiades image acquired on the 09th May 2023. Within the extent of this map, at least 623 structures appear to be affected or potentially affected by landslides. 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).

This dataset is of simplified geometries from COD live services deployed September 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 September 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

**UNOSAT code: FL20211008COD** This map illustrates satellite-detected surface waters in Kasenyi town, Gethy Zone de Santé as observed from a Sentrinel-2 acquired on 04 October 2021. Within the analyzed area, the surface waters appears to have slightly progressed inland since 27 January 2021. 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).

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: VO20210523COD** This map illustrates the lava flow extent and the related geological information north of Goma airport, Nord-Kivu province, D.R. of the Congo as detected by satellite images acquired after the eruption of the Mount Nyiragongo on 22 May 2021. UNITAR-UNOSAT analysis used Sentinel-1 acquired on 25 May 2021, Sentinel-2 & Pleiades images acquired on 1 June 2021, at respectively 16:21 UTC, 08:30 UTC and 11:35 UTC, to extract the lava flow extent. Within this map, three vents have been identified along the hillside south of Nyiragongo caldera. In addition, about 10 km of fissures have been mapped and are mainly in NNE-SSW and NNW-SSE directions. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

**UNOSAT code: VO20210523COD** This map illustrates potentially affected structures and buildings in Nyiragongo district, Nord-Kivu province, DR Congo as detected by satellite image acquired after the 22 May 2021 Nyiragongo volcanic eruption. UNITAR-UNOSAT analysis used a Sentinel-1 image acquired on 25 May 2021, at 16:21 UTC, to extract the lava flow extent. Within the map extent, about 1,722 structures and the road about 18 km are potentially affected by the lava flow. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

**UNOSAT code: FL20191118COD** This map illustrates satellite-detected flooded structures along the Ubangui River over Zongo, Libenge Territory, Sud-Ubangui Territory in Democratic Republic of the Congo as observed from GeoEye-1 imagery acquired on 12 November 2019. UNITAR-UNOSAT has identified within the extent of this map 276 potentially flooded structures north-west of Zongo. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

**UNOSAT code: FL20191118COD** This map illustrates satellite-detected flooded structures along the Ubangui River over Libenge, Libenge Territory, Sud-Ubangui Territory in Democratic Republic of the Congo as observed from Pleiades imagery acquired on 15 November 2019. UNITAR-UNOSAT identified 22 potentially flooded structures west of Libenge, within the extent of this map. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

**UNOSAT code: FL20191118COD** This map illustrates satellite-detected flood waters along the Ubangi River over Libenge, Libenge Territory, Sud-Ubangi Province in Democratic Republic of the Congo as observed from Pleiades imagery acquired on 15 November 2019. 90 ha of potential flood waters have been identified in Libenge and its vicinity. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

**UNOSAT code: FL20191118COD** This map illustrates satellite-detected floodedwaters along the Ubangui River over Zongo, Libenge Territory, Sud-Ubangi Territory in Democratic Republic of the Congo as observed from GeoEye-1 imagery acquired on 12 November 2019. UNITAR-UNOSAT has identified 58 ha of potentially flood waters north-west of Zongo. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

**UNOSAT code: FL20191118COD** This map illustrates satellite-detected flooded waters along the Ubangui River over Mobayi-Mbongo,Mobayi-Mbongo Territory, Nord-Ubangi Province in Democratic Republic of the Congo as observed from SPOT 7 imagery acquired on 16 November 2019. UNITAR-UNOSAT has identified about 60 buildings/houses likely surrounded by waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

**UNOSAT code: FL20240919COD** This map illustrates satellite-detected surface waters in Ituri Province as observed from a Sentinel-2 image acquired on 18 Sep. 2024. Within the analysed area, about 15km² of lands appear to be affected with water increase. Based on Worldpop population data and the detected surface waters, about 2,300 people are potentially exposed to the water increase. 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).