Democratic Republic of the Congo environment data

**ADAM ID: **FL-20250415-COD-00 A flood occurred on Apr 15 2025 in Congo, The Democratic Republic of the. It affected an estimated 182007 people and 2603 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.

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.

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: 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: FL20250408COD** This application provides flood impact assessment in Kinshasa, Democratic Republic of the Congo The boundaries and names shown, and the designations used on this map do not imply official endorsement or acceptance by the United Nations. The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

The Soil and Terrrain database of Central Africa (SOTERCAF, version 1.0) was compiled at scale 1:2 million for the Democratic Republic of Congo and at scale 1:1 million for Rwanda and Burundi. The SOTERCAF compilation has been a joint collaboration of the Soil Science Laboratory of the University of Ghent, Belgium and ISRIC - World Soil Information, Wageningen under contract with the Food and Agriculture Organisation of the United Nations. Further assistance is provided by the Department BIOT of the Hogeschool Gent, the Royal Museum for Central Africa (Tervuren) and data holders in the Democratic Republic Congo, Burundi and Rwanda. The project started in September 2005 by deriving physiographic units from SRTM grid data based on SOTER landform definitions. The database was completed in July 2006 after combining the physiographic layer with the lithology and soils layer. The border harmonization with the SOTERSAF database was finalized November 2006. SOTERCAF forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts.

This harmonized set of soil parameter estimates for Central Africa, comprising Burundi, the Democratic Republic of the Congo and Rwanda, was derived from the Soil and Terrain Database for Central Africa (SOTERCAF ver. 1.0) and the ISRIC-WISE soil profile database, using standardized taxonomy-based pedotransfer (taxotransfer) procedures. The land surface of Central Africa, comprising some 2.4 million km2, has been characterized using 244 unique SOTER units, corresponding with 504 polygons. Each SOTER unit may consist of up to 6 soil components; each of these has been characterized by a representative profile. The main soil units mapped for the region have been characterized using 167 real profiles, selected by soil experts as being regionally representative for these units. The associated soil analytical data have been derived from soil survey reports. Gaps in the measured soil data have been filled using a scheme of using a step-wise procedure that uses taxotransfer rules. These rules were developed using some 5672 soil profiles, held in the ISRIC-WISE database, having similar FAO soil unit names as those reported in the primary SOTERCAF database. Parameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, C/N ratio, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments (less than 2 mm), and available water capacity (-33 kPa to -1.5 MPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and analyses of global environmental change. The current parameter estimates should be seen as best estimates based on the current selection of soil profiles and data clustering procedure. Taxotransfer rules have been flagged to provide an indication of the possible confidence in the derived data.