3iSolution

The Ethiopia Market Center dataset provides comprehensive information on market centers across Ethiopia. It includes spatial data that outlines the locations and attributes of these centers, facilitating analyses related to trade, commerce, and economic planning. Detailed information in Ethiopia Market Center

This database contains regional estimates of Facebook users based on data from the Facebook Marketing API. It includes information on the number of individuals aged 18 and older who have accessed Facebook in the past month, with data separated by region. These estimates are intended for trend identification and triangulation purposes and are not designed to match official census data or other government sources. This data can be used as a proxy of internet access. It should be noted that there could be duplicates across different regions, and the data is anonymized by Meta.

The dataset available at the Ethiopian Health Data Analytics and Visualization Hub provides information on under-five mortality rates across various regions (Adm 1) in Ethiopia from 1990 to 2020.

This dataset represents populated places in Ethiopia at the locality level, including villages, kebeles, towns, and other administrative divisions. Each entry is associated with XY coordinates and is integrated with Ethiopian administrative boundaries. The data originates from the National Geospatial-Intelligence Agency (NGA) and is accessible through their GeoNames platform(https://geonames.nga.mil/geonames/GNSData/).The dataset includes various types of populated areas such as: villages, kebeles and towns. This dataset is crucial for various applications, including urban planning to assist in the development of infrastructure and services based on population distribution, for research, and on disaster management to support humanitarian efforts by identifying populated areas during crises.

This dataset includes the spatial locations of health facilities across Ethiopia, along with their associated attribute information.

This dataset contains the population distribution of primary and secondary schools in Ethiopia, disaggregated by sex.

This dataset encompasses a collection of water points across Ethiopia, each annotated with administrative region tags (Admin 1, Admin 2, and Admin 3) to facilitate detailed geographic analysis. Sourced as secondary data from mWater, the dataset compiles information from multiple sources collected at various times. It provides insights into water accessibility, infrastructure types, and management across different regions. However, users are advised to exercise caution as the dataset may include water points that are no longer available or may omit new ones due to the nature of data collection. The degree of confidence in the accuracy and completeness of the data is moderate, reflecting the variability in source data and the dynamic nature of water point status. This resource is particularly useful for stakeholders in humanitarian response, development planning, and resource management, offering a broad overview but requiring validation for precision-critical applications.

This dataset contains commonly observed spelling variations of woredas and zones as identified in reports from humanitarian partners. These variations have been standardized and aligned with the official P-codes issued by OCHA in 2024 to ensure consistency and accuracy in data reporting and analysis.

[Initial analysis] The database contains information about buildings identified by Google outside of settlements recognized by GRID3. It serves as a proxy for identifying potential new settlements or areas of urban growth. The analysis incorporates two levels of clustering: one at a distance of 500 meters and another at 100 meters. The 500-meter clustering helps identify broader areas where multiple buildings are concentrated, potentially indicating the presence of a new settlement or an expansion of an existing one. This distance threshold allows for the initial identification of potential new settlement areas. The 100-meter clustering provides a more granular view, highlighting tighter clusters of buildings within the broader 500-meter areas. This finer level of clustering aids in distinguishing individual settlement units or neighborhoods within the larger potential settlement areas. By combining these two levels of clustering, the database facilitates a comprehensive analysis of potential new settlements or urban growth areas. It enables researchers, urban planners, and policymakers to identify and prioritize areas for further investigation, resource allocation, or development planning.

The GRID3 ETH - Settlement Extents v3.0 consists of a geographic representation of settlements in Ethiopia. Data inputs and methodology are described in data release notes available at GRID3 ETH - Settlement Extents v3.0 3iS has enhanced the settlement dataset by integrating administrative attributes from a shapefile at the Admin 3 level. This process involved associating settlements with the corresponding administrative divisions, including the following attributes: Admin 1 (Region) Names and P-codes: Identifying the broader regions where settlements are located. Admin 2 (Zone) Names and P-codes: Associating zones within regions to each settlement. Admin 3 (Woreda) Names and P-codes: Providing detailed locality-level information.

Para el año 2024 la estimación de las Personas en Necesidad (PiN) General y las Severidades intersectoriales para Colombia, se desarrolló siguiendo la metodología global JIAF 2.0 (Joint Intersectoral Analysis Framework, por sus siglas en inglés). Esto se relaciona con el análisis del documento del Plan de Respuesta a Prioridades Comunitarias – PRPC- 2024.