electricsheepafrica/africa-education-cameroon

该数据集提供了喀麦隆医疗和教育服务空间可达性的深入见解。它使用免费开放工具（如openrouteservice）和开放数据源（主要是OpenStreetMap）创建。为了评估教育和医疗的可达性，数据集使用旅行时间等时线——代表汽车在给定时间或距离内可到达区域的多边形，并与WorldPop人口数据（提供100米分辨率估计）叠加。这允许计算从医院服务10到120分钟时间间隔内以及从学校5到50公里距离间隔内的人口。分析单位由geoboundaries国家边界定义，并在可用时在更细的管理级别（ADM 1–4）总结结果。数据集包含以下变量：名称（地区或国家名称）、ISO（ISO3国家代码）、ID（管理单位的唯一标识符）、国家（ISO3国家代码）、管理级别（单位的管理级别）、类别（服务类别——教育、医院或初级医疗）、范围类型（用于集水区的方法——距离或时间）、范围（用于生成多边形的距离（米）或时间（秒））、人口（指定范围内的总人口）、学龄人口（范围内的学龄个体数量）、学龄人口份额（学龄人口的累计百分比）、学龄人口间隔（当前距离带中新增的学龄人口）、学龄人口间隔份额（当前间隔中新学龄人口的比例）、人口份额（总人口的累计百分比）、人口间隔（当前距离带中新增的人口）、人口间隔份额（当前间隔所代表的总人口份额）。数据集是HeiGIT在HDX上众多导出之一，用于机器学习和分析目的。

This dataset provides insights into spatial accessibility to healthcare and education services across Cameroon. It has been created using free and open tools such as openrouteservice and open data sources, primarily OpenStreetMap (OSM). To assess accessibility to education and healthcare, we use travel-time isochrones—polygons representing areas reachable within a given time or distance by car. We overlay these isochrones with WorldPop population data, which provides 100m-resolution estimates. This allows us to calculate the population within time intervals from 10 to 120 minutes away from hospital services and distance intervals from 5 to 50 km away from schools. The unit of analysis is defined by geoboundaries country borders, and where available we also summarise results at finer administrative levels (ADM 1–4). The dataset includes variables such as name (region or country name), iso (ISO3 country code), id (unique identifier for the administrative unit), country (ISO3 country code), admin_level (administrative level of the unit), category (service category—education, hospitals, or primary_healthcare), range_type (method used for the catchment zone—distance or time), range (distance in meters or time away in seconds from schools used to generate the polygon), population (total population within the specified range), school_age_population (number of school-age individuals within the range), school_age_population_share (cumulative percentage of school-age population), school_age_population_interval (incremental school-age population added in the current distance band), school_age_population_interval_share (proportion of new school-age population in the current interval), population_share (cumulative percentage of total population), population_interval (incremental population added in the current distance band), and population_interval_share (share of the total population represented by the current interval). This dataset is one of many HeiGIT exports on HDX, intended for machine learning and analytical purposes.