Population and age structure in Hungary: a residential preference and age dependency approach to disaggregate census data

We present a simple model to disaggregate age structured population census data to a 1-km grid for Hungary. A dasymetric approach was used to predict the spatial distribution of population in different age groups by distinguishing residential preferences (in relation to accessible social, economic and green amenities) for working age groups (15–29, 30–49 and 50–64) and population dependencies for children and the elderly (aged 0–14 and 65+). By using open-access land cover data and fine-level population census data as inputs, the model predicts the likely spatial distribution of population and age structure for Hungary in 2011. The resulting map and gridded data provide information to support spatial planning of residential development and urban infrastructure. The model is less data-demanding than most existing approaches, but provides greater power for describing population patterns. It can also be used to create scenarios of future demographic change.

本研究提出一款简易模型，可将匈牙利按年龄结构分组的人口普查数据分解至1公里网格尺度。本研究采用密度分区插值法（dasymetric approach），通过区分劳动年龄人口（15-29岁、30-49岁及50-64岁）与儿童、老年人口（0-14岁及65岁以上）的居住偏好（与可及性社会、经济及绿色公共设施相关）及抚养依赖特征，预测不同年龄组人口的空间分布。本模型以开放获取的土地覆盖数据与精细化人口普查数据作为输入，对匈牙利2011年的人口空间分布与年龄结构进行了预测。所生成的地图与网格数据集可为住宅开发及城市基础设施的空间规划提供数据支撑。相较于多数现有方法，本模型的数据需求更低，却能更精准地刻画人口分布格局。此外，该模型还可用于构建未来人口变化的情景模拟方案。