Test and develop high resolution mapping and modelling methods to support inter-censal population estimates

测试和开发高分辨率绘图和建模方法以支持普查间人口估计

• 批准号: 2891457
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2891457
• 关键词: Test; develop; resolution; mapping; modelling

Sierra Leone has recently concluded its georeferenced mid-term census that collected up-to-date, accurate andcomplete demographic information on its residents. This provides a unique opportunity to compare and validatedifferent types of small area population estimation models and therefore inform approaches to producingintercensal estimates going forward. By utilizing the full georeferenced mid-term census results, the proposedresearch will:(i) Test various population estimation methods using sub-samples from the mid-term census:a. test the performance of different sample design strategies in 'bottom-up' model applications (e.g., stratification,weighted, etc.)b. quantify the performance of such 'bottom-up' estimates against the mid-term census when using routinelycollected surveys as inputsc. develop and test a wide range of geospatial data (i.e., covariates) and identify the best suited for populationestimation. This will include the exploration of machine learning options to model building usage (residential/nonresidential,and other characteristics) using high-resolution satellite imagery, building footprint data and labels anddata from various surveys.d. identify the best method to estimate age/sex structures at high resolution,(ii) test different types of sub-national projection methods from the last census to examine which work mostaccurately and what ancillary datasets are most valuable, and(iii) compare various top-down disaggregation of population projections with the geo-referenced census data.

塞拉利昂最近完成了地理参考中期人口普查，收集了有关其居民的最新、准确和完整的人口信息。这为比较和验证不同类型的小区域人口估计模型提供了一个独特的机会，从而为今后产生普查间估计的方法提供信息。通过利用完整的地理参考中期人口普查结果，建议的研究将：(i)使用中期人口普查的子样本检验各种人口估计方法；测试不同样本设计策略在“自下而上”模型应用中的性能（例如，分层、加权等）。当使用例行收集的调查作为输入时，量化这种“自下而上”的估计与中期人口普查的表现。开发和测试广泛的地理空间数据（即协变量），并确定最适合人口估计的数据。这将包括探索机器学习选项，使用高分辨率卫星图像、建筑足迹数据和标签以及来自各种调查的数据来模拟建筑使用（住宅/非住宅和其他特征）。确定以高分辨率估计年龄/性别结构的最佳方法，（ii）测试上次人口普查中不同类型的次国家预测方法，以检查哪种方法最准确，哪些辅助数据集最有价值，以及（iii）将各种自上而下的人口预测分类与地理参考人口普查数据进行比较。