Data and code from: Foundations for digital twins: Spatially disaggregated synthetic populations of refugee and IDP settlements

Refugee and internally displaced people (IDPs) settlements are highly dynamic, with rapid changes to demographic and geographical structures. Knowledge of the population size, disaggregated by demographic attributes, is essential to informing humanitarian programming and settlement planning by humanitarian organisations. However, access to such data, when formal censuses of settlements have not been conducted creates a significant barrier. In this paper, we present a methodological framework for estimating settlement censuses by combining globally available satellite imagery with aggregate national census data from the population's country of origin generate a spatially disaggregated synthetic population of the settlement. The creation of such synthetic populations serves as a foundational layer for Digital Twins and simulation models, enabling: the integration of these disparate datasets at different levels of granularity; and provides decision-makers with a spatially disaggregated dyn..., , # Replication Code and Data: Spatially Disaggregated Synthetic Population Generation This repository contains the mock data, models, and complete 4-script computational pipeline to reproduce the methodology and results presented in our paper. The framework extracts shelter footprints from satellite imagery and generates a highly granular, spatially disaggregated synthetic population for non-monitored settlements. All processing scripts are bundled in the compressed archive: `RSOS-251315_code_data.zip`. ## Data Sources and Availability * **Refugee Camp Imagery:** The actual imagery used in the paper consists of four high-resolution satellite images of Zaatari camp (taken Sept 2013, Nov 2013, Jan 2014, and Mar 2014 from Maxar's WorldView-2 and GeoEye-1), obtained via the United Nations. * **Imagery Substitutes:** Due to commercial licensing and political sensitivities, the original high-resolution imagery cannot be published in this repository. Instead, lower-resolution substitutes fr..., ,难民与国内流离失所者（internally displaced people, IDPs）安置点具有高度动态性，人口结构与地理空间结构均会发生快速变化。掌握按人口属性细分的安置点人口规模数据，是人道主义组织开展人道主义项目规划与安置点规划的核心依据。然而，若未对安置点开展正式人口普查，获取此类数据将构成重大阻碍。 本文提出一套方法论框架，通过结合全球可获取的卫星影像与来源国的汇总式全国人口普查数据，生成安置点的空间细分合成人口（spatially disaggregated synthetic population）。此类合成人口可作为数字孪生（Digital Twins）与仿真模型的基础支撑层，实现不同粒度级别的异构数据集整合，并为决策者提供空间细分的动态…… # 复制代码与数据：空间细分合成人口生成 本仓库包含用于复现本文所述方法与结果的模拟数据、模型及完整的4脚本计算流程。该框架可从卫星影像中提取庇护所占地轮廓，并为非监测型安置点生成高粒度、空间细分的合成人口。 所有处理脚本均打包于压缩归档文件`RSOS-251315_code_data.zip`中。 ## 数据来源与可用性 * **难民营影像**：本文使用的实际影像为扎阿塔里难民营（Zaatari camp）的四张高分辨率卫星影像（拍摄时间为2013年9月、2013年11月、2014年1月及2014年3月，由Maxar旗下的WorldView-2与GeoEye-1拍摄），通过联合国渠道获取。 * **影像替代物**：受商业许可与政治敏感性限制，原始高分辨率影像无法在本仓库中发布。取而代之的是低分辨率替代影像……