Clean water and sanitation are essential for health, well-being, and sustainable development, yet significant global disparities persist. Although the United Nations' Sustainable Development Goal (SDG) 6 clearly defines targets for universal access to clean water and sanitation, limitations in data coverage and openness impede accurate tracking of progress in many countries. To bridge these gaps, this study integrates Afrobarometer survey data, satellite imagery from Sentinel-2, and advanced deep learning techniques using Meta's self-supervised Distillation with No Labels (DINO) model to develop a modeling framework for evaluating access to piped water and sewage systems across diverse African regions. The modeling framework achieved notable accuracy, with over 84% for piped water and 87% for sewage system access classification. When combined with geospatial population data, validation against official statistics from the United Nations Joint Monitoring Program demonstrated high concordance at the national scale (R2 of 0.92 for piped water access and R2 of 0.72 for sewage system access). The national-level estimates can represent SDG Indicators 6.1.1 and 6.2.1. This approach provides policymakers and stakeholders with an effective, scalable, and cost-efficient tool to pinpoint underserved areas requiring targeted intervention. The methodology developed herein can be adapted for assessing other infrastructure-related SDGs, promoting enhanced monitoring and informed decision-making towards achieving global sustainability objectives.

翻译：清洁水源与卫生设施对健康、福祉及可持续发展至关重要，但全球范围内的显著差距依然存在。尽管联合国可持续发展目标（SDG）6明确界定了实现全民清洁水源和卫生设施的目标，但许多国家在数据覆盖范围和开放性方面的局限性，阻碍了对进展的精确追踪。为弥补这些差距，本研究整合了Afrobarometer调查数据、Sentinel-2卫星影像以及Meta公司基于自监督无标签蒸馏（DINO）模型的先进深度学习技术，构建了一个评估框架，用于分析非洲不同地区管道供水和污水系统的接入情况。该建模框架取得了显著的准确率：对管道供水接入分类超过84%，对污水系统接入分类超过87%。与地理空间人口数据结合后，与联合国联合监测计划官方统计数据的全国尺度验证呈现高度一致性（管道供水接入R²=0.92，污水系统接入R²=0.72）。全国层面的估算结果可代表SDG指标6.1.1和6.2.1。该方法为政策制定者和利益相关者提供了有效、可扩展且经济高效的工具，以精准定位需要针对性干预的未充分覆盖区域。本研究所开发的方法可适用于评估其他与基础设施相关的SDG，从而推动更优的监测和基于信息的决策，助力实现全球可持续发展目标。