Access to drinking water and sanitation is essential for health and well-being, yet major disparities remain, especially in data-scarce regions such as Africa. SDG 6 aims for universal access, but current monitoring relies on costly, infrequent, and spatially uneven surveys and censuses with long reporting delays. This study develops a scalable remote-sensing framework to estimate piped water and sewage system access at approximately 2.56 km resolution using Sentinel-2 imagery, Afrobarometer survey responses, 30 m population data, and DINO self-supervised Vision Transformer features. The best model achieves AUROC values of 91.54% for piped water and 93.24% for sewage access. Across 50 African countries, population-weighted estimates strongly align with WHO/UNICEF JMP statistics for piped water ($R^2 = 0.92$) and show meaningful agreement for sewage access ($R^2 = 0.72$). In countries without Afrobarometer coverage, MAEs are 9.5% and 10.7%, with estimates within 15% of JMP values for 121.4 million and 159.7 million people, respectively. A Nigeria case study across 767 Local Government Areas (LGAs) shows that the framework reveals fine-scale environmental inequality. The largest no-access burdens reach 1.155 million people for piped water and 1.452 million for sewage, 7.9 and 8.3 times the median LGA burden, while top-decile no-access thresholds of 0.805 and 0.952 indicate that deprivation is widespread. These findings show that DINO-based satellite models can complement household surveys with low-cost, spatially detailed evidence for SDG 6 monitoring, infrastructure targeting, and environmental equity assessment.

翻译：安全饮用水和卫生设施对健康福祉至关重要，但在非洲等数据匮乏地区仍存在显著差距。联合国可持续发展目标6（SDG 6）旨在实现全民享有这些服务，但当前监测依赖成本高昂、频次有限、空间分布不均且报告延迟的普查和抽样调查。本研究开发了一种可扩展的遥感框架，利用哨兵二号影像、非洲晴雨表调查数据、30米人口分布数据以及DINO自监督视觉Transformer特征，以约2.56公里分辨率估算管道供水和污水系统覆盖率。最优模型在管道供水和污水接入任务上分别达到91.54%和93.24%的AUROC值。在50个非洲国家中，人口加权估算值与世界卫生组织/联合国儿童基金会联合监测计划（JMP）的管道供水统计数据高度吻合（$R^2 = 0.92$），对污水接入也有显著一致性（$R^2 = 0.72$）。在无非洲晴雨表覆盖的国家，平均绝对误差分别为9.5%和10.7%，对应1.214亿和1.597亿人口的估算值偏离JMP数据不超过15%。尼日利亚767个地方政府区域的案例研究表明，该框架能揭示精细尺度的环境不平等：管道供水与污水服务缺口最大的区域分别达115.5万和145.2万人，为地方政府区域中位缺口的7.9倍和8.3倍；而最高十分位无服务阈值分别达到0.805和0.952，表明剥夺现象普遍存在。这些发现证明，基于DINO的卫星模型能以低成本提供高空间分辨率的证据，补充家庭调查数据，用于SDG 6监测、基础设施靶向部署和环境公平评估。