Leveraging Night-Time Lights (NTL) data to fingerprint the impact of the 2022 Indus floods

Abstract Floods are among the most damaging natural hazards, disrupting settlements, infrastructure, and livelihoods. While most flood-impact research focuses on inundation mapping, exposure, and post-disaster loss assessments, flood effects extend far beyond mapped flood zones, disturbing energy systems, transport networks, and supply chains, with recovery often uneven across socio-economic groups. Here, we demonstrate how satellite observations, using NASA’s Black Marble night-time lights (NTL) dataset, enable high-resolution monitoring of infrastructure disruption and recovery following large-scale flooding. Focusing on the 2022 Indus River floods in Pakistan, we identify a statistically significant decline in radiance beginning in June 2022 and persisting for 18 weeks—longer than the period of intense rainfall and extending beyond inundation extents derived from satellite imagery. Urban areas showed the largest radiance losses (80–100%) yet recovered faster than rural areas that experienced smaller declines, underscoring disparities in recovery trajectories. By integrating NTL data with radar-based flood extents, we show that cascading and compounding disruptions reach well beyond inundated areas. Our results highlight NTL’s value for real-time, socio-economically disaggregated monitoring of flood impacts and recovery, offering a scalable framework to support disaster response and resilience planning.