Capturing Peak Flood Conditions from Space: Empirical Revisit Requirements and Observational Gaps

Floods are among the most widespread and destructive natural hazards globally. They cause loss of life, damage buildings and critical infrastructure, disrupt transportation and supply chains, and impact agricultural productivity, with cascading consequences for food and water security. Near real time flood information is essential for emergency response and coordination of relief operations, while retrospective flood observations are needed by governments, humanitarian organizations, and the insurance sector to evaluate event severity, quantify damages, and improve preparedness and risk reduction. Despite major progress in flood remote sensing, a persistent limitation is that satellite-based flood products often provide an opportunistic view of inundation that does not coincide with maximum impacts. Peak flood conditions are transient, spatially heterogeneous in timing, and frequently asynchronous across a single event, making them unlikely to be observed in any single image acquisition.

Earth-observing satellite missions provide broad spatial coverage, but publicly available systems typically undersample flood evolution due to revisit constraints and the availability of usable observations. Optical missions can be severely constrained by clouds and precipitation during storms, while single-platform SAR missions, though all-weather, can still have multi-day revisit times depending on acquisition planning and orbit geometry. In practice, time gaps of days to weeks can occur between observations at a given location, limiting the ability to characterize peak inundation extent and the duration of near-peak conditions.

Here we present a data-driven assessment of observational requirements and remaining gaps for capturing near-peak flood conditions, and we evaluate how different satellite constellations perform against these requirements. The analysis is based on global flood map products generated by ICEYE during 2023–2025, complemented by a rich archive of multi-sensor satellite imagery, social media observations, river gauge records, and field measurements for event validation and timing constraints. We discretize flood evolution into a hexagonal (H3) grid and intersect time-stamped extents with grid cells to derive cell-scale inundation time series. Peak timing is constrained using hydrographs from multiple gauges per event. For each H3 cell, we estimate (i) maximum inundation extent, (ii) the timing of peak inundation, and (iii) the duration of near-peak conditions, yielding a spatially explicit “observability window” for peak impacts.

Using these empirically derived near-peak windows, we quantify the revisit cadence required to observe peak conditions with high likelihood and compare the resulting requirements with observation opportunities from public missions (Sentinel-1/2 and Landsat-8/9). We then assess the extent to which a large constellation of small imaging SAR satellites, exemplified by ICEYE, can close the remaining gaps in near-peak observability across diverse flood regimes, landscapes, and event dynamics. The resulting framework provides a transferable approach for evaluating current and planned satellite constellations for flood response and risk assessment, with direct implications for acquisition strategies and the design of future observing systems.