Editing Urban flood inundation extent (section)

== Monitoring and Measurement ==
Monitoring urban flood inundation extent relies on a combination of observational technologies and modeling approaches. Remote sensing platforms, particularly satellite-based Synthetic Aperture Radar (SAR), are widely used due to their ability to capture floodwater presence regardless of cloud cover and lighting conditions. SAR data enable mapping of flooded areas at high spatial resolution and frequent revisit intervals. Complementary data sources include optical satellite imagery, aerial photography, and ground-based sensors such as water level gauges and rain gauges.

Hydrodynamic flood models simulate water flow and accumulation in urban terrains, integrating topographic data, land cover, and drainage infrastructure information. Machine learning and deep learning methods have been increasingly applied to enhance flood extent mapping by assimilating multi-source data and improving classification accuracy. Institutions involved in urban flood monitoring include national meteorological and hydrological services, research organizations, and emergency management agencies.

Within the SIGNAL system, this phenomenon is treated as a defined environmental signal whose boundaries and measurement conventions are described below.