Advances in online computing platforms and satellite sensor technologies enable unprecedented uptake of EO products

Since the early seventies, it has been known that satellite images can add value to mapping and monitoring floods. With the early launches of the Landsat series, followed in the early eighties and nineties by synthetic aperture radar (SAR) missions on SIR-B, ERS-1 and RADARSAT-1 with their all-weather and day and night capabilities considerably expanded the potential of flood mapping from space. Since then, the world of open-access Earth Observation (EO) has grown considerably and available data to inform about floods and assist flood disasters from local to global scales have proliferated.

This EO data proliferation coupled, in recent years, with complementing data from drones, IOT sensors and significant progress in online cloud computing platforms and interoperability has led to a massive amount of progress in both geospatial technology development and better actionable products and services based on EO. In the context of floods, machine learning has started to enable onboard satellite mapping, and reconstructing flooded area under cloud cover in optical images. In addition, recent scientific progress in SAR signal coherence processing is enabling the mapping of flooded buildings in urban areas. Online cloud computing platforms can now be used to upscale such flood mapping applications over entire regions, countries or even continents with the click of a button.

Using several use case illustrations, this paper will present some major historical breakthroughs in EO-based flood mapping before presenting recent technological advances in rapidly mapping rural and urban flooding across various spatial scales.