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UID:pretalx-global-workshop-2026-8YNN39@pretalx.earthmonitor.org
DTSTART;TZID=Europe/Amsterdam:20261007T183500
DTEND;TZID=Europe/Amsterdam:20261007T184000
DESCRIPTION:Flash flood events are increasing in frequency and intensity in
  Mediterranean regions\, requiring rapid\, reliable\, and scalable monitor
 ing approaches to support emergency response and climate adaptation. Earth
  Observation (EO) offers a powerful means to provide timely spatial intell
 igence\; however\, single-sensor approaches remain limited by cloud cover\
 , revisit frequency\, and data latency. This work presents an automatic\, 
 multi-sensor\, modular\, and open-source flood mapping framework designed 
 to deliver actionable information for emergency responders through near-re
 al-time flood detection coupled with a first-pass impact assessment.\nThe 
 proposed methodology integrates Synthetic Aperture Radar (Sentinel-1) and 
 multispectral imagery (Sentinel-2 and Landsat 8) with ancillary geospatial
  datasets within a unified processing pipeline. A change detection approac
 h is applied to pre- and post-event observations\, followed by automated t
 hresholding and morphological filtering to generate consistent flood exten
 t maps. To reduce noise sensitivity\, outputs from multiple sensors are th
 en fused at the pixel level to generate flood extent\, severity\, and dama
 ge assessment maps. \nThe framework was validated against ground-truth dat
 a from the October 2024 flash flood event in Valencia\, with results clear
 ly demonstrating the value of automated multi-sensor data fusion by increa
 sing the likelihood of acquiring usable observations by up to ~60%. This m
 odular architecture is fully reproducible and designed for extensibility\,
  enabling the integration of additional sensors and seamless deployment wi
 thin open EO ecosystems and distributed data infrastructures.
DTSTAMP:20260624T084807Z
LOCATION:Aula Magna
SUMMARY:Data fusion for flood monitoring - Ana Linares Barrio
URL:https://pretalx.earthmonitor.org/global-workshop-2026/talk/8YNN39/
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