Articles | Volume 23, issue 10
https://doi.org/10.5194/nhess-23-3305-2023
https://doi.org/10.5194/nhess-23-3305-2023
Research article
 | 
23 Oct 2023
Research article |  | 23 Oct 2023

Sentinel-1-based analysis of the severe flood over Pakistan 2022

Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner

Related authors

A PRELIMINARY COMPARISON OF TWO EXCLUSION MAPS FOR LARGE-SCALE FLOOD MAPPING USING SENTINEL-1 DATA
J. Zhao, F. Roth, B. Bauer-Marschallinger, W. Wagner, M. Chini, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 911–918, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, 2023
COMPUTING GLOBAL HARMONIC PARAMETERS FOR FLOOD MAPPING USING TU WIEN’S SAR DATACUBE SOFTWARE STACK
M. Tupas, C. Navacchi, F. Roth, B. Bauer-Marschallinger, F. Reuß, and W. Wagner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 495–502, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022,https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022, 2022

Related subject area

Hydrological Hazards
Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024,https://doi.org/10.5194/nhess-24-2995-2024, 2024
Short summary
Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024,https://doi.org/10.5194/nhess-24-2953-2024, 2024
Short summary
Exploring the use of seasonal forecasts to adapt flood insurance premiums
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024,https://doi.org/10.5194/nhess-24-2923-2024, 2024
Short summary
Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024,https://doi.org/10.5194/nhess-24-2857-2024, 2024
Short summary
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024,https://doi.org/10.5194/nhess-24-2817-2024, 2024
Short summary

Cited articles

Bauer-Marschallinger, B., Cao, S., Tupas, M. E., Roth, F., Navacchi, C., Melzer, T., Freeman, V., and Wagner, W.: Satellite-Based Flood Mapping through Bayesian Inference from a Sentinel-1 SAR Datacube, Remote Sens., 14, 3673, https://doi.org/10.3390/rs14153673, 2022. a, b, c
Dasgupta, A., Hostache, R., Ramsankaran, R., Grimaldi, S., Matgen, P., Chini, M., Pauwels, V. R., and Walker, J. P.: Earth observation and hydraulic data assimilation for improved flood inundation forecasting, in: Earth observation for flood applications, Elsevier, 255–294, https://doi.org/10.1016/B978-0-12-819412-6.00012-2, 2021. a
Gaurav, K., Sinha, R., and Panda, P.: The Indus flood of 2010 in Pakistan: a perspective analysis using remote sensing data, Nat. Hazards, 59, 1815–1826, 2011. a, b
Global Flood Monitoring: GFM Product Definition Document, https://extwiki.eodc.eu/GFM/PDD/GFMoutputLayers#output-layer-exclusion-mask (last access: 23 September 2022), 2022. a
Global Flood Monitoring Service: Global Flood Awareness System, https://www.globalfloods.eu/ (last access: 20 October 2023), 2023. a
Download
Short summary
In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Altmetrics
Final-revised paper
Preprint