Thumbnail Image

A rapid geospatial flood impact assessment in Pakistan, 2022

Year of publication 2022

Place of publication Rome, Italy ;

Pages 82 p.

Author Mushtaq, F.; Ali, M.; Ghosh, A.; Jalal, R.; Asghar, A.; Dadhich, G.; Chiozza, F.; Franceschini, G.; Muchoney, D.; Toirov, F.; Rolle, F.; Henry, M.;

Publisher FAO ;

Product type Book (stand-alone)

ISBN 978-92-5-137174-9

To cite or share https://doi.org/10.4060/cc2873en

Synopsis (short abstract) Pakistan is among the ten countries most affected by extreme weather events despite its very low carbon footprint, according to the Global Climate Risk Index 2021 and Climate Watch. Frequent natural disasters negatively impact the agricultural sector and household livelihoods, and push thousands of people into poverty and hunger. In 2022, intense rainfall in monsoon season caused severe flooding across Pakistan and impacted a large number of people and households including deaths of people, damage to infrastructure (including roads, dams, buildings, electricity poles etc.), destruction of agricultural area and pushed millions of people into poverty and hunger. Since the beginning of the rainy season, it is reported that over 735 000 livestock have perished, and about 2 million acres of crops have been adversely impacted (UNCT, 2022).

Cite this content as:

Mushtaq, F., Ali, M., Ghosh, A., Jalal, R., Asghar, A., Dadhich, G., Chiozza, F., Franceschini, G., Muchoney, D., Toirov, F., Rolle, F. and Henry, M. 2022. A rapid geospatial flood impact assessment in Pakistan. Rome, FAO.

https://doi.org/10.4060/cc2873en

Language English

Also available in:
No results found.

Related items

Showing items related by metadata.

  • Thumbnail Image
    Book (stand-alone)
    Nepal: Flood impact assessment
    DIEM-Impact report, November 2024
    2025
    Also available in:
    No results found.
    The rainfall on 26 and 27 September 2024 was identified as the heaviest ever recorded in Nepal's history. As at 5 October 2024, more than 5 300 households (approximately 26 500 people) had been affected across the districts of Kavre Palanchowk, Lalitpur, Makwanpur, Panchthar, Ramechhhap and Sindhuli. As at 16 October 2024, the death toll had reached 250 and more than 17 000 people had been rescued through rescue operations deploying more than 30 000 security personnel. The Government of Nepal declared 71 municipalities across 20 districts as disaster crisis or emergency zones due to the severe impact of landslides and floods. The Food and Agriculture Organization of the United Nations' (FAO) Data in Emergencies (DIEM) conducted a DIEM-Impact assessment to understand the impact of the floods on the affected population, infrastructure and essential services from 17 to 24 November 2024. FAO established DIEM-Impact to provide a granular and rapid understanding of the impact of large-scale hazards on agriculture and agricultural livelihoods using a variety of assessment methodologies, including primary and secondary information, remote sensing technologies, and FAO’s damage and loss methodology. DIEM-Impact presents a regularly updated and accessible state of food insecurity in fragile environments, and helps underpin FAO's programming based on evidence.
  • Thumbnail Image
    Brochure, flyer, fact-sheet
    A rapid geospatial analysis of the flood impacts on crops in Eastern Cape province of South Africa in 2022 2023
    Also available in:
    No results found.
    An analysis to assess the impacts of floods on cropland in KwaZulu-Natal province was performed using existing data, GIS and remote sensing. The crop mask was derived from the South African National Land Cover map (SANLC, 2018). The water mask was derived from the Joint Research Centre (JRC) water body data (2020). Sentinel 1 SAR was used to assess flood extent.
  • Thumbnail Image
    Brochure, flyer, fact-sheet
    A rapid geospatial analysis of the flood impacts on crops in KwaZulu-Natal province of South Africa in 2022 2023
    Also available in:
    No results found.
    An analysis to assess the impacts of floods on cropland in KwaZulu-Natal province was performed using existing data, GIS and remote sensing. The crop mask was derived from the South African National Land Cover map (SANLC, 2018). The water mask was derived from the Joint Research RC) water body data (2020). Sentinel 1 SAR was used to assess flood extent.
Show more

Users also downloaded

Showing related downloaded files

No results found.