Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105418
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorQamer, FM-
dc.creatorAbbas, S-
dc.creatorAhmad, B-
dc.creatorHussain, A-
dc.creatorSalman, A-
dc.creatorMuhammad, S-
dc.creatorNawaz, M-
dc.creatorShrestha, S-
dc.creatorIqbal, B-
dc.creatorThapa, S-
dc.date.accessioned2024-04-12T06:52:19Z-
dc.date.available2024-04-12T06:52:19Z-
dc.identifier.urihttp://hdl.handle.net/10397/105418-
dc.language.isoenen_US
dc.publisherNature Publishing Groupen_US
dc.rights© The Author(s) 2023en_US
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Qamer, F.M., Abbas, S., Ahmad, B. et al. A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods. Sci Rep 13, 4240 (2023) is available at https://doi.org/10.1038/s41598-023-30347-y.en_US
dc.titleA framework for multi-sensor satellite data to evaluate crop production losses : the case study of 2022 Pakistan floodsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume13-
dc.identifier.doi10.1038/s41598-023-30347-y-
dcterms.abstractIn August 2022, one of the most severe floods in the history of Pakistan was triggered due to the exceptionally high monsoon rainfall. It has affected ~ 33 million people across the country. The agricultural losses in the most productive Indus plains aggravated the risk of food insecurity in the country. As part of the loss and damage (L&D) assessment methodologies, we developed an approach for evaluating crop-specific post-disaster production losses based on multi-sensor satellite data. An integrated assessment was performed using various indicators derived from pre- and post-flood images of Sentinel-1 (flood extent mapping), Sentinel-2 (crop cover), and GPM (rainfall intensity measurements) to evaluate crop-specific losses. The results showed that 2.5 million ha (18% of Sindh’s total area) was inundated out of which 1.1 million ha was cropland. The remainder of crop damage came from the extreme rainfall downpour, flash floods and management deficiencies. Thus approximately 57% (2.8 million ha) of the cropland was affected out of the 4.9 million ha of agricultural area in Sindh. The analysis indicated expected production losses of 88% (3.1 million bales), 80% (1.8 million tons), and 61% (10.5 million tons) for cotton, rice, and sugarcane. This assessment provided useful tools to evaluate the L&D of agricultural production and to develop evidence-based policies enabling post-flood recovery, rehabilitation of people and restoration of livelihood.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationScientific reports, 2023, v. 13, 4240-
dcterms.isPartOfScientific reports-
dcterms.issued2023-
dc.identifier.scopus2-s2.0-85150231554-
dc.identifier.pmid36918608-
dc.identifier.eissn2045-2322-
dc.identifier.artn4240-
dc.description.validate202403 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextInternational Centre for Integrated Mountain Developmenten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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