Evidence map›Paper›PMID 36918608›Full record

ArticleScientific reports2023

A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods.

Faisal Mueen Qamer, Sawaid Abbas, Bashir Ahmad, Abid Hussain, Aneel Salman, Sher Muhammad, Muhammad Nawaz, Sravan Shrestha, Bilal Iqbal, Sunil Thapa

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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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8 citing papers in PubMed.

  1. Article
  2. Pakistan sheep industry its constrains and future trends.Tropical animal health and production · 2024
    Review
  3. Article
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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Faisal Mueen Qamer *International Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan. Faisal.Qamer@icimod.org.
Sawaid Abbas *Smart Sensing for Climate and Development, Center for Geographical Information System, University of the Punjab, Lahore, Pakistan. sawaid.abbas@gmail.com.
Bashir AhmadPakistan Agricultural Research Council (PARC), Islamabad, Pakistan.
Abid HussainInternational Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan.
Aneel SalmanIslamabad Policy Research Institute (IPRI), Islamabad, Pakistan.
Sher MuhammadInternational Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan.
Muhammad NawazPakistan Agricultural Research Council (PARC), Islamabad, Pakistan.
Sravan ShresthaInternational Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan.
Bilal IqbalPakistan Agricultural Research Council (PARC), Islamabad, Pakistan.
Sunil ThapaInternational Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 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.

Identifiers

PMID36918608
PMCPMC10015072

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