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<p>The disastrous Monsoon floods from June to September in year 2022 caused extensive agricultural losses across Pakistan, particularly in the Indus Plains, that have severe consequences for food insecurity and livelihood. This research presents an integrated multi-sensor satellite assessment of post-flood crop damage in the provinces of Khyber Pakhtunkhwa (KP) and Punjab. We combined pre- and post-flood imagery from Sentinel-1 Synthetic Aperture Radar (SAR) for flood extent mapping, Sentinel-2 optical data for crop cover analysis, and rainfall estimates from the Global Precipitation Measurement (GPM) mission. Data processing and analysis were conducted using the Google Earth Engine (GEE) cloud platform, and results were validated with ground observations from the Pakistan Meteorological Department. Analytical methods included Otsu’s thresholding for flood segmentation and Normalized Difference Vegetation Index (NDVI) classification for crop damage assessment. Our findings reveal that approximately 2.67&#xa0;million acres (13.3%) of Punjab’s cropland and 287,000 hectares (16.5%) of KP’s cultivable land were inundated, with rice being the most severely affected crop. The spatial analysis identified key flood hotspots, such as Tank, Lakki Marwat, and Dera Ismail Khan in KP, and significant losses in Punjab’s rice with 15% of Punjab’s rice-growing region being submerged, and wheat, sugarcane, and cotton also suffered significant damage. These results provide critical insights for targeted recovery, climate-resilient agricultural planning, and disaster risk reduction. This integrated approach demonstrates the value of combining high-resolution satellite data with ground observations for rapid, large-scale post-disaster assessment.</p> Graphical Abstract <p>This study examines the effects of the devastating monsoon floods that struck Pakistan from June to September 2022, particularly focusing on their impact on agriculture in the crucial Indus Plains region. The research employs a multi-sensor satellite approach to evaluate the aftermath of these floods on key crops in two significant provinces: Khyber Pakhtunkhwa (KP) and Punjab. Utilizing pre- and post-flood satellite imagery from Sentinel-1, Sentinel-2, and GEE, the study offers an in-depth analysis of flood extent, crop coverage, and rainfall intensity. The results indicate that the floods imposed severe damage, with major crops responsible for 81.2% of the overall agricultural losses. The analysis revealed an inundation of approximately 2.67&#xa0;million acres of crops in Punjab and 287,000 hectares in KP, highlighting the grave consequences for food security, livestock, and farming households. The study pinpointed specific regions severely affected by flooding, emphasizing the percentage of livelihoods dependent on key crops such as cotton, sugarcane, wheat, and rice, and illustrating the widespread repercussions for rural communities. Areas like Lakki Marwat, and Dera Ismail Khan are identified as significant flood hotspots. In summary, this research delivers vital insights into the floods consequences on agricultural production, aiming to inform policy-making and promote climate-smart recovery strategies to bolster food security and rehabilitate livelihoods in the wake of this disaster. </p>

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Assessing Agrometeorological Damage after the 2022 Pakistan Floods: Insights from Multi-Sensor Satellite Data

  • 期刊论文

  • 发表日期：

    2025年6月6日

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  • Mohsin Khan,
  • Adnan Arshad,
  • Shahida Haji,
  • Alaa Ahmed

摘要

The disastrous Monsoon floods from June to September in year 2022 caused extensive agricultural losses across Pakistan, particularly in the Indus Plains, that have severe consequences for food insecurity and livelihood. This research presents an integrated multi-sensor satellite assessment of post-flood crop damage in the provinces of Khyber Pakhtunkhwa (KP) and Punjab. We combined pre- and post-flood imagery from Sentinel-1 Synthetic Aperture Radar (SAR) for flood extent mapping, Sentinel-2 optical data for crop cover analysis, and rainfall estimates from the Global Precipitation Measurement (GPM) mission. Data processing and analysis were conducted using the Google Earth Engine (GEE) cloud platform, and results were validated with ground observations from the Pakistan Meteorological Department. Analytical methods included Otsu’s thresholding for flood segmentation and Normalized Difference Vegetation Index (NDVI) classification for crop damage assessment. Our findings reveal that approximately 2.67 million acres (13.3%) of Punjab’s cropland and 287,000 hectares (16.5%) of KP’s cultivable land were inundated, with rice being the most severely affected crop. The spatial analysis identified key flood hotspots, such as Tank, Lakki Marwat, and Dera Ismail Khan in KP, and significant losses in Punjab’s rice with 15% of Punjab’s rice-growing region being submerged, and wheat, sugarcane, and cotton also suffered significant damage. These results provide critical insights for targeted recovery, climate-resilient agricultural planning, and disaster risk reduction. This integrated approach demonstrates the value of combining high-resolution satellite data with ground observations for rapid, large-scale post-disaster assessment.

Graphical Abstract

This study examines the effects of the devastating monsoon floods that struck Pakistan from June to September 2022, particularly focusing on their impact on agriculture in the crucial Indus Plains region. The research employs a multi-sensor satellite approach to evaluate the aftermath of these floods on key crops in two significant provinces: Khyber Pakhtunkhwa (KP) and Punjab. Utilizing pre- and post-flood satellite imagery from Sentinel-1, Sentinel-2, and GEE, the study offers an in-depth analysis of flood extent, crop coverage, and rainfall intensity. The results indicate that the floods imposed severe damage, with major crops responsible for 81.2% of the overall agricultural losses. The analysis revealed an inundation of approximately 2.67 million acres of crops in Punjab and 287,000 hectares in KP, highlighting the grave consequences for food security, livestock, and farming households. The study pinpointed specific regions severely affected by flooding, emphasizing the percentage of livelihoods dependent on key crops such as cotton, sugarcane, wheat, and rice, and illustrating the widespread repercussions for rural communities. Areas like Lakki Marwat, and Dera Ismail Khan are identified as significant flood hotspots. In summary, this research delivers vital insights into the floods consequences on agricultural production, aiming to inform policy-making and promote climate-smart recovery strategies to bolster food security and rehabilitate livelihoods in the wake of this disaster.