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<p>Flooding poses a serious threat to agricultural productivity and food security, particularly in data-scarce regions. This study examines the impact of floods on croplands in Golestan Province, northern Iran, by integrating radar and optical satellite data on the Google Earth Engine (GEE) platform. In the first phase, major crops were classified using Sentinel-1 and Sentinel-2 imagery based on phenology and vegetation indices. In the second phase, flood-affected areas were mapped using pre-, peak-, and post-flood Sentinel-1 images through a change detection approach. In the third phase, flood extent was overlaid with crop maps to assess crop-specific damage. Finally, long-term trends in land surface temperature (LST) and precipitation were analyzed using Landsat and CHIRPS datasets, and historical flood records were used to examine climate–flood relationships. The results show that about 43,932&#xa0;ha hectares of cropland were affected by flooding. The most impacted areas were located in the northwest and near the Atrak, Qaresou, and Gorganrood river basins. Majorly damaged crops included wheat (13,150&#xa0;ha), rice (4,144&#xa0;ha), barley and rapeseed (6,715&#xa0;ha), soybean and cotton (528&#xa0;ha), and other crops (19,395&#xa0;ha). Climate analysis revealed a steady increase in mean and maximum LST. Precipitation levels declined, with extreme rainfall fluctuations. These extreme events were closely linked to major flood occurrences. The findings highlight the need for climate-resilient strategies to reduce flood risks and enhance food security.</p>

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Assessing flood impacts on food security and climate trends using remote sensing

  • 期刊论文

  • 发表日期：

    2025年8月8日

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  • Zahra Parvar,
  • Abdolrassoul Salmanmahiny

摘要

Flooding poses a serious threat to agricultural productivity and food security, particularly in data-scarce regions. This study examines the impact of floods on croplands in Golestan Province, northern Iran, by integrating radar and optical satellite data on the Google Earth Engine (GEE) platform. In the first phase, major crops were classified using Sentinel-1 and Sentinel-2 imagery based on phenology and vegetation indices. In the second phase, flood-affected areas were mapped using pre-, peak-, and post-flood Sentinel-1 images through a change detection approach. In the third phase, flood extent was overlaid with crop maps to assess crop-specific damage. Finally, long-term trends in land surface temperature (LST) and precipitation were analyzed using Landsat and CHIRPS datasets, and historical flood records were used to examine climate–flood relationships. The results show that about 43,932 ha hectares of cropland were affected by flooding. The most impacted areas were located in the northwest and near the Atrak, Qaresou, and Gorganrood river basins. Majorly damaged crops included wheat (13,150 ha), rice (4,144 ha), barley and rapeseed (6,715 ha), soybean and cotton (528 ha), and other crops (19,395 ha). Climate analysis revealed a steady increase in mean and maximum LST. Precipitation levels declined, with extreme rainfall fluctuations. These extreme events were closely linked to major flood occurrences. The findings highlight the need for climate-resilient strategies to reduce flood risks and enhance food security.