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Greenhouse baseline assessment during the conflict across Lebanon in 2024











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    Greenhouse damage assessment during the conflict across Lebanon in 2024 2025
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    A geospatial damage assessment was conducted to evaluate the impact of the 2023–2024 conflict on greenhouses in Lebanon. The assessment utilized very high-resolution (VHR) satellite imagery from WorldView-2 (50 cm) and WorldView-3 (30 cm), comparing images from before October 2023 and 2024. This assessment covered four of the most conflict-affected governorates. Using VHR imagery, visual interpretations were conducted in those governorates to assess the damage of the greenhouses. While the map depicts the distribution of damaged greenhouse areas using a hexagonal grid for the two visual interpretations, the graph illustrates the proportion of damaged greenhouses relative to the total intact greenhouse area by governorate. Overall, a 3.4 percent difference of damaged greenhouses was observed between visually interpreted points and delineated greenhouses. Two independent assessments were conducted with less than 3 percent difference.
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    Assessing vegetation changes in agriculture and forestry during the conflict in Lebanon – October 2023 to October 2024 2025
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    Lebanon is facing a growing risk of food insecurity due to the conflict that began in October 2023, which threatens the country's agricultural land and assets. This geospatial assessment aims to analyse changes in agricultural land during the baseline period from October 2019 to 7 October 2023, in comparison with October 2024. A land cover map for 2023 was generated using Sentinel-2 imagery (10 m resolution). To assess vegetation loss, Normalized Difference Vegetation Index (NDVI) values for October 2024, derived from Landsat 7 and 8 (30 m resolution), were compared with the baseline NDVI. Areas with significant negative deviations in NDVI were identified by initially comparing the average NDVI for October 2024 with the baseline average and standard deviation. High-resolution imagery (VHR) was then used to classify and confirm land cover changes in regions showing notable vegetation loss.
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