Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery
Yin, He, Elkund, Lina, Habash, Dimah, Qumsiyeh, Mazin B. and Van Den Hoek, Jamon, (2025). Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery. Science of Remote Sensing, n/a-n/a
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http://dx.doi.org/10.1016/j.srs.2025.100199 Full text from publisher -
Sub-type Journal article Author Yin, He
Elkund, Lina
Habash, Dimah
Qumsiyeh, Mazin B.
Van Den Hoek, JamonTitle Evaluating war-induced damage to agricultural land in the Gaza Strip since October 2023 using PlanetScope and SkySat imagery Appearing in Science of Remote Sensing Publication Date 2025-02-01 Place of Publication Amsterdam, Netherlands Publisher Elsevier B.V Start page n/a End page n/a Language eng Abstract The ongoing 2023 Israel-Hamas War has severe and far-reaching consequences for the people, economy, food security, and environment. The immediate impacts of damage and destruction to cities and farms are apparent in widespread reporting and first-hand accounts from within the Gaza Strip. However, there is a lack of comprehensive assessment of the war’s impacts on key Gazan agricultural land that are vital for immediate humanitarian concerns during the ongoing war and for long-term recovery. In the Gaza Strip, agriculture is arguably one of the most important land use systems. However, remote detection of damage to Gazan agriculture is challenged by the diverse agronomic landscapes and small farm sizes. This study uses multi-resolution satellite imagery to monitor damage to tree crops and greenhouses, the most important agricultural land in the Gaza Strip. Our methodology involved several key steps: First, we generated a pre-war cropland map, distinguishing between tree crop fields (e.g., olives, orchards) and greenhouses, using a random forest and the Segment Anything Model (SAM) on 3-m PlanetScope and 50-cm Planet SkySat imagery, obtained from 2022 to 2023. Second, we assessed damage to tree crop fields due to the war, employing a harmonic-model-based time series analysis using PlanetScope imagery. Third, we assessed the damage to greenhouses by classifying PlanetScope imagery using a random forest model. We performed accuracy assessments on generated tree crop fields damage map using 1,200 randomly sampled 3×3-meter areas, and generated error-adjusted area estimates with a 95% confidence interval. To validate the generated greenhouse damage map, we used a random sampling-based analysis. We found that 64–70% tree crop fields and 58% greenhouses had been damaged by 27 September 2024 after almost one year of the war in the Gaza Strip. Agricultural land in Gaza City and North Gaza were the most heavily damaged with 90% and 73% of tree crop fields damaged in each governorate, respectively. By the end of 2023, all greenhouses in North Gaza and Gaza City had been damaged. Our damage estimate overall agrees with that from UNOSAT but provides more detailed and accurate information such as the timing of the damage as well as fine-scale changes. Our results attest to the severe impacts of the Israel-Hamas War on Gaza's agricultural sector with direct relevance for food security and economic recovery needs. Due to the rapid progression of the war, the latest damage maps and area estimates are available on GitHub (https://github.com/hyinhe/Gaza). Keyword Armed Conflict
Israel-Hamas war
Agriculture
PlanetScope
SkySat
Artificial Intelligence
Deep Learning
Tree crops
Greenhouses
Harmonic modelCopyright Holder Elsevier B.V. Copyright Year 2025 Copyright type All rights reserved DOI 10.1016/j.srs.2025.100199 -
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