Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War

• URL: http://arxiv.org/abs/2312.10819v2
• Date: Sun, 2 Jun 2024 11:06:55 GMT
• Title: Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War
• Authors: Hannah Kerner, Catherine Nakalembe, Benjamin Yeh, Ivan Zvonkov, Sergii Skakun, Inbal Becker-Reshef, Amy McNally,
• Abstract summary: The Tigray War was an armed conflict that took place primarily in the Tigray region of northern Ethiopia from November 3, 2020 to November 2, 2022. Given the importance of agriculture in Tigray to livelihoods and food security, determining the impact of the war on cultivated area is critical. Using satellite imagery and statistical area estimation techniques, we assessed changes in crop cultivation area in Tigray before and during the war.
• Score: 10.852723817335475
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The Tigray War was an armed conflict that took place primarily in the Tigray region of northern Ethiopia from November 3, 2020 to November 2, 2022. Given the importance of agriculture in Tigray to livelihoods and food security, determining the impact of the war on cultivated area is critical. However, quantifying this impact was difficult due to restricted movement within and into the region and conflict-driven insecurity and blockages. Using satellite imagery and statistical area estimation techniques, we assessed changes in crop cultivation area in Tigray before and during the war. Our findings show that cultivated area was largely stable between 2020-2021 despite the widespread impacts of the war. We estimated $1,132,000\pm133,000$ hectares of cultivation in pre-war 2020 compared to $1,217,000 \pm 132,000$ hectares in wartime 2021. Comparing changes inside and outside of a 5 km buffer around conflict events, we found a slightly higher upper confidence limit of cropland loss within the buffer (0-3%) compared to outside the buffer (0-1%). Our results support other reports that despite widespread war-related disruptions, Tigrayan farmers were largely able to sustain cultivation. Our study demonstrates the capability of remote sensing combined with machine learning and statistical techniques to provide timely, transparent area estimates for monitoring food security in regions inaccessible due to conflict.

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