Satellite Data and AI Confirm Devastating Forest Loss in Ukraine Amid War

Satellite Data and AI Confirm Devastating Forest Loss in Ukraine Amid War

The war in Ukraine has caused widespread destruction. The loss of forests is one of its major environmental consequences. A team of researchers headed by Roberto Cazzolla Gatti, Professor at the Department of Biological, Geological, and Environmental Sciences at the University of Bologna used artificial intelligence and satellite images to quantify forest loss. Their findings, which are discussed in an article published in Global Ecology and Conservation, provide evidence that the ongoing Russia-Ukraine conflict has caused severe environmental damage.

The Hidden Cost of Russia-Ukraine War: 1580 Square Kilometers of Forests in Ukraine Destroyed

Background

Historical evidence shows that wars often lead to the destruction of natural resources such as forests, water sources, and agricultural lands. The Russia-Ukraine War, apart from its human toll and damage to properties, is no exception due to its documented impact on the environment. Forest loss is one of the main issues. Forested areas in Ukraine play a crucial role in ecosystem processes and the domestic agricultural sector.

Researchers R. Cazzolla Gatti et al. used remote sensing and artificial intelligence to monitor forest destruction in Ukraine. They specifically employed a machine learning algorithm called Random Forest to analyze high-quality satellite images. This method enabled them to monitor changes in forest cover and quantify the impact of the war. The findings offer an accurate picture of the environmental damage caused by the conflict.

Findings

The study identified significant forest loss in Ukraine between 2022 and 2023. Total forest loss includes 808 square kilometers in 2022 and 772 square kilometers in 2023 or a total of 1580 square kilometers of forest cover. This land area is about twice as large as Toronto and about 19 percent larger than Los Angeles City.

Specific details showed that the most affected regions were Kyiv, with 268 square kilometers lost, and Kherson, with 214 square kilometers lost. Kyiv is the capital of Ukraine while Kherson is a port city and a regional economic center that is home to a major ship-building industry.

Other areas with significant forest cover loss are Luhansk, with 195 square kilometers lost, Kharkiv, with 181 square kilometers lost, and Donetsk, with 180 square kilometers lost. Both Luhansk and Donetsk are under Russian occupation. Kharkiv, the second-largest city in Ukraine, has remained under intermittent Russian fire.

Researchers believe that fire is the main cause of forest loss. Many fires were recorded in conflict areas. Most incidents occurred in March 2022 following the Russian invasion in February. For example, in Kherson, Russian troops allegedly blocked efforts to extinguish the flames.

Implications

Cazzolla Gatti, in a statement, identified possible damage to several biodiversity and ecosystem processes. These include water filtration, soil formation, and climate regulation. All are difficult to measure. These processes are important in environmental conservation efforts. Furthermore, with regard to agricultural productivity, take note that these are essential in sustainable farming practices and increasing the resilience of crops.

Nevertheless, when the Russia-Ukraine war concludes through a binding agreement, he further highlighted the need for strong and efficient policies that would prevent additional biodiversity loss, promote reforestation, and restore ecosystems. He also noted that reforested areas may contribute to the creation of ecological humanitarian corridors and support demilitarization, thus creating buffer zones to build and preserve peace.

FURTHER READING AND REFERENCE

  • Cazzolla Gatti, R., Cortès Lobos, R. B., Torresani, M., & Rocchini, D. 2025. An Early Warning System Based on Machine Learning Detects Huge Forest Loss in Ukraine During the War. In Global Ecology and Conservation. 58: e03427. Elsevier BV. DOI: 1016/j.gecco.2025.e03427
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