Assessing damage to agricultural fields from military actions in Ukraine: An integrated approach using statistical indicators and machine learning

Assessing damage to agricultural fields from military actions in Ukraine: An integrated approach using statistical indicators and machine learning

The ongoing full-scale Russian invasion of Ukraine has led to widespread damage of agricultural lands, jeopardizing global food security. Timely detection of impacted fields enables quantification of production losses, guiding recovery policies and monitoring military actions. This study presents a...

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Bibliographic Details
Main Authors: Nataliia Kussul, Sofiia Drozd, Hanna Yailymova, Andrii Shelestov, Guido Lemoine, Klaus Deininger
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Machine learning
Remote sensing
War damaged fields
Statistical analysis
Spectral bands
Vegetation indices
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843223003862

Internet

http://www.sciencedirect.com/science/article/pii/S1569843223003862

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