Flooded and Irrigation Area Monitoring After the Kakhovka Dam Disaster Based on Machine Learning and Satellite Data

Скорочена інформація про документ
dc.contributor.authorYailymov, Bohdan
dc.contributor.authorYailymova, Hanna
dc.contributor.authorKolotii, Andrii
dc.contributor.authorShelestov, Andrii
dc.contributor.authorSkakun, Sergii
dc.contributor.authorBaber, Sheila
dc.contributor.authorBecker-Reshef, Inbal
dc.contributor.authorKussul, Nataliia
dc.date.accessioned2025-09-03T09:38:48Z
dc.date.available2025-09-03T09:38:48Z
dc.date.issued2025
dc.description.abstractThis study aims to assess the impact of the Kakhovka Dam destruction in Ukraine that occurred on 6 June 2023, on cropland irrigation using satellite remote sensing data. The main goal of this study is to assess flooded areas and the impact on irrigated area before and after Kakhovka Dam destruction. In particular, we analyzed flooded areas in 2023, and the changes in irrigated areas before and after the dam destruction (in 2019 and 2024) were also assessed. Maps of water bodies were generated before and after the flood using Sentinel-1, Sentinel-2, and Landsat-9 images. The random forest classifier was used for flooded area mapping, while the multilayer perceptron and the U-shaped network classifier were used for irrigated land identification. The main findings are as follows. 1) As of 9 June 2023, the total area of flooding under the Kakhovka Dam was 47.33 thousand hectares (th. ha) (473 km2), affecting 1.67 th. ha of cropland, 0.97 th. ha of forests, 12.3 th. ha of grasslands, 1.85 th. ha of settlements, and 29.4 th. ha of wetlands. 2) The analysis of irrigated area shows a decrease in irrigated cropland—from 351 th. ha in 2019 to 38 th. ha. in 2024. 3) The classification accuracy for 2019 irrigation mapping achieved 90.4% overall accuracy with F1-scores of 90.4% for both irrigated and nonirrigated classes based on ground truth data. 4) The complete disappearance of water in irrigation canals was documented, indicating the systematic destruction of agricultural infrastructure with far-reaching consequences for regional food security. The flood also affected areas along the Ingulets River, which led to the flooding of agricultural land located near the river banks and affected water quality. The disappearance of water in canals used to irrigate cropland is also analyzed, indicating the disruption of irrigation systems and possible far-reaching consequences for agriculture. Thus, this study shows the utility of satellite remote sensing and machine learning approaches for rapid monitoring and quantification of flood-related natural disaster impacts and the analysis of irrigated areas in conflict-affected regions.
dc.description.sponsorshipNational Research Foundation of Ukraine
dc.format.pagerangePp. 19129-19144
dc.identifier.citationFlooded and Irrigation Area Monitoring After the Kakhovka Dam Disaster Based on Machine Learning and Satellite Data / B. Yailymov, H. Yailymova, A. Kolotii, A. Shelestov, S. Skakun, S. Baber, I. Becker-Reshef, N. Kussul // IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - 2025. - Vol. 18. - Pp. 19129-19144.
dc.identifier.doihttps://doi.org/10.1109/JSTARS.2025.3592368
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/75780
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 18, 2025
dc.subjectDisaster monitoring
dc.subjectflooding
dc.subjectirrigation
dc.subjectKakhovska Hydroelectric Power Plant (HPP)
dc.subjectmachine learning
dc.subjectsatellite monitoring
dc.subjectUkraine
dc.titleFlooded and Irrigation Area Monitoring After the Kakhovka Dam Disaster Based on Machine Learning and Satellite Data
dc.typeArticle

Файли

Контейнер файлів
Зараз показуємо 1 - 1 з 1
Ескіз
Назва:
Flooded_and_Irrigation_Area_Monitoring.pdf
Розмір:
10.72 MB
Формат:
Adobe Portable Document Format
Завантажити
Ліцензійна угода
Зараз показуємо 1 - 1 з 1
Ескіз недоступний
Назва:
license.txt
Розмір:
8.98 KB
Формат:
Item-specific license agreed upon to submission
Опис:
Завантажити

Зібрання

Статті (ММАД)