Cybernetics And Systems Analysis logo
Editorial Board Announcements Abstracts Authors Archive
KIBERNETYKA TA SYSTEMNYI ANALIZ
International Theoretical Science Journal
-->

DOI 10.34229/KCA2522-9664.25.5.17
UDC 004.8, 519.6, 528.8

A. Kolotii
Space Research Institute under NAS of Ukraine and State Space Agency of Ukraine, Kyiv, Ukraine; Institute of Physics and Technology of the National Technical University “Igor Sikorsky Kyiv Polytechnic Institute,” Kyiv, Ukraine, andrew.k.911@gmail.com

A. Shelestov
Institute of Physics and Technology of the National Technical University “Igor Sikorsky Kyiv Polytechnic Institute,” Kyiv, Ukraine; Space Research Institute under NAS of Ukraine and State Space Agency of Ukraine, Kyiv, Ukraine, andrii.shelestov@gmail.com

O. Zhdanova
Institute of Physics and Technology of the National Technical University “Igor Sikorsky Kyiv Polytechnic Institute,” Kyiv, Ukraine, 0982496208z@gmail.com

Ye. Volkova
Institute of Physics and Technology of the National Technical University “Igor Sikorsky Kyiv Polytechnic Institute,” Kyiv, Ukraine, yelvol-ipt22@lll.kpi.ua


THE IMPACT OF WAR ON ECONOMIC ACTIVITY IN UKRAINE USING SATELLITE
NIGHT LIGHT DATA TO ASSESS THE ECONOMIC SITUATION

Abstract. This study examines the impact of war on economic activity in Ukraine through the analysis of satellite Night Light data. Traditional economic indicators, such as Gross Regional Product (GRP), are not always available in conflict areas, making it difficult to assess the actual state of the economy. The use of satellite data provides objective and timely information on the level of economic activity, particularly in regions most affected by military actions. The study analyzes the correlation between Night Light intensity and economic indicators and extrapolates GRP for 2022-2023. The results show a significant decline in economic activity in areas of active military conflict and occupied territories, confirming the effectiveness of satellite data for economic monitoring.

Keywords: satellite data, night lights, economic activity, regression models, regional development, economic monitoring.


full text

REFERENCES

    • 1. Singhal A., Sahu S., Chattopadhyay S., Mukherjee A., Bhanja S.N. Using night time lights to find regional inequality in India and its relationship with economic development. PLOS ONE. 2020. Vol. 15, Iss. 11. Article number e0241907. https://doi.org/10.1371/journal.pone.0241907.
    • 2. Li Q., Shi X., Wu Q. Effects of China’s ecological restoration on economic development based on Night-Time Light and NDVI data. Environmental Science and Pollution Research. 2021. Vol. 28, Iss. 46. P. 65716–65730. https://doi.org/10.1007/s11356-021-15595-7.
    • 3. Ling J., Liu X., Wang Q., Niu D. Temporal and spatial pattern changes of regional economic development based on night-time light data. Journal of Physics: Conference Series. 2020. Vol. 1646, Iss. 1. Article number 012083. https://doi.org/10.1088/1742-6596/1646/1/012083.
    • 4. Watson C.S., Elliott J.R., CЛrdova M., Menoscal J., Bonilla-Bedoya S. Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador. International Journal of Remote Sensing. 2023. Vol. 44, Iss. 8. P. 2691–2716. https://doi.org/10.1080/01431161.2023.2205983.
    • 5. Bargain O.B., Vincent R.C., Caldeira E. Shine a (night)light: Decentralization and economic development in Burkina Faso. World Development. 2025. Vol. 165. Article number 106851. https://doi.org/10.1016/j.worlddev.2024.106851.
    • 6. Animashaun J.O. Democracy, growth, and the political resource curse: Evidence from night-time lights. Research Square, 2024. 32 p. (Preprint). https://doi.org/10.21203/rs.3.rs-4613565/v1.
    • 7. Eun J., Skakun S. Characterizing land use with night-time imagery: the war in Eastern Ukraine (2012–2016). Environmental Research Letters. 2022. Vol. 17, N 9. Article number 095006. https://doi.org/10.1088/1748-9326/ac8b23.
    • 8. Huang C., Hong S., Niu X. et. al. Mapping of nighttime light trends and refugee population changes in Ukraine during the Russian-Ukrainian war. Frontiers in Environmental Science. 2023. Vol. 11. Article number 1055100. https://doi.org/10.3389/fenvs.2023.1055100.
    • 9. Li L.-L., Liang P., Jiang S., Chen Z.-Q. Multi-scale dynamic analysis of the Russian-Ukrainian conflict from the perspective of night-time lights. Applied Sciences. 2022. Vol. 12, Iss. 24. Article number 12998. https://doi.org/10.3390/app122412998.
    • 10. Chen B., Tu Y., An J. et al. Quantification of losses in agriculture production in eastern Ukraine due to the Russia-Ukraine war. Communications Earth & Environment. 2024. Vol. 5. Article number 336. https://doi.org/10.1038/s43247-024-01488-3.
    • 11. Cerra D., Merkle N., Henry C., Gapp S., Gstaiger V. Increases in night lights intensity reveal extreme events: A case of study on the ongoing conflict in Ukraine. ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences. 2024. Vol. X-3-2024. P. 53–59. https://doi.org/10.5194/isprs-annals-x-3-2024-53-2024.
    • 12. Lin Y., Gao C., Yu J. et. al. Pixel-level quantification of damage and recovery caused by the Russia-Ukraine conflict based on nighttime light imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2024. Vol. 17.
      https://doi.org/10.1109/jstars.2024.3449394.
    • 13. Xiao B., Hu S., Ai W. et. al. Night-time light loss during the 2022 Kyiv offensive revealed through VIIRS DNB. European Journal of Remote Sensing. 2024. Vol. 57, Iss. 1. Article number 2362387. https://doi.org/10.1080/22797254.2024.2362387.
    • 14. Lavreniuk M., Shumilo L., Yailymov B., Kussul N. Reviewing deep learning methods in the applied problems of economic monitoring based on geospatial data. Cybernetics and Systems Analysis. 2022. Vol. 58, N 6. P. 1008–1020. https://doi.org/10.1007/s10559-023-00535-9.
    • 15. Kussul N.M., Shelestov A.Yu., Lavreniuk A.M. et al. Methods of computer vision and deep neural networks for ecological and economic analysis. Kyiv: Nauk. Dumka, 2024. 474 p.
    • 16. VIIRS Stray Light Corrected Nighttime Day/Night Band Composites Version 1.
      URL: https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_MONTHLY_V1_VCMSLCFG#description.
    • 17. Mills S., Weiss S., Liang C. VIIRS day/night band (DNB) stray light characterization and correction. Proc. SPIE Optical Engineering + Applications – Earth Observing Systems XVIII (25–29 August 2013, San Diego, USA). San Diego, 2013. Vol. 8866. Article number 88661P. https://doi.org/10.1117/12.2023107.
    • 18. Gross regional product (2004–2021) taking into account the revision of balance of payments data. Kyiv: State Statistics Service of Ukraine, 2023.
      URL: https://www.ukrstat.gov.ua/operativ/operativ2021/vvp/kvartal_new/vrp/arh_vrp_u.html.
    • 19. Deichmann U., Reuter A., Vollmer S., Zhang F. The relationship between energy intensity and economic growth: new evidence from a multi-country multi-sectorial dataset. World Development. 2019. Vol. 124. Article number 104664. https://doi.org/10.1016/j.worlddev.2019.104664.
    • 20. Capital investments by regions for 2010–2024. Kyiv: State Statistics Service of Ukraine, 2024. URL: https://www.ukrstat.gov.ua/operativ/operativ2023/ibd/kin_reg/ki_reg_10-20.xlsx.
    • 21. Shelestov A., Yailymova H., Yailymov B., Kussul N. Air quality estimation in Ukraine using SDG 11.6.2 indicator assessment. Remote Sensing. 2021. Vol. 13, Iss. 23. Article number 4769. https://doi.org/10.3390/rs13234769.
    • 22. Skakun S., Justice C.O., Kussul N., Shelestov A., Lavreniuk M. Satellite data reveal cropland losses in South-Eastern Ukraine under military conflict. Frontiers in Earth Science. 2019. Vol. 7. Article number 305. https://doi.org/10.3389/feart.2019.00305.
    • 23. Copernicus Land Monitoring Service. Urban Atlas.
      URL: https://land.copernicus.eu/en/products/urban-atlas.
    • 24. European Environment Agency Urban Atlas:
      URL: https://www.eea.europa.eu/en/datahub/datahubitem-view/e006507d-15c8-49e6-959c-53b61facd873.
    • 25. Shelestov A., Yailymova H., Yailymov B., Shumilo L., Lavreniuk A.M. Extension of Copernicus Urban Atlas to non-European countries. Proc. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (11–16 July 2021, Brussels, Belgium). Brussels, 2021. P. 6789–6792. https://doi.org/10.1109/IGARSS47720.2021.9553546.
    • 26. Kussul N., Lavreniuk M., Skakun S., Shelestov A. Deep learning classification of land cover and crop types using remote sensing data. IEEE Geoscience and Remote Sensing Letters. 2017. Vol. 14, Iss. 5. P. 778–782. https://doi.org/10.1109/LGRS.2017.2681128.
    • 27. Warsaw Plus. Gallery. Construction progress.
      URL: https://plus.varshavsky.com.ua/ua/gallery/hidbud/.



© 2026 Kibernetika.org. All rights reserved.