Geospatial Workflow for Mapping War-Related Environmental Degradation and Potential Public Health Risks in Ukraine
DOI:
https://doi.org/10.66659/wrsfjb97Keywords:
Geospatial analysis; Google Earth Engine; war-related environmental degra-dation; Sentinel-2; public health; remote sensingAbstract
This article systematizes methods of geospatial analysis for mapping the geoecological consequences of armed conflict in Ukraine and considers their potential long-term implications for public health. The study focuses on the spatial distribution of environmental risks associated with landscape destruction and other forms of war-related territorial degradation. As a practical case study, it demonstrates the integration of open geospatial datasets, particularly Copernicus Sentinel-2 imagery, using the open-source QGIS environment and the Google Earth Engine cloud platform. The proposed workflow illustrates how raw geospatial data can be processed into a landscape degradation map suitable for preliminary environmental screening and decision support. Particular attention is also given to ethical requirements for the future integration of health-related spatial data, including spatial aggregation and patient de-identification.
References
1. Anselin, L. (1989). What is special about spatial data? Alternative perspectives on spatial data analysis. Technical Report 89–4, National Center for Geographic Infor-mation and Analysis.
2. Johnson, S. (2006). The ghost map: The story of London's most terrifying epidemic—and how it changed science, cities, and the modern world. Penguin.
3. May, J. M. (1958). The ecology of human disease. MD Publications.
4. May, J. M. (1961). Studies in disease ecology. Hafner Publishing.
5. Emch, M., & Goel, V. (2026). Disease ecology in health and medical geography: His-tory, progress, and innovations. Singapore Journal of Tropical Geography, 47(1), 7–32. https://doi.org/10.1111/sjtg.12581
6. Troll, C. (1971). Landscape ecology (geoecology) and biogeocenology: A terminologi-cal study. Geoforum, 2(4), 43–46. https://doi.org/10.1016/0016-7185(71)90029-7
7. Huggett, R. J. (2017). Fundamentals of geomorphology (4th ed.). Routledge. https://doi.org/10.4324/9781315674179
8. Bolstad, P. (2019). GIS fundamentals: A first text on geographic information systems (6th ed.). XanEdu.
9. Jones, K., & Moon, G. (1993). Medical geography: Taking space seriously. Progress in Human Geography, 17(4), 515–524. https://doi.org/10.1177/030913259301700405
10. Parchman, M. L., Ferrer, R. L., & Blanchard, S. (2002). Geography and geographic information systems in family medicine research. Family Medicine, 34(2), 132–137.
11. Jayasinghe, S. (2024). The 12 dimensions of health impacts of war (the 12-D frame-work): A novel framework to conceptualise impacts of war on social and environmen-tal determinants of health and public health. BMJ Global Health, 9(5), Article e014512. https://doi.org/10.1136/bmjgh-2023-014749
12. Chandran, A., & Roy, P. (2024). Applications of geographical information system and spatial analysis in Indian health research: A systematic review. BMC Health Ser-vices Research, 24(1), Article 1448. https://doi.org/10.1186/s12913-024-11837-9
13. Chang, K. T. (2019). Introduction to geographic information systems (9th ed.). McGraw-Hill Education.
14. DiBiase, D. (2014). Nature of geographic information: An open geospatial textbook. Pennsylvania State University.
15. Open Source Geospatial Foundation. (2024). About the Open Source Geospatial Foundation. https://www.osgeo.org/about/
16. QGIS Development Team. (n.d.). QGIS Geographic Information System [Computer software]. Open Source Geospatial Foundation. https://qgis.org
17. Neteler, M., Bowman, M. H., Landa, M., & Metz, M. (2012). GRASS GIS: A multi-purpose open source GIS. Environmental Modelling & Software, 31, 124–130. https://doi.org/10.1016/j.envsoft.2011.11.014
18. gvSIG Association. (n.d.). gvSIG desktop: A powerful, user-friendly, open source ge-ographic information system. http://www.gvsig.com
19. GDAL/OGR Contributors. (n.d.). GDAL: Geospatial Data Abstraction Library [Com-puter software]. Open Source Geospatial Foundation. https://gdal.org
20. Google. (n.d.). Google Earth Engine [Web platform]. https://earthengine.google.com
21. Hasselbring, W., Carr, L., Hettrick, S., Packer, H., & Tiropanis, T. (2020). From FAIR software to FAIR data and beyond. Computer Science - Research and Devel-opment, 35(1), 109–122. https://doi.org/10.48550/arXiv.1908.05986
22. Trofymenko, P. I., Zatserkovnyi, V. I., & Kokosha, L. O. (2024). Determination of greenhouse gas concentration in the atmosphere by Earth remote sensing means: Cartographic and analytical assessment of the geospatial distribution of its values. Space Science and Technology, 30(4), 34–47. https://doi.org/10.15407/knit2024.04.034
23. World Health Organization. (2021). WHO global air quality guidelines: Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon mon-oxide. https://iris.who.int/handle/10665/345329
24. Kokosha, L., Trofymenko, P., Liashenko, D., & Malik, T. (2025). Geoinformation modeling of the urban heat island in Kharkiv under wartime conditions. 18th Inter-national Conference Monitoring of Geological Processes and Ecological Condition of the Environment, 2025(1), 1–5. https://doi.org/10.3997/2214-4609.2025510053
25. Tatem, A. J. (2017). WorldPop, open data for spatial demography. Scientific Data, 4(1), Article 170004. https://doi.org/10.1038/sdata.2017.4
26. OpenStreetMap contributors. (n.d.). OpenStreetMap [Map]. Retrieved July 13, 2026, from https://www.openstreetmap.org
27. KMZMap. (n.d.). Ukraine war library: Mapping the conflict [Interactive map]. Re-trieved July 10, 2026, from https://kmzmap.com/uk?mode=library&src=ukraine-war
28. Deutsche Welle. (2023, January 12). Bytva za Soledar: Yak misto vyhliadaie sohodni [Battle for Soledar: What the city looks like today]. https://www.dw.com/uk/bitva-za-soledar-ak-misto-vigladae-sogodni-foto/a-64361808
29. Humanity & Inclusion. (2026, April 2). Landmines: Use, contamination and civilian harm in Ukraine—Factsheet 2026. ReliefWeb. https://reliefweb.int/report/ukraine/landmines-use-contamination-and-civilian-harm-ukraine-factsheet-2026-enuk
30. Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation (NASA/GSFC Type III Third Progress Report). NASA Goddard Space Flight Center.
31. Key, C. H., & Benson, N. C. (2006). Landscape assessment (LA). In D. C. Lutes, R. E. Keane, J. F. Caratti, C. H. Key, N. C. Benson, S. Sutherland, & L. J. Gangi (Eds.), FIREMON: Fire effects monitoring and inventory system (General Technical Report RMRS-GTR-164-CD, pp. LA-1–LA-55). USDA Forest Service, Rocky Mountain Re-search Station.
32. European Space Agency. (2021). ESA WorldCover 10 m 2020 product (Version v100) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5571936
33. NASA FIRMS. (n.d.). VIIRS 375m Active Fire Product [Data set]. Near Real-Time NRT Quality Data. Retrieved July 13, 2026, from https://firms.modaps.eosdis.nasa.gov
34. Ministerstvo Rozvytku Hromad ta Terytorii Ukrainy. (2020). Kodyfikator admin-istratyvno-terytorialnykh odynyts ta terytorii terytorialnykh hromad (KATOTTH) [Codifier of administrative-territorial units and territories of territorial communities]. https://mindev.gov.ua/diialnist/rozvytok-mistsevoho-samovriaduvannia/kodyfikator-administratyvno-terytorialnykh-odynyts-ta-terytorii-terytorialnykh-hromad
35. Verkhovna Rada of Ukraine. (2010). Pro zakhyst personalnykh danykh [On protec-tion of personal data] (Act No. 2297-VI). https://zakon.rada.gov.ua/laws/show/2297-17
36. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). (2016). Official Journal of the European Un-ion, L 119, 1–88. http://data.europa.eu/eli/reg/2016/679/oj
37. Kwan, M.-P. (2018). The limits of the neighborhood effect: Contextual uncertainties in geographic, environmental health, and social science research. Annals of the American Association of Geographers, 108(6), 1482–1490. https://doi.org/10.1080/24694452.2018.1453777
38. Dent, B. D., Torguson, J. S., & Hodler, T. W. (2009). Cartography: Thematic map design (6th ed.). McGraw-Hill.
39. Humanitarian OpenStreetMap Team. (2026). Ukraine – health facilities (Open-StreetMap export) [Data set]. Humanitarian Data Exchange. https://data.humdata.org/dataset/hotosm_ukr_health_facilities
40. Kontur. (2023). Kontur population: Ukraine [Data set]. Humanitarian Data Ex-change. https://data.humdata.org/dataset/kontur-population-ukraine
41. Brewer, C. A. (n.d.). ColorBrewer 2.0: Color advice for maps. http://colorbrewer2.org/
42. Bloch, M. (n.d.). Mapshaper [Computer software]. Retrieved [10-07-2026], from https://mapshaper.org/
43. Trimaille, É. (2026). QuickOSM (Version 2.3.2) [QGIS plugin]. GitHub. https://github.com/3liz/QuickOSM
44. Čerba, O. (2025). OpenStreetMap as the data source for territorial innovation poten-tial assessment. ISPRS International Journal of Geo-Information, 14(3), Article 127. https://doi.org/10.3390/ijgi14030127
45. Frumkin, H. (Ed.). (2021). Environmental health: From global to local (4th ed.). Jossey-Bass.
46. Smith, M. J., Goodchild, M. F., & Longley, P. A. (2021). Geospatial analysis: A com-prehensive guide (6th ed.). Winchelsea Press
47. European Space Agency. (2022). Sentinel-2 MSI: MultiSpectral Instrument, Level-2A [Data set]. Google Earth Engine. https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED
48. National Aeronautics and Space Administration. (2022). Fire Information for Re-source Management System (FIRMS) thermal anomalies / fire product [Data set]. Google Earth Engine Data Catalog. https://developers.google.com/earth-engine/datasets/catalog/FIRMS
49. Zanaga, D., Van De Kerchove, R., De Keersmaecker, W., Souverijns, N., Brock-mann, C., Quast, R., Wevers, J., Grosu, A., Paccini, A., Vergnaud, S., Cartus, O., Santoro, M., Fritz, S., Lesiv, M., Arino, O., & WorldCover Consortium. (2021). ESA WorldCover 10 m 2020 v100 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7254221
50. Monmonier, M. (2018). How to lie with maps (3rd ed.). University of Chicago Press.