MAPPING MINE RISK USING LARGE-SCALE MULTISPECTRAL IMAGERY - LIASHENKO, Dmytro; ZOBNIV, Ivanna; TSVYK, Oleksandr (Visnyk of Taras Shevchenko National University of Kyiv. Geology, 2025)
Background. The full-scale armed aggression against Ukraine has resulted in significant changes in natural and anthropogenic landscapes. This negatively affects the safety of the population and the development of the country's economy. Mines, unexploded ordnance and other explosive objects pose an extraordinary threat. To identify mines, we analyzed the possibility of using spectral images obtained from UAVs for mapping.Methods. For the mapping tasks, high-resolution images of test images of the test site located in Khmelnytsky region (Ukraine) with dummy mines placed on the surface and at a shallow depth were used. Data processing was performed in ArcGIS PRO, using Python programming.Results. The article compares the methods of remote mine identification by different sensors according to the literature. A methodology for decoding high spatial resolution geo-images obtained from UAVs in the visible and thermal ranges of the spectrum to detect mines in open areas for humanitarian demining was tested. The image processing algorithm for mine detection, analysis and interpretation of the results using the Python language was further developed.Conclusions. The comparative analysis and experimental work emphasize the effectiveness of using multispectral images, in particular, the Soil Water Index (SWI) calculated on their basis, for mine identification on multispectral images obtained from UAVs. The use of SWI provides an accuracy of mine identification of only about 70% and can be used only for preliminary assessment of the contamination of territories by explosive objects.
Keywords: humanitarian demining; UAVs; remote sensing; vegetation indices; decoding; automation; mapping