METHODS TO DETECT EXPLOSIVE HAZARDS IN AGRICULTURAL AREAS

Background. Contamination of agricultural land with explosive ordnance (EO) following the war unleashed by the Russian Federation poses a significant threat to the life and health of farmers and hinders the restoration of agricultural activities. Detection and neutralization of EO is a complex and dangerous process that requires a comprehensive approach. This article examines the main types of landmines found in Ukraine, outlines the main revealing factors of explosive ordnance, analyzes existing methods and technologies for detecting EO on agricultural land, and evaluates their advantages and disadvantages. Results. The application of UAVs in humanitarian demining demonstrates significant potential for risk reduction and accelerated clearance of affected territories from explosive ordnance. Specifically, aerial photography and thermal imaging scanning via UAVs prove effective for the initial inspection of extensive areas and the identification of potentially hazardous zones. The application of metal detectors and geophysical methods allows for the optimization of further efforts. The integration of geographic information systems (GIS) with artificial intelligence (AI) offers a promising auxiliary approach. By leveraging satellite imagery and machine learning, AI can analyze extensive datasets to detect and classify changes in land resources resulting from military actions. Besides, it plays a crucial role in rapid and accurate monitoring of affected territories. Based on the test plots in the Kyiv and Kharkiv regions, this study demonstrates the practical application of Earth remote sensing data, GIS spatial analysis, and machine learning for EO detection on agricultural lands. Conclusions. Traditional methods of mine detection and disposal are labour-intensive, dangerous, and often ineffective. Applying a combination of diverse EO detection methods (metal detectors, mechanical methods, geophysical methods, biophysical methods, UAVs with aerial photography and thermal imaging scanning, and other sensors) and integrating modern technologies (remote sensing tools and artificial intelligence) allows for achieving maximum survey efficiency and increasing safety. Each method has its advantages and limitations, and combining them promotes compensating for the shortcomings of individual methods.