Concept of a geoinformation platform for landmines and other explosive objects detection and mapping with UAV

The subject of this article is the concept of a geoinformation platform for landmine detection. Modern warfare and its increasing scale have become a relevant topic today. Undetected explosives threaten business (agriculture, logistics, etc.) and human lives. The problem becomes more acute with the rapid extension of minefield areas, which requires significant time and resources and carries high risks. Remote sensing leverages landmine detection possibilities, providing useful information about landmine displacement with no additional risk during data collection over a large area. This study aims to present a combined approach for revealing hidden landmines using UAVs equipped with different sensor types. The tasks to be solved are to define the overall structure and components of the geoinformation platform, choose the technological solutions for each of them, and implement the system prototype that makes it possible to extend its configuration in the future. The methods used are remote sensing, automated object detection, and centralized data processing in a geographic information system (GIS). Multispectral imagery and magnetometric remote measurements create the background information required to detect landmines and other explosive objects. The results of this study provide a general framework, i.e., a geoinformation platform for landmine detection and mapping. The tasks include UAV-based remote data gathering, UAV mission planning and flight control, data processing and mapping via general GIS, and updating new landmine signatures in the corresponding database. The landmine detection process uses information from the landmine signature database to verify suspicious objects. The results are presented in the form of a probabilistic map, which supports the decision-making process of demining. Conclusion. The proposed approach significantly decreases the time required for landmine detection and mitigates demining risks, which is crucial for dealing with the consequences of war. At present, the concept is being developed in the form of a geoinformation platform research prototype involving an open-source Quantum GIS (QGIS) software system and Python programming language, which is used to create plug-ins for QGIS. The entire landmine remote detection process can be fully automated. Future studies will involve extensive experimental testing and may involve convolutional neural networks (CNN) as a detection mechanism.