Auto digitization of aerial images to map generation from UAV feed

Abstract

Nowadays the rapid growth of unmanned aerial vehicles (UAVs) bridges the space between worldly and airborne photogrammetry as well as allow flexible acquisition of great solution images. In the case of natural disasters such as floods, tsunamis, earthquakes, and cyclones, their effects are most often felt in the micro-spaces and urban environments. Therefore, rescuers have to go around to get to the victims. This paper presents an auto digitization of aerial images to map generation from UAV feed at night time. In case of a power outage and an absence of alternative light sources, rescue operations are also slowed due to the darkness caused by the lack of electricity and the inability to light additional sources. In other words, to save lives, we need to know about all essential large-scale feature spaces in the dark so that we can use this information in times of disaster. The research proposed a soft framework for crisis mapping to aid in mapping the state of the aerial landscape in disaster-stricken areas, allowing strategic rescue operations to be more effectively planned.