Identification of Dangerous Rural Houses Using Oblique Photogrammetry and Photo Recognition Technology

Abstract

Indentify dangerous houses in rural areas isn’t very efficient, considering the large workload to visit the rural area, patchy and untimely manual document’s registration management. This study first uses UAV oblique photography technology to quickly obtain high-resolution aerial photographic images of villages and reconstruct three-dimensional reality models. Then, based on the YOLOv5 algorithm, the features of dangerous houses in aerial photography images are automatically detected, and the features of dangerous houses are mapped to the real 3D model to accurately locate the dangerous buildings. Finally, a digital management platform for rural dangerous houses is developed to support rural managers in identifying, measuring and tracking dangerous houses. The application results in a village along the coast of southern Fujian province showed that the accuracy rate of the final dangerous house screening rate of this method was 92%, and the coverage rate was 95%, which could greatly improve the efficiency, accuracy and coverage of dangerous house screening and reduce the workload of manual screening; and improve management efficiency through platform-based and visual methods.