Unmanned aerial vehicle remote-sensing image building three-dimensional damage detection method

Abstract

An unmanned aerial vehicle remote-sensing image building three-dimensional damage detection method comprises the steps of generating a pre-disaster DSM and a post-disaster DSM, carrying out registering, identifying suspected damaged building area, obtaining vector information of a building according to the pre-disaster DSM, further segmenting a pre-disaster building area and a post-disaster building area, carrying out characteristic extraction according to the segmenting result of the pre-disaster building area and the segmenting result of the post-disaster building area, obtaining characteristic evidence, calculating the confidence coefficient of collapse and damage of the building according to the principle of an evidence theory by using the characteristic evidence and obtaining a detection result. The unmanned aerial vehicle remote-sensing image building three-dimensional damage detection method makes full use of point cloud three-dimensional information generated by multiple overlapped images, and obviously improves the accuracy of detecting the damage to the building by combining the house damage characteristics of remote-sensing images before and after the disaster.

Description

technical field [0001] The invention relates to the technical field of remote sensing image applications, in particular to a method for detecting three-dimensional damage to buildings in remote sensing images of drones. Background technique [0002] After a natural disaster occurs, how to quickly detect and evaluate the damage of houses in the disaster is of great significance. It can timely and accurately understand the affected area and disaster level, so that corresponding emergency measures can be made quickly. As a new type of remote sensing monitoring platform, unmanned aerial vehicle (UAV) has a high degree of intelligence in flight operation. It can fly autonomously and take pictures according to the predetermined route, and provide remote sensing monitoring data and low-altitude video monitoring in real time. It has the characteristics of strong mobility, convenience, and low cost. The obtained high-resolution overlapping remote sensing data has the characteristics...

AI Technical Summary

Problems solved by technology

From the traditional extraction method based on the pixel level to the current mainstream object-oriented technology extraction method, combined with various features of the image, including geometric structure, shape, edge, texture, color, etc., to extract building damage information ; but this method is difficult to extract the height change information of the building, even if the height of some buildings can be obtained by using shadows, etc., it is not universal

2) The building damage information extraction method using two / multi-temporal remote sensing images, the core idea is remote sensing change detection, through the comparison of remote sensing image changes before and after the disaster, the building damage information is extracted; these methods are mainly based on changes in two-dimensional data Detection, it is difficult to detect the height change information of the building, and it has inherent defects in the detection of those buildings whose height changes such as partial collapse, overall settlement, lower part collapse or middle layer collapse

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