Urban inland inundation ponding area monitoring method based on deep learning technology

Abstract

The invention discloses an urban inland inundation monitoring method based on a deep learning technology. The urban inland inundation monitoring method comprises the following steps: step 1, making aninitial ponding image data set; 2, preprocessing the initial ponding image data set; step 3, performing training based on a Mask RCNN instance segmentation algorithm, and obtaining an optimal pondingmodel water.h5; 4, calibrating the camera by adopting a method based on a single-plane checkerboard, and carrying out distortion correction on the image; 5, performing perspective transformation processing; and step 6, on the basis of a water.h5 model, taking a result image subjected to perspective transformation in the step 5 as model input, and calculating and obtaining a real ponding area range. According to the method, the limitation of a traditional manual monitoring method is broken through, the real-time performance and the accuracy of ponding information acquisition in the waterlogging monitoring process are guaranteed, and powerful technical support is provided for efficiently, safely and quickly carrying out urban waterlogging monitoring work.

Description

technical field [0001] The invention belongs to the technical field of urban waterlogging monitoring, and in particular relates to a method for monitoring urban waterlogging water area based on deep learning technology. Background technique [0002] With the intensification of global climate change, the number of extreme rainstorms has increased, coupled with the rapid development of urbanization, many cities in China have frequent rainstorms and waterlogging disasters. According to statistics, since 2000, more than 200 urban waterlogging disasters of varying degrees have occurred in China every year, covering 31 provinces, and the affected population is about 100 million. The national economic loss reached 400 billion yuan. The occurrence of urban waterlogging disasters not only seriously caused the death of people due to accidents such as drowning and electric shock, but also greatly hindered urban traffic, restricted the development of social economy and China's urbaniza...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an urban waterlogging monitoring method based on deep learning technology, which solves the problem of low efficiency, difficulty, poor accuracy and waste of a lot of manpower, material and financial resources in the existing monitoring methods

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