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Automatic division method for catchment area of urban drainage pipe network

A drainage pipe network and automatic division technology, applied in the direction of neural learning methods, biological neural network models, instruments, etc., can solve the problem of low efficiency of catchment area division, achieve division accuracy improvement, improve modeling efficiency, and accelerate modeling The effect of the process

Active Publication Date: 2021-04-27
HARBIN INST OF TECH
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AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of low efficiency of existing water catchment division, the present invention provides an automatic division method of urban drainage pipe network water catchment

Method used

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  • Automatic division method for catchment area of urban drainage pipe network
  • Automatic division method for catchment area of urban drainage pipe network
  • Automatic division method for catchment area of urban drainage pipe network

Examples

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specific Embodiment

[0126] In a certain city A, the environment configuration uses an Intel(R) Core(TM) i9-9700K processor with a main frequency of 4.0GHz, a memory of 64GB, and an NVIDIA GTX 2080Ti graphics card with 11GB of video memory. The specific process is as follows:

[0127] Step 1. Image acquisition and preprocessing of the target area of ​​city A:

[0128] Use the omnipotent map downloader to download the remote sensing image and road extraction layer of city A from Google Earth; use ArcGIS to vectorize the remote sensing image and road extraction layer of the same geographical location and crop them into 1024×1024 primitives;

[0129] The preprocessing includes: performing HSV contrast transformation and spatial geometric transformation data enhancement processing on the original remote sensing image of city A; cutting the enhanced remote sensing image of city A and the road extraction layer according to 1024×1024; performing binary value processing on the road extraction layer proce...

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Abstract

The invention discloses an automatic division method for a catchment area of an urban drainage pipe network, solves the problem of low division efficiency of an existing catchment area, and belongs to the field of cross application of environmental engineering, visible light remote sensing image semantic segmentation and computer vision. The method comprises the following steps: S1, acquiring a remote sensing image of an urban target area, and constructing a training data set; S2, utilizing a convolutional neural network coupling variant residual network to construct a road network extraction convolutional neural network model, and using a variant residual network as a coding structure of the convolutional neural network; S3, training a road network extraction convolutional neural network model by using the training data set, and determining parameters of the road network extraction convolutional neural network model; S4, inputting the remote sensing image of the city area to be divided into a road network extraction convolutional neural network model, and extracting road network information; and S5, dividing the extracted road network information into water catchment area, and further dividing sub-water catchment areas by using an inverse distance weighted Thiessen polygon method in combination with prior information of rainwater well point distribution.

Description

technical field [0001] The invention relates to a method for automatically dividing urban drainage pipe network catchment areas based on a convolutional neural network coupling variant residual learning unit, and belongs to the cross-application fields of environmental engineering, visible light remote sensing image semantic segmentation, and computer vision. Background technique [0002] The establishment process of the urban drainage network model mainly includes the division of catchment area, the input of pipe section parameters, the parameter setting of key wading facilities, and the calibration of sensitivity parameters. Among them, the division of catchment areas is the basis for the construction of the entire drainage network model, and the accuracy of the division results directly affects the calculation accuracy of urban rainwater infiltration, evaporation and runoff processes. [0003] In the process of traditional urban drainage network modeling, the division of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08G06K9/34G06Q50/26
CPCG06N3/08G06Q50/26G06V20/182G06V10/267G06F18/253G06F18/214
Inventor 田禹张天奇李铭马丽娜胡智超李俐频
Owner HARBIN INST OF TECH
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