Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Manifold learning-based method for monitoring water quality by remote sensing

A technology of water quality monitoring and manifold learning, applied in color/spectral characteristic measurement, instrumentation, scene recognition, etc., can solve problems such as not revealing the essential laws of multispectral remote sensing image data, reducing the reliability of water quality evaluation results, etc.

Inactive Publication Date: 2012-10-03
CHONGQING UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This means that the traditional water quality evaluation model cannot effectively discover the essential laws in the multispectral data, and does not reveal the essential laws hidden in the multispectral remote sensing image data, which reduces the reliability of the water quality evaluation effect.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Manifold learning-based method for monitoring water quality by remote sensing
  • Manifold learning-based method for monitoring water quality by remote sensing
  • Manifold learning-based method for monitoring water quality by remote sensing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0085] refer to figure 1 , a remote sensing water quality monitoring method based on manifold learning, comprising the following steps:

[0086] (1) Read the remote sensing image data into the computer, and extract the rectangular area including the water body;

[0087] (2) Mask each band of the remote sensing image by using the mask matrix, and remove the background information from the image to generate remote sensing data that only includes the entire water body;

[0088] (3) Obtain the water quality remote sensing data of each monitoring point and the corresponding water quality parameter field monitoring data, select the water quality remote sensing data of some monitoring points as samples, and calculate the Euclidean distance between the sample points;

[0089] (4) According to the Euclidean distance between the sample points, construct the weight matrix of neighbors and the weight matrix of non-nearest neighbors;

[0090] (5) Use the nearest neighbor weight matrix an...

Embodiment 2

[0137] The method of the invention is used to monitor the water quality of the remote sensing image data of the water quality of the Shaanxi section of the Weihe River in 2006. In 2006, the remote sensing images of water quality in the Shaanxi section of the Weihe River had 4 bands, with a total of 3451×3654 data. The range of [1260:2100, 400:2300] was selected to include all monitoring points, including Gengzhen and Chengyang, with a total of 841×1901 data, including 60944 water body data. At the same time, a total of 13 sets of water quality remote sensing data and corresponding field monitoring data were obtained from 2000 to 2006 at some monitoring points in the Shaanxi section of the Wei River. The data are distributed in 9 monitoring sections of the Shaanxi section of the Wei River. The water quality parameters include the permanganate index of each monitoring point. (COD mn ) and so on, since the pollution in the Shaanxi section of the Weihe River is mainly organic pol...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a manifold learning-based method for monitoring water quality by remote sensing, and particularly relates to a manifold learning-based method for monitoring water quality by multispectral remote sensing, which comprises the following steps of: training a sample point by a manifold learning method to obtain a projection matrix of water quality remote sensing data in low-dimensional embedded space; building a nonlinear model by using a support vector regression algorithm according to a feature matrix of the low-dimensional embedded space of the sample point and corresponding water quality parameter site monitoring data; and inverting an integral water body by utilizing the nonlinear model to obtain a concentration value of a water quality parameter of the integral water quality, and providing different colors for the water body according to different intervals in which the water body is positioned to display the concentration condition of the water quality parameter of the integral water body visually, so that the water quality evaluation and monitoring of the water body are realized. In the method, the essential law hidden in multispectral remote sensing image data is disclosed effectively, and the nonlinear problem of the water quality evaluation is solved.

Description

technical field [0001] The invention relates to the technical field of water quality monitoring methods and applications, in particular to a multispectral remote sensing water quality monitoring method based on manifold learning. Background technique [0002] Judging from the current situation of water resources in various provinces and cities in my country, the shortage of total water resources and the deterioration of water quality are widespread. It is an inland water body, and its water quality directly affects national production and people's daily life, and the solution of water quality problems is imminent. Therefore, it is necessary to strengthen the monitoring of water quality, understand and master the degree and development trend of water pollution, and strengthen water pollution control. Water quality monitoring data is the basis for water quality evaluation. Traditional water quality monitoring is to collect water samples on site, and then measure and analyze th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/25G01N21/27G06N99/00G06V20/13
CPCG06K9/0063G06V20/13
Inventor 黄鸿冯海亮王立志秦高峰何同弟
Owner CHONGQING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com