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Remote Sensing Method Of Water Pollution And Application On Water Pollution Monitoring In ShaoXing Area

Posted on:2009-05-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiuFull Text:PDF
GTID:2121360272462336Subject:Structural geology
Abstract/Summary:PDF Full Text Request
The traditional approaches of monitoring water quality are mostly by doing physical and chemical analysis on the water samples, and then calculate the water quality evaluation.When the monitoring object is a wide range of water, the traditional approaches have to get a large number of water samples; the shortcomings are not only heavy workload, but also high cost and long cycle.With the rapid development of technology, remote sensing technology has proved to be a fast and economical method in monitoring the water environment. Time-spatial distribution images could observe the same water in different historical periods, research water pollution distribution characteristics and the trend, it is useful for water protection and programming.This paper introduces the remote sensing mechanism and methods of water pollution and application on water pollution monitoring in shaoxing area. The research indicates that it can be found that water reflectance in VI—NIR bands becomes decreasing as the increase of water pollution. Through comparison, classification and segmentation image of remote sensing distinguish and recognize water polluting more effectively after logarithm,IHS and K-L transformation. Time-spatial distribution images of water pollution are made through the above techniques, and the time-spatial distribution characteristics and changing trends are summarized through combination to ground analytical and investigation data of water quality. With linear regression and factor analysis, we established a model between the DN value of TM images and the ground water pollution data, suggesting that the model is applicable for the estimation of water quality in shaoxing area.
Keywords/Search Tags:Shaoxing area, Water pollution, Time-spatial distribution images, Remote Sensing
PDF Full Text Request
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