H. Hong, Yang Feng-jie, Zhou Guang-zhu, Li Yin-ming
{"title":"重金属出版社矿山植被光谱特征与回归模型研究","authors":"H. Hong, Yang Feng-jie, Zhou Guang-zhu, Li Yin-ming","doi":"10.1109/ETCS.2010.398","DOIUrl":null,"url":null,"abstract":"Vegetation reflectance spectra in field with spectrometer to be tested in this study, used eight kinds of spectral parameters to analysis spectral of vegetation, six kinds of heavy metal content in plant leaves to be measured, then the regression model from the spectral characteristic parameters to the heavy metal content can be built, according to this can inverse heavy metal content with spectral parameters, further analysis the pollution extent of mine vegetation. Sampling areas were polluted by Cr more seriously, secondly was Ni. The 4th point was polluted most seriously by the heavy metal, The regression equations of Pb, Cu, Zn heavy metals had high correlation coefficient. The red valley area and the water absorption area with the Zn content in leaves had a high linear correlation, the red valley depth and the water absorption depth with the Cu content in leaves had a high linear correlation.","PeriodicalId":193276,"journal":{"name":"2010 Second International Workshop on Education Technology and Computer Science","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Notice of RetractionSpectral Features and Regression Model of Mine Vegetation in the Press of Heavy Metal\",\"authors\":\"H. Hong, Yang Feng-jie, Zhou Guang-zhu, Li Yin-ming\",\"doi\":\"10.1109/ETCS.2010.398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vegetation reflectance spectra in field with spectrometer to be tested in this study, used eight kinds of spectral parameters to analysis spectral of vegetation, six kinds of heavy metal content in plant leaves to be measured, then the regression model from the spectral characteristic parameters to the heavy metal content can be built, according to this can inverse heavy metal content with spectral parameters, further analysis the pollution extent of mine vegetation. Sampling areas were polluted by Cr more seriously, secondly was Ni. The 4th point was polluted most seriously by the heavy metal, The regression equations of Pb, Cu, Zn heavy metals had high correlation coefficient. The red valley area and the water absorption area with the Zn content in leaves had a high linear correlation, the red valley depth and the water absorption depth with the Cu content in leaves had a high linear correlation.\",\"PeriodicalId\":193276,\"journal\":{\"name\":\"2010 Second International Workshop on Education Technology and Computer Science\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Workshop on Education Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETCS.2010.398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Workshop on Education Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCS.2010.398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Notice of RetractionSpectral Features and Regression Model of Mine Vegetation in the Press of Heavy Metal
Vegetation reflectance spectra in field with spectrometer to be tested in this study, used eight kinds of spectral parameters to analysis spectral of vegetation, six kinds of heavy metal content in plant leaves to be measured, then the regression model from the spectral characteristic parameters to the heavy metal content can be built, according to this can inverse heavy metal content with spectral parameters, further analysis the pollution extent of mine vegetation. Sampling areas were polluted by Cr more seriously, secondly was Ni. The 4th point was polluted most seriously by the heavy metal, The regression equations of Pb, Cu, Zn heavy metals had high correlation coefficient. The red valley area and the water absorption area with the Zn content in leaves had a high linear correlation, the red valley depth and the water absorption depth with the Cu content in leaves had a high linear correlation.