{"title":"利用航空高光谱数据对黄铁矿尾矿表面pH值进行表征","authors":"Natalie Zabcic, B. Rivard, C. Ong, A. Müller","doi":"10.1109/WHISPERS.2009.5289015","DOIUrl":null,"url":null,"abstract":"High spatial-resolution Hymap airborne hyperspectral data was used to generate predictive pH maps of acid mine drainage (AMD) for the Sotiel-Migollas mine complex, Southwest Spain. These maps portray the spatial distribution of highly acidic areas, which are likely associated with high concentrations of heavy metals. A predictive pH model was built using partial least squares (PLS) analysis to determine the relationship between the spectral response of AMD samples and their leachate pH measured in the laboratory. A validation of the model for an independent data set shows a r2 of 0.71 between actual and predicted pH values. Hyperspectral imagery is shown to provide an effective means to quantitatively pinpoint sources of acidity.","PeriodicalId":242447,"journal":{"name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Using airborne hyperspectral data to characterize the surface pH of pyrite mine tailings\",\"authors\":\"Natalie Zabcic, B. Rivard, C. Ong, A. Müller\",\"doi\":\"10.1109/WHISPERS.2009.5289015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High spatial-resolution Hymap airborne hyperspectral data was used to generate predictive pH maps of acid mine drainage (AMD) for the Sotiel-Migollas mine complex, Southwest Spain. These maps portray the spatial distribution of highly acidic areas, which are likely associated with high concentrations of heavy metals. A predictive pH model was built using partial least squares (PLS) analysis to determine the relationship between the spectral response of AMD samples and their leachate pH measured in the laboratory. A validation of the model for an independent data set shows a r2 of 0.71 between actual and predicted pH values. Hyperspectral imagery is shown to provide an effective means to quantitatively pinpoint sources of acidity.\",\"PeriodicalId\":242447,\"journal\":{\"name\":\"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WHISPERS.2009.5289015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2009.5289015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using airborne hyperspectral data to characterize the surface pH of pyrite mine tailings
High spatial-resolution Hymap airborne hyperspectral data was used to generate predictive pH maps of acid mine drainage (AMD) for the Sotiel-Migollas mine complex, Southwest Spain. These maps portray the spatial distribution of highly acidic areas, which are likely associated with high concentrations of heavy metals. A predictive pH model was built using partial least squares (PLS) analysis to determine the relationship between the spectral response of AMD samples and their leachate pH measured in the laboratory. A validation of the model for an independent data set shows a r2 of 0.71 between actual and predicted pH values. Hyperspectral imagery is shown to provide an effective means to quantitatively pinpoint sources of acidity.