{"title":"国内大规模高光谱数据处理及地质应用的高效解决方案","authors":"Junchuan Yu, Bokun Yan","doi":"10.1109/RSIP.2017.7970774","DOIUrl":null,"url":null,"abstract":"As we have entered an era of information, the RS data are undergoing a plosive growth. The needs of large-scale earth observation have led to the development of high-resolution and high-dimensionality RS data, which has posed significant challenges in processing and application. In this paper, we demonstrate some possible solution of large-scale domestic hyperspectral data processing and geological application, mainly from three aspects.","PeriodicalId":262222,"journal":{"name":"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)","volume":"2005 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Efficient solution of large-scale domestic hyperspectral data processing and geological application\",\"authors\":\"Junchuan Yu, Bokun Yan\",\"doi\":\"10.1109/RSIP.2017.7970774\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As we have entered an era of information, the RS data are undergoing a plosive growth. The needs of large-scale earth observation have led to the development of high-resolution and high-dimensionality RS data, which has posed significant challenges in processing and application. In this paper, we demonstrate some possible solution of large-scale domestic hyperspectral data processing and geological application, mainly from three aspects.\",\"PeriodicalId\":262222,\"journal\":{\"name\":\"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)\",\"volume\":\"2005 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RSIP.2017.7970774\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RSIP.2017.7970774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient solution of large-scale domestic hyperspectral data processing and geological application
As we have entered an era of information, the RS data are undergoing a plosive growth. The needs of large-scale earth observation have led to the development of high-resolution and high-dimensionality RS data, which has posed significant challenges in processing and application. In this paper, we demonstrate some possible solution of large-scale domestic hyperspectral data processing and geological application, mainly from three aspects.
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