{"title":"融合图像和地图","authors":"M. Carlotto","doi":"10.1117/12.780170","DOIUrl":null,"url":null,"abstract":"Spatial data sharpening techniques that fuse images and maps are described. The statistical basis of these techniques are reviewed and extended for sharpening other kinds of spatial data that can be difficult to collect in denied areas. One example is demographic data. We demonstrate the ability to derive high-resolution population maps from county or district census data and Landsat imagery that is accurate to within 5% of the true population within a test area.","PeriodicalId":133868,"journal":{"name":"SPIE Defense + Commercial Sensing","volume":"12 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fusing images and maps\",\"authors\":\"M. Carlotto\",\"doi\":\"10.1117/12.780170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spatial data sharpening techniques that fuse images and maps are described. The statistical basis of these techniques are reviewed and extended for sharpening other kinds of spatial data that can be difficult to collect in denied areas. One example is demographic data. We demonstrate the ability to derive high-resolution population maps from county or district census data and Landsat imagery that is accurate to within 5% of the true population within a test area.\",\"PeriodicalId\":133868,\"journal\":{\"name\":\"SPIE Defense + Commercial Sensing\",\"volume\":\"12 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPIE Defense + Commercial Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.780170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPIE Defense + Commercial Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.780170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial data sharpening techniques that fuse images and maps are described. The statistical basis of these techniques are reviewed and extended for sharpening other kinds of spatial data that can be difficult to collect in denied areas. One example is demographic data. We demonstrate the ability to derive high-resolution population maps from county or district census data and Landsat imagery that is accurate to within 5% of the true population within a test area.
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