{"title":"时序图代数在植被指数合成中的应用与分析","authors":"P. Mali, C. O'Hara, B. Shrestha, V. Vijayaraj","doi":"10.1109/AMTRSI.2005.1469847","DOIUrl":null,"url":null,"abstract":"Temporal image cubes are created using co-registered temporal image data sets as ordered stacks of bands within a multi-band image. These may be manipulated and analyzed using new temporal map algebra (TMA) functions that extend normal raster map algebra from operating on a single raster band to operating on one, many, or all bands within the temporal image cube. Temporal image cubes can be constructed to encode attribute information such as image quality, scan angle, or other attribute per each pixel. Multiple cubes may be utilized to manipulate image data and generate model-specific results. Low resolution imagery such as NOAA-AVHRR and MODIS require the use maximum value compositing (MVC) that consider local pixel values in time series multi-temporal NDVI image cube. Using temporal map algebra multiple criteria may be imposed on attribute cubes to create masks cubes that can select from temporal image cubes only those specific pixels that meet scan angle, quality, or other user-defined criteria. After reducing the image data to only the desired pixels, local and focal functions may be employed to create custom composites for specific temporal intervals.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Use and analysis of temporal map algebra for vegetation index compositing\",\"authors\":\"P. Mali, C. O'Hara, B. Shrestha, V. Vijayaraj\",\"doi\":\"10.1109/AMTRSI.2005.1469847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Temporal image cubes are created using co-registered temporal image data sets as ordered stacks of bands within a multi-band image. These may be manipulated and analyzed using new temporal map algebra (TMA) functions that extend normal raster map algebra from operating on a single raster band to operating on one, many, or all bands within the temporal image cube. Temporal image cubes can be constructed to encode attribute information such as image quality, scan angle, or other attribute per each pixel. Multiple cubes may be utilized to manipulate image data and generate model-specific results. Low resolution imagery such as NOAA-AVHRR and MODIS require the use maximum value compositing (MVC) that consider local pixel values in time series multi-temporal NDVI image cube. Using temporal map algebra multiple criteria may be imposed on attribute cubes to create masks cubes that can select from temporal image cubes only those specific pixels that meet scan angle, quality, or other user-defined criteria. After reducing the image data to only the desired pixels, local and focal functions may be employed to create custom composites for specific temporal intervals.\",\"PeriodicalId\":302923,\"journal\":{\"name\":\"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AMTRSI.2005.1469847\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AMTRSI.2005.1469847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use and analysis of temporal map algebra for vegetation index compositing
Temporal image cubes are created using co-registered temporal image data sets as ordered stacks of bands within a multi-band image. These may be manipulated and analyzed using new temporal map algebra (TMA) functions that extend normal raster map algebra from operating on a single raster band to operating on one, many, or all bands within the temporal image cube. Temporal image cubes can be constructed to encode attribute information such as image quality, scan angle, or other attribute per each pixel. Multiple cubes may be utilized to manipulate image data and generate model-specific results. Low resolution imagery such as NOAA-AVHRR and MODIS require the use maximum value compositing (MVC) that consider local pixel values in time series multi-temporal NDVI image cube. Using temporal map algebra multiple criteria may be imposed on attribute cubes to create masks cubes that can select from temporal image cubes only those specific pixels that meet scan angle, quality, or other user-defined criteria. After reducing the image data to only the desired pixels, local and focal functions may be employed to create custom composites for specific temporal intervals.