E. Mesrobian, R. Muntz, J. R. Santos, E. C. Shek, C. Mechoso, J. Farrara, P. Stolorz
{"title":"从地球科学数据集中提取时空模式","authors":"E. Mesrobian, R. Muntz, J. R. Santos, E. C. Shek, C. Mechoso, J. Farrara, P. Stolorz","doi":"10.1109/VMV.1994.324983","DOIUrl":null,"url":null,"abstract":"A major challenge facing geophysical science today is the unavailability of high-level analysis tools with which to study the massive amount of data produced by sensors or long simulations of climate models. We have developed a prototype information system called QUEST to provide content-based access to massive datasets. QUEST employs workstations as well as teraFLOP computers to analyze geoscience data to produce spatial-temporal features that can be used as high-level indexes. Our first application area is global change climate modeling. In the initial prototype, the first features extracted are cyclones trajectories from the output of multi-year climate simulations produced by a General Circulation Model. We present an algorithm for cyclone extraction and illustrate the use of cyclone indexes to access subsets of GCM data for further analysis and visualization.<<ETX>>","PeriodicalId":380649,"journal":{"name":"Proceedings of Workshop on Visualization and Machine Vision","volume":"333 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Extracting spatio-temporal patterns from geoscience datasets\",\"authors\":\"E. Mesrobian, R. Muntz, J. R. Santos, E. C. Shek, C. Mechoso, J. Farrara, P. Stolorz\",\"doi\":\"10.1109/VMV.1994.324983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A major challenge facing geophysical science today is the unavailability of high-level analysis tools with which to study the massive amount of data produced by sensors or long simulations of climate models. We have developed a prototype information system called QUEST to provide content-based access to massive datasets. QUEST employs workstations as well as teraFLOP computers to analyze geoscience data to produce spatial-temporal features that can be used as high-level indexes. Our first application area is global change climate modeling. In the initial prototype, the first features extracted are cyclones trajectories from the output of multi-year climate simulations produced by a General Circulation Model. We present an algorithm for cyclone extraction and illustrate the use of cyclone indexes to access subsets of GCM data for further analysis and visualization.<<ETX>>\",\"PeriodicalId\":380649,\"journal\":{\"name\":\"Proceedings of Workshop on Visualization and Machine Vision\",\"volume\":\"333 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Workshop on Visualization and Machine Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VMV.1994.324983\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Workshop on Visualization and Machine Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VMV.1994.324983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting spatio-temporal patterns from geoscience datasets
A major challenge facing geophysical science today is the unavailability of high-level analysis tools with which to study the massive amount of data produced by sensors or long simulations of climate models. We have developed a prototype information system called QUEST to provide content-based access to massive datasets. QUEST employs workstations as well as teraFLOP computers to analyze geoscience data to produce spatial-temporal features that can be used as high-level indexes. Our first application area is global change climate modeling. In the initial prototype, the first features extracted are cyclones trajectories from the output of multi-year climate simulations produced by a General Circulation Model. We present an algorithm for cyclone extraction and illustrate the use of cyclone indexes to access subsets of GCM data for further analysis and visualization.<>