| DOI: | 10.2172/1228822
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| 报告号: | SAND2015--10645
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| 报告题名: | PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning. |
| 作者: | Czuchlewski, Kristina Rodriguez; Hart, William E.
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| 出版年: | 2015
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| 发表日期: | 2015-09-01
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| 总页数: | 37
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| 国家: | 美国
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| 语种: | 英语
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| 中文主题词: | 雷达
; 雷达影像
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| 主题词: | RADAR
; RADAR IMAGERY
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| 英文摘要: | Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of human perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations. |
| URL: | http://www.osti.gov/scitech/servlets/purl/1228822
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| Citation statistics: |
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| 资源类型: | 研究报告
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/41782
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| Appears in Collections: | 过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响
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| 1228822.pdf（1664KB） | 研究报告 | -- | 开放获取 | | View
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| Recommended Citation: | |
Czuchlewski, Kristina Rodriguez,Hart, William E.. PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.. 2015-01-01.
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