CDI-Type I: International Collaboration to Study Oceanic Currents Phenomena and Climate Changes Through Cross-Mining and Retrieving Multispectral Satellite Image and Sensor Network

CDI-I型：通过交叉挖掘和检索多光谱卫星图像和传感器网络研究洋流现象和气候变化的国际合作

• 批准号: 1027854
• 负责人: James Wang
• 金额: $ 65.6万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1027854&HistoricalAwards=false
• 关键词: CDI; Type; International; Collaboration; Study

Many are concerned about climate change and one of the most important climate research problems is understanding the relationship between oceans and the global climate. A significant challenge facing climatologists and meteorologists today is making sense of the vast and continually increasing amount of data generated by earth observation satellites, radars, and sensor networks. These data are increasingly available in high-resolution image formats and must be incorporated correctly into climate change models. Timely and proper interpretation of these data can provide advanced warnings for severe weather, enabling action that minimizes the resulting damage and saving lives. Computerized systems for cross-modality image query, mining, and recovery by content are becoming essential. This project will form an international multi-disciplinary virtual organization to develop an efficient data modeling cross mining and retrieval system for satellite images and other sensor data applied to mesoscale ocean structures. The team will take a novel data-driven approach, designing an image retrieval system using advanced knowledge management and statistical learning techniques and developing advanced technologies for large-scale image and sensor network data management. These developments will advance the fields of computer and information sciences, meteorology, and climatology and the open-source platform will benefit the researchers and developers of remote sensing systems. This project will enable real-time monitoring of severe weather and climate change and the discovery and analysis of the evolution of various ocean phenomena. It will increase our knowledge of atmospheric and oceanic circulations and interactions, improving our understanding of the mechanism of climate change and clarifying the potential for environmental catastrophes and economic boondoggles. Through active collaboration with international researchers and institutions across the Atlantic and the Pacific, the virtual organization will coordinate and streamline research efforts while increasing the value of available resources and developing an international graduate student exchange program.

许多人都关心气候变化，最重要的气候研究问题之一是了解海洋和全球气候之间的关系。 气候学家和气象学家今天面临的一个重大挑战是理解地球观测卫星、雷达和传感器网络产生的大量且不断增加的数据。这些数据越来越多地以高分辨率图像格式提供，必须正确地纳入气候变化模型。 对这些数据进行及时和适当的解释可以为恶劣天气提供预先警报，从而能够采取行动，最大限度地减少所造成的损害并挽救生命。用于跨模态图像查询、挖掘和按内容恢复的计算机化系统正变得至关重要。该项目将组成一个国际多学科虚拟组织，为应用于中尺度海洋结构的卫星图像和其他传感器数据开发一个有效的数据建模、交叉挖掘和检索系统。该团队将采用一种新的数据驱动方法，使用先进的知识管理和统计学习技术设计图像检索系统，并开发用于大规模图像和传感器网络数据管理的先进技术。这些发展将推动计算机和信息科学、气象学和气候学领域的发展，开源平台将使遥感系统的研究人员和开发人员受益。该项目将能够实时监测恶劣天气和气候变化，发现和分析各种海洋现象的演变。它将增加我们对大气和海洋环流及其相互作用的了解，提高我们对气候变化机制的了解，并阐明环境灾难和经济浪费的可能性。 通过与大西洋和太平洋地区的国际研究人员和机构的积极合作，该虚拟组织将协调和简化研究工作，同时增加现有资源的价值，并制定国际研究生交流计划。