Digital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA Imagery

数字政府：美国地质调查局和NIMA图像的超大规模多维数据管理和检索本项目将对合作政府机构（美国地质调查局（USGS）和美国国家成像和测绘局（NIMA））持有的多维数据进行管理和检索研究。在这种应用中，必须在其他地点提供分布在偏远地点的地理图像数据库，以便检索数据。随着基于内容的图像数据检索的出现，传统的数据库设计和查询搜索方法将不适合开发分布式图像检索系统。本研究的目的是探索新的方法，以支持在互联网上有效和高效地访问综合地理图像数据库。这些方法将为分布式地理图像检索系统的设计奠定基础。与设计这种集成相关的技术挑战是在图像数据库之上创建元级系统。具体的研究目标是：(1)确定地理图像的多尺度表示（多维）方法；(2)研究可以检测任意形状的多维图像数据聚类的新聚类方法；(3)构建元数据模型，该模型制定集成系统对相关数据库进行可视化查询所需的元数据；(4)发展基于元数据的数据库选择方法的理论基础。(5)设计集成从视觉数据内容中提取的异构特征的新型视觉查询处理方法。在项目期间，USGS和NIMA将提供所有必要的图像数据集及其类别。在项目期间结束时，将在美国地质勘探局和NIMA站点传播一个系统。通过上述研究活动，将提供基本的理解和新技术，以支持在互联网上分布的多维数据的分布式容量的设计，并将为其他政府机构（如NASA）的分布式图像数据库系统的开发提供广泛的模板应用。所生成的实验结果可用于建立有效的基准，以评估分布式图像数据检索系统的性能。

EIA-9983430Zhang, AidongSUNY BuffaloDigital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA ImageryThis project will conduct research on managing and retrieving multidimensional data held by partner government agencies (the United States Geological Survey (USGS) and the National Imaging and Mapping Agency (NIMA)). In such applications, geographic image databases distributed at remote locations must be made available at other locations for purpose of data retrieval. With the advent of content-based retrieval of image data, traditional methods for database design and query search will not be suitable in developing distributed image retrieval systems.The objective of the proposed research is to investigate novel approaches to supporting effective and efficient access to the integrated geographic image databases over the Internet. These approaches will establish a foundation for the design of distributed geographic image retrieval systems. The technical challenge relating to the design of such integration is the creation of meta-level system on top of the image databases. The specific research goals are : (1) identify multi-scale representation (multidimensional) methods for geographic images, (2) investigate novel clustering approaches that can detect clusters of arbitrary shape of multidimensional image data, (3) construct a metadata model that formulates the metadata that are needed for the integrated system to direct a visual query to relevant databases, (4) develop the theoretical foundation of database selection approaches based on the metadata, and (5) design novel visual query processing approaches that integrate heterogeneous features extracted from the content of visual data.During the project period, USGS and NIMA will provide all necessary imagery data sets and their categories. A system will be disseminated at both USGS and NIMA sites at the end of the project period. Through the above research activities, the fundamental understanding and novel techniques will be provided to support the design of distributed volume of multidimensional data distributed over the Internet and will find broad applications as a template for the development of distributed image database system in other government agencies, such as NASA. The experimental results to be generated can be used to establish effective benchmarks for assessing the performance of distributed image data retrieval systems.