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SOME KEY TECHNIQUES ON UPDATING SPATIAL DATA INFRASTRUCTURE BY SATELLITE REMOTE SENSING IMAGERY

机译:卫星遥感图像更新空间数据基础架构的一些关键技术

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In general only a small part of spatial data in SDI change because of different factors, so rapid and effective updating methods are very vital. With the improvement of spatial resolution of satellite remote sensing (RS) imagery, it is possible to update spatial data infrastructure efficiently by satellite RS images. But the RS data volume is vast, so high processing capacity is required. It is impossible to update spatial data without the support of high performance of RS image management, retrieval, and change detection and pattern discovery. After introducing some background information including significance of SDI updating, feasibility and advantages of satellite RS imagery used to update spatial data, the framework of updating spatial and attribute information based on RS image is proposed. In the process, the integrated processing of raster data and vector data is very important, so some functions of RS image processing and GIS software should be fused. In order to extract the anticipated images from vast image database, effective retrieval technique is vital. Based on content-based image retrieval, content-based RS image retrieval is put forward and some topics including retrieval pattern, useful image content, feature extraction and similarity measure are researched. After related images are retrieved from vast image database, it is necessary to discover those change areas, so change detection from multi-temporal RS images are discussed further. RS image data mining and knowledge discovery is the synergy of Spatial Data Mining (SDM) and Image Data Mining (IDM). Oriented to the demands of SDI updating to intelligent information processing, some primary issues on RSDM are analysed. It is pointed out that updating SDI by satellite RS imagery will be potential advantageous in the future, and all the techniques discussed in this paper including content-based RS image retrieval, change detection, multi-temporal RS image fusion and RS Data Mining and Knowledge Discovery are very important and will play important roles in the future.
机译:通常只有不同因素,SDI变化中只有一小部分空间数据,因此快速有效的更新方法非常重要。随着卫星遥感(RS)图像的空间分辨率的改进,可以通过卫星RS图像有效更新空间数据基础架构。但RS数据量差,因此需要高处理能力。不可能更新空间数据而不支持RS图像管理,检索和改变检测和模式发现的高性能。在引入包括SDI更新的重要性的一些背景信息之后,提出了用于更新空间数据的卫星RS图像的可行性和优点,提出了基于RS图像的更新空间和属性信息的框架。在此过程中,光栅数据和矢量数据的集成处理非常重要,因此应融合RS图像处理和GIS软件的某些功能。为了从大型图像数据库中提取预期的图像,有效的检索技术至关重要。基于基于内容的图像检索,提出了基于内容的RS图像检索,并且研究了一些包括检索模式,有用图像内容,特征提取和相似度量的话题。在从巨大图像数据库中检索相关图像之后,需要发现这些改变区域,因此进一步讨论从多时间RS图像的变化检测。 RS图像数据挖掘和知识发现是空间数据挖掘(SDM)和图像数据挖掘(IDM)的协同作用。面向SDI更新对智能信息处理的需求,分析了RSDM的一些主要问题。有望通过卫星RS图像更新SDI将来是潜在的未来有利的,并且本文讨论的所有技术包括基于内容的RS图像检索,改变检测,多时间RS图像融合和RS数据挖掘和知识发现是非常重要的,将来会发挥重要作用。

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