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

机译:利用卫星遥感影像更新空间数据基础设施的一些关键技术

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摘要

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,由于不同的因素,SDI中的空间数据只有一小部分发生变化,因此快速有效的更新方法至关重要。随着卫星遥感(RS)图像空间分辨率的提高,有可能通过卫星RS图像有效地更新空间数据基础结构。但是RS数据量巨大,因此需要高处理能力。没有高性能的RS图像管理,检索以及变化检测和模式发现,就不可能更新空间数据。在介绍了SDI更新的意义,卫星RS图像用于空间数据更新的可行性和优点等背景信息之后,提出了一种基于RS图像的空间和属性信息更新框架。在此过程中,栅格数据和矢量数据的集成处理非常重要,因此应该融合RS图像处理和GIS软件的某些功能。为了从庞大的图像数据库中提取预期的图像,有效的检索技术至关重要。在基于内容的图像检索的基础上,提出了基于内容的遥感图像检索,研究了检索模式,有用图像内容,特征提取和相似性度量等主题。从庞大的图像数据库中检索到相关图像后,有必要发现那些变化区域,因此将进一步讨论多时间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。针对SDI更新对智能信息处理的需求,分析了RSDM的一些主要问题。需要指出的是,通过卫星RS影像更新SDI将在未来具有潜在的优势,本文讨论的所有技术包括基于内容的RS影像检索,变化检测,多时间RS影像融合以及RS数据挖掘和知识。发现非常重要,并将在未来发挥重要作用。

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