多尺度空间数据库建立中的关键技术与对策

多尺度空间数据表达及数据库建立具有广阔的应用前景，在流媒体网络数据传输、自适应动态可视化、空间认知导航、互操作尺度匹配多个领域都有重要作用，但实现该技术面临着数据存储量大、操作响应慢、横向空间一致关系难以维护、尺度变化难以达到真正的连续性等诸多问题。针对这些问题提出了实现多尺度空间数据表达的4种技术策略；多级尺度显式存储、初级尺度变化累积、关键尺度函数演变和初级尺度自动综合；其中，结合算法实例重点讨论的初级尺度变化累积模型，借鉴了视频数据压缩的思想，是本研究领域的一种新方法。

KEY TECHNOLOGIES AND STRATEGIES IN THE DEVELOPMENT OF MULTI-SCALE SPATIAL DATABASE

Multi-scale representation and multi-scale spatial database play an important role in such fields as the transmission of streaming media data over the web, the self-adaptable visualization of spatial information, the navigation in spatial cognition, the scale match during inter-operation and other applications. Realizing this technology has to resolve the questions including the large data volume, the slow response, the conflicts between data representations and the steep change in scale range. This study aims at the questions above presenting four strategies: storing data of multi-scale versions, accumulating changes based on the initial version, transferring between key state versions and generalizing to derive any version based on the initial state. Among four strategies, the changes accumulation model has been attached importance to be a new method which borrows the ideas from the technology of video data compress.