对空间数据多尺度表达有关问题的思考

多尺度空间数据表达及数据库建立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贡献，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四种技术策略。

Key Issues of Multi-Scale Representation of Spatial Data

Multi-scale representation and multi-scale spatial database plays an important role in such fields as the transmission of streaming media data over 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.