点群多尺度表达不确定性评估方法研究

Assessment on uncertainty of multi-scale representation for point cluster

空间数据的不确定性评估是保证数据质量的重要手段。由于点群多尺度表达的不确定性非常复杂,评价指标和评估模型是点群多尺度表达不确定性评估需要亟待解决的关键问题。本文围绕点群的多尺度表达和空间分析流程,确立了点群多尺度表达不确定性的评估内容为位置不确定性和空间分析结论的不确定性,建立了点群及其多尺度表达位置不确定性的评价指标K和量化模型,并依据误差传播定律推导出了点群不同尺度上空间分析结论的不确定性的评估方法,得出点群在尺度扩展中位置和空间分析不确定性的变化规律。弥补了点群综合质量评估不考虑点群本身及其空间分析结论不确定性的弱点,为点群数据多尺度表示的质量评价提供了理论基础,为其质量控制和空间决策提供参考。

Assessment of uncertainty for spatial data is an important means to ensure the spatial data quality. Because of the com- plexity on the multi-scale expression uncertainty for point cluster, the index and model is an essential issue for assessment of multi- scale expression uncertainty on point cluster. Based on the flow of multi-scale expression of point group and spatial analysis, this paper ascertained the assessment content of multi-scale expression uncertainty for point group that includes the uncertainty of position and spa- tial analysis. The assessment indicator K and the quantitative model of the position uncertainty of point cluster and its multi-scale repre- sentation were established. According as the error propagation law, this paper deduced the assessment method of spatial analysis in dif- ferent scale for point cluster. Finally, the change rule of uncertainty for point cluster in the course of scale-extend and spatial analysis were gained. This study made up for the weakness of existing research, and it also provided theoretical foundation for the quality assess- ment of geographic point cluster data on multi-scale representation. Meanwhile, it would be the reference standards for quality control and spatial decisions.