Assessment on uncertainty of multi-scale representation of point cluster

In this paper, it firstly establishes the assessment contents on uncertainty of multi-scale representation of point cluster around the process of multi-scale representation of point cluster and its spatial analysis, which includes positional uncertainty and uncertainty of spatial analysis conclusions; the assessment index K and the quantitative model of positional uncertainty related to point cluster and its multi-scale representation are established afterwards, and methods for assessing uncertainty on spatial analysis conclusions of point cluster in different scales have been derived according to error propagation law; in the last part of the paper, the changing law of positional uncertainty and uncertainty of spatial analysis conclusions in the up-scaling of point cluster is concluded, which makes up the weakness that the existing quality assessment methods of point object generalization don´t consider the uncertainty of point cluster itself and its spatial analysis conclusions. And it provides not only theoretical foundation for quality assessment of multi-scale representation on geographic point cluster data, but also reference standards for its quality control and spatial decisions.