动态数据空间分析的不确定性问题——以城市中心识别为例

Uncertainty in Spatial Analysis of Dynamic Data ——Identifying City Center

动态数据在空间分析中存在不确定性问题。以手机定位数据为例来识别城市中心,探索可塑性面积单元问题和不确定的地理情境问题,发现群体活动强度的空间自相关程度受到采样区域划分方式和分析单元大小的影响,地理情境的时空动态变化也会带来不确定的地理情境问题。讨论了减轻不确定性的可能方法。

The spatial analysis of dynamic data faces uncertainty problems. This paper utilizes mobile phone positioning data as the example to identify the city center, and to explore the modifiable areal unit problem and the uncertain geographic context problem. We find that the spatial autocorrelation of activity density distribution is influenced by the zoning scheme and areal unit scale, while complex spatial and temporal dynamics also generate uncertainty. We also discusse possible means to mitigate the uncertainty problems.