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人口老龄化正成为制约东北振兴发展的突出问题。本文依照状态—过程—机制的研究范式，以东北地区为典型研究案例，采用空间关联分析、地理探测器等方法，基于省级、市级和县级三个尺度分析了2000～2010年东北地区人口老龄化的时空特征及影响因素，结果表明：①东北地区不同尺度老龄化系数均呈现逐年上升趋势，但各尺度省际差异明显，相对于吉林和黑龙江两省，辽宁省老龄化程度更为严重，一定程度上拉高了东北地区老龄化水平。②从空间分布看，市级尺度和县级尺度人口老龄化均呈现全面升级的态势，老龄化高值区又以辽宁省为主向全区扩散。③从空间关联看，全局自相关分析表明，市级和县级尺度人口老龄化存在显著的空间正相关，集聚特征明显，但集聚强度呈减弱态势；局部空间自相关分析表明，市级和县级尺度人口老龄化空间集聚均呈收缩趋势，显著性H-H集聚和L-L集聚数量明显减少，县级尺度表现得更加明显，H-H集聚区空间上发生了跳转。④从速度空间分异看，市级尺度上空间分布呈现显著的轴带分布特征，老龄化低速增长和较低速增长主要分布在哈大经济带上，较高速增长和高速增长主要分布在黑龙江北部沿边经济带上；县级尺度呈现由北向南增速递减的空间分布格局。⑤从宏观定性和微观定量两个角度，分析了不同尺度人口老龄化的影响因素。
<<Population aging is becoming a prominent problem that restricts the revitalization and development of Northeast China. In accordance with the state-process-mechanism research paradigm，taking Northeast China as a typical case study area，this research uses spatial association analysis and geo-probe methods to analyze the temporal and spatial characteristics of population aging and influencing factors of the Northeast China from 2000 to 2010 based on provincial，municipal，and county scales data. The results show that：Ⅰ The ageing coefficients at different scales in Northeast China tend to rise year by year，but there are significant differences among provinces at all scales. Compared with Jilin and Heilongjiang Provinces，the degree of aging of Liaoning Province is even higher，which has raised the level of aging in northeast China. Ⅱ From the perspective of spatial distribution，the population ageing at both the municipal scale and the county scale shows an overall upgrading trend. The highly aging areas spread mainly from Liaoning Province to the whole area；however，there are differences in the spatial distribution pattern of aging at different scales. The spatial distribution of highly aging areas at the county scale is more dispersed. Ⅲ From the perspective of spatial correlation，the global auto-correlation analysis shows that there is a significant spatial positive correlation between population aging at the municipal and county scales. In addition，the agglomeration characteristics are obvious while the agglomeration intensity is weakening. The local spatial auto-correlation analysis shows that the municipal and county scales aggregation of population aging has a contraction trend. To be more specific，significant HH agglomeration and LL agglomeration are obviously reduced，and there is a jump in the HH-type agglomeration area showing that the contraction at county level scale is more evident. Ⅳ From the dual perspectives of macro-characterization and micro-quantitative analysis，the influencing factors of population aging at different scales were analyzed.
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