高度城镇化背景下深圳市易涝点驱动因子分析

Analysis of driving factors for waterlogging points in Shenzhen City under high urbanization background

根据深圳市2018—2022年易涝点统计资料,运用标准差椭圆、空间自相关和核密度估计等方法对深圳市易涝点时空分布特征进行分析。将分别利用优化热点分析和核密度估计方法所得的内涝易发度作为因变量,运用参数最优地理探测器对连续型驱动因子最优离散化处理,探测易涝点空间分布差异的主要驱动因子及作用机制。结果表明:深圳市易涝点空间分布差异性显著,其分布的方向性减弱,集聚特征明显;人口经济类驱动因子对易涝点空间分布有最强解释力,气候特征类次之,暴雨日数和人口驱动因子的协同作用可以解释59.50%的易涝点分布;核密度估计所得的易发度具有更好的代表性,且对连续型因子最优离散化处理能显著提升其解释力。

Based on the statistical data of waterlogging points in Shenzhen City from 2018 to 2022,the spatiotemporal distribution characteristics of waterlogging points in Shenzhen City were analyzed using methods such as standard deviation ellipse,spatial autocorrelation,and kernel density estimation.Using the optimized hotspot analysis and kernel density estimation to obtain the susceptibility to waterlogging as the dependent variable,respectively,the optimal parameter geographic detector was used to discretize the continuous driving factors and explore the main driving factors and the mechanisms of spatial distribution differences in waterlogging points.The results show that there are significant differences in the spatial distribution of waterlogging points in Shenzhen City,with weakened directionality and obvious clustering characteristics.The population economic driving factors have the strongest explanatory power for the spatial distribution of waterlogging points,followed by the climate characteristics.The synergistic effect of rainstorm days and population driving factors can explain 59.50%of the distribution of waterlogging points.The susceptibility obtained from kernel density estimation has better representativeness,and the optimal discretization of continuous factors can significantly improve their explanatory power.