基于POI大数据与土地利用数据协同的小尺度区域GDP空间化方法

Using the Combination of POI Big Data and Land Use Data to Spatialize GDP in Small Scale Regions

针对小尺度区域难以准确获取空间完整、时间连续的经济格网数据问题。以广西南宁市为例,第一产值基于土地利用数据采用面积权重法建模;第二、三产值基于热点(point of interest,POI)数据空间关系权重建模;最后构建2019年南宁市1 km×1 km的GDP空间化密度图。研究结果表明:(1)城市POI数据与第二、三产值有较强的空间关系,R;在0.80以上;(2)将模拟值与统计值对比分析,模拟的经济统计数据精度较高,第一产值模拟精度R;为0.87;第二、三产值模拟精度R;为0.94;总产值模拟精度R;为0.92。研究结果揭示了区域内部经济变化规律,为小尺度区域经济格网化方法研究拓展新的思路。

It is difficult for small-scale regions to accurately obtain economic grid data with spatial integrity and continuous time.The area weight method is used to model the output value of first industry of Nanning based on the land use data;the output value of second and third industries are modeled based on POI hotspot data spatial relationship weights;finally,a spatial density map of 1 km×1 km GDP of Nanning in 2019 is constructed.The research results show that:1)The urban hotspot POI has a strong spatial relationship with the second and third industry output values,and R;basically reaches above0.80;The simulation accuracy R;of the first industry production value is 0.87;the simulation accuracy R;of the second and third industry production values is 0.94;the simulation accuracy R;of the total production value is 0.92.The results show the law of regional internal economic changes,and expands new ideas for the study of small-scale regional economic gridding methods.