摘要
产业结构作为经济增长的基础和结果,是经济发展水平的集中体现.为估测产业结构,基于NPP-VIIRS夜间灯光数据,以河南省18个省辖市为研究对象,首先进行影像处理,将各市的夜间灯光总强度与其第一产业、第二产业、第三产业产值进行相关性分析,得知二、三产业与夜间灯光总强度相关性显著,得到二、三产业的估测模型.针对第一产业与夜间灯光总强度相关性弱的问题,提出以亮度值小于0.7与DEM数据划分的坡度等级相结合来提取耕地区域,构建第一产业产值估测模型,进而实现产业结构的建模.最后结合各年度经济数据对估测模型进行验证,表明估测模型具有较好的精度,所提方法和研究结果可以为估算产业结构、优化产业布局、促进经济转型等提供决策支撑.
In order to estimate the industrial structure,based on NPP-VIIRS nighttime light data,18cities in Henan Province were taken as the research objects.First,image processing was carried out,and the regression analysis was made between the total nighttime light intensity of each city and the added value of the primary,secondary and tertiary industries.It is found that the secondary and tertiary industries are significantly correlated with the total nighttime light intensity.The estimation models of secondary and tertiary industries are obtained.In view of the weak correlation between the primary industry and the total intensity of night light,this paper proposes to identify the cultivated land area by combining the brightness value less than 0.7with the slope grade divided by DEM data,and constructs the estimation model of the added value of the primary industry to realize the modeling of the industrial structure.Finally,the estimation model is verified with annual economic data,which shows that it has a good accuracy at provincial and municipal scale,and completes the spatial expression of industrial structure.The proposed method and research results can provide decision support for estimating industrial structure,optimizing industrial layout and promoting economic transformation.
作者
唐小辉
蔡中祥
刘宏建
樊新刚
TANG Xiaohui;CAI Zhongxiang;LIU Hongjian;FAN Xingang(School of Geospatial Information,Information Engineering University,Zhengzhou 450001,China;School of Economics and Management,Ningxia University,Yinchuan 750021,China)
出处
《河南大学学报(自然科学版)》
CAS
2023年第3期305-313,共9页
Journal of Henan University:Natural Science
基金
国家自然科学基金资助项目(42161050)
国家社会科学基金重大项目(20&ZD143)
关键词
夜间灯光
GDP
产业结构
回归分析
估测
nighttime light data
GDP
industrial structure
regression analysis
estima