摘要
目前包括GDP在内的社会经济数据大多以行政区划为统计单元,普遍存在统计单元内的数据均一化以及与其他环境数据空间不匹配等问题。以中国海岸带地区为例,利用DMSP/OLS夜间灯光数据和植被指数构建的人居指数与非农业GDP之间的线性关系建模,对非农业GDP进行了空间化模拟,基于土地利用数据建立了农业GDP空间化模型,最终得到2010年中国海岸带地区250 m×250 m空间分辨率的GDP密度图。结果显示:相比仅利用夜间灯光数据模拟非农业GDP,人居指数模型较好地改善了夜间灯光数据的像元溢出效应以及过饱和问题,提高了对非农业GDP的模拟精度。栅格尺度上的中国海岸带GDP密度图可以为沿海地区灾害风险评估、社会经济决策、区域规划和可持续发展研究提供基础数据支持。
Gross Domestic Product（ GDP）, which provides the characteristics of social and economic development,is the most widely used socioeconomic indicator for the politic agency to develop strategies and assess disaster risks. However, there often exists a spatial mismatch between socio-economic data（ at administrative unit level） and environmental data（ at pixel level）. In this paper,a Human Settlement Index（ HSI） was developed by combining the Defense Meteorological Satellite Program Operational Linescan System（ DMSP/OLS） nighttime light imagery data and enhanced vegetation index（ EVI） data. The input of EVI can effectively decrease the information loss of population distribution caused by the saturation effect of nighttime light imagery. A threshold method（ Digital Number 9） was used to remove the potential nighttime light blooming areas to reduce the error caused by the overglow effect of DMSP/OLS nighttime light imagery and classify the different types of GDP. The land use and land cover data was used to map the agricultural GDP,and the non-agricultural GDP was mapped based on the linear relationship between the cumulative HSI and the GDP of secondary and tertiary industries（ R-2= 0. 823）. Then the GDP density across the coastal area of China in 2010 was mapped at a spatial resolution of 250 m. The results showed that the application of HSI can improve the accuracy in simulating the GDP of secondary and tertiary industries than the single nighttime light model,and the highest GDP density mainly located in the regions with a high urbanization level,especially in the Yangtze River Delta and the Pearl River Delta. The method developed by this paper to map GDP at pixel level can compare the GDP value within and between the study units. This method can provide an effective application in developing economic strategies,regional planning,and natural disaster risk assessment,etc.
出处
《长江流域资源与环境》
CAS
CSSCI
CSCD
北大核心
2018年第2期235-242,共8页
Resources and Environment in the Yangtze Basin
基金
国家自然科学基金面上项目(41371068)
