摘要
为了研究省域尺度上像素级GDP空间化的方法,基于NPP-VIIRS夜间灯光数据,首先去除孤立极亮像元和背景噪声,将夜间灯光总强度、线性加权灯光指数和综合灯光指数分别与河北省11地市内的各区县GDP进行相关性分析,得知夜间灯光总强度与地市内各区县GDP相关性最显著,根据每个地市中最高相关系数对应的回归模型计算每个像素对应的GDP,经过线性纠正后,生成河北省GDP密度图.结果表明,全省172个区县的平均GDP相对误差为0.10%.该方法精度较高,生成的GDP密度图可以反映河北省经济发展的现状.
To investigate an approach of provincial GDP spatialization at pixel level, using NPP-VIIRS night time light image as data source, isolated exceeding-bright pixels and background noises were firstly filtered. Then totai nighttime light （TNL）, linear weighted light index （L） and compounded night light index （CNLI） were respectively calculated and analyzed on correlation with all counties＇ GDP including in each prefecture-level city of Hebei province. TNL and all counties＇ GDP included in each prefecture-level city showed the strongest correlation in three light indexes. The optimum regression model corresponding to TNL in each prefecture-level city was used to calculate each pixel＇s GDP. Once these GDPs at pixel level were linearly calibrated, a Hebei province＇s GDP density map was generated based on these linearly corrected GDPs. The results showed that relative error of estimated average GDP＇s relative error was 0.10% among 172 counties of Hebei province. Additionally, this approach had higher precision and produced GDP density map could reflect the current economic development situation of Hebei province.
出处
《信阳师范学院学报（自然科学版）》
CAS
北大核心
2016年第1期152-156,共5页
Journal of Xinyang Normal University(Natural Science Edition)
基金
河北省高等学校科学研究计划重点项目(ZD2014203)
中央高校基本科研业务费资助项目(ZD2014203)
