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基于NPP-VIIRS数据的山东省县级GDP分级空间建模
引用本文:刘沼辉,柳林,邹健.基于NPP-VIIRS数据的山东省县级GDP分级空间建模[J].测绘通报,2019,0(1):114-117,122.
作者姓名:刘沼辉  柳林  邹健
作者单位:山东科技大学测绘科学与工程学院,山东 青岛,266590;山东科技大学测绘科学与工程学院,山东 青岛,266590;山东科技大学测绘科学与工程学院,山东 青岛,266590
基金项目:山东省自然科学基金(ZR2012FM015);青岛经济技术开发区重点科技项目(2013-1-27)
摘    要:传统的统计方法对国内生成总值(GDP)进行统计耗时耗力费财。而夜间灯光遥感影像能对人类社会活动进行最直观的反映,为社会经济研究提供了新的思路方法和技术支持。本文以山东省作为研究区域,采用NPP-VIIRS灯光影像数据与山东省137个县级GDP数据进行分级多方式空间建模,以找到两者空间分布的最优规律。试验结果表明总GDP与总灯光亮度值的各级最优拟合优度R2均在0.9左右。单位面积GDP与平均灯光亮度值的各级拟合优度R2均在0.85左右。而且通过最优模型进行县级和市级GDP预测精度优于未分级的预测精度。

关 键 词:NPP-VIIRS  夜间灯光影像  县级GDP  空间关系模型  GDP预测分析
收稿时间:2018-06-19
修稿时间:2018-08-13

Hierarchical spatial modeling of county GDP in Shandong province based on NPP-VIIRS data
LIU Zhaohui,LIU Lin,ZOU Jian.Hierarchical spatial modeling of county GDP in Shandong province based on NPP-VIIRS data[J].Bulletin of Surveying and Mapping,2019,0(1):114-117,122.
Authors:LIU Zhaohui  LIU Lin  ZOU Jian
Institution:Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China
Abstract:Because of the traditional statistical methods, the time consuming and energy consuming spending on statistical the gross domestic product (GDP) is large. The night lighting remote sensing images can react directly to human social activities and provide a new way of thinking and technical support for the study of social economy. This paper takes Shandong Province as the research area, uses the NPP-VIIRS light image data and the GDP data of 137 counties in Shandong Province to establish many kinds of spatial relation models in order to find the optimal law of the spatial distribution of the two places. The experimental results show that the total GDP and the brightness of the total lighting are all about 0.9 at all levels of the goodness of fit R2. The unit area GDP and the average lamplight brightness value are all about 0.85 at all levels of the goodness of fit R2.The prediction accuracy of GDP at county level and city level by the optimal model is better than that of the unclassified one.
Keywords:NPP-VIIRS  nighttime light image  county GDP  spatial correlation model  GDP prediction analysis  
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