基于夜晚灯光数据探究华北地区时空分布
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摘要
随着科学技术发展和人民生活水平的不断提升,华北地区在时空上发生了一定的变化。本次研究旨在以华北地区为研究对象,将DMSP/OLS夜间灯光数据引入到华北地区时空分布变化问题的研究中。利用ENVI软件,通过对2014-2018年华北地区的空间变化和经济变化进行分析,得到一定价值的结论,为政府决策和未来华北地区发展提供一定的依据。分析结果表明,华北地区在一定程度上贫富差异明显,内蒙古地区西北与京津冀地区存在很大程度上的经济差异,并且,在城镇变化上也存在一定的劣势。而北京和天津地区以明显的地理和政治优势,无论是GDP还是城镇变化方面都远远高于河北、山西和内蒙古地区。通过灯光数据可以看出,京津冀地区经济呈现快速的趋势,而内蒙古和山西部分地区则长势较慢。
With the development of science and technology and the continuous improvement of people's living standards, the North China region has undergone certain changes in time and space. This study aims to introduce DMSP/OLS nighttime lighting data into the study of temporal and spatial distribution changes in North China. Using ENVI software, through the analysis of spatial changes and economic changes in North China in 2014-2018, the conclusions of certain value are obtained, which provides a certain basis for government decision-making and the future development of North China. The analysis results show that there is a significant difference between the rich and the poor in the North China region. There are large economic differences between the northwestern part of Inner Mongolia and the Beijing-Tianjin-Hebei region, and there are certain disadvantages in urban changes. The Beijing and Tianjin regions are far superior to Hebei, Shanxi and Inner Mongolia in terms of GDP and urban changes due to their obvious geographical and political advantages. It can be seen from the light data that the economy of Beijing-Tianjin-Hebei region has a rapid trend, while parts of Inner Mongolia and Shanxi are growing slowly.
With the development of science and technology and the continuous improvement of people's living standards, the North China region has undergone certain changes in time and space. This study aims to introduce DMSP/OLS nighttime lighting data into the study of temporal and spatial distribution changes in North China. Using ENVI software, through the analysis of spatial changes and economic changes in North China in 2014-2018, the conclusions of certain value are obtained, which provides a certain basis for government decision-making and the future development of North China. The analysis results show that there is a significant difference between the rich and the poor in the North China region. There are large economic differences between the northwestern part of Inner Mongolia and the Beijing-Tianjin-Hebei region, and there are certain disadvantages in urban changes. The Beijing and Tianjin regions are far superior to Hebei, Shanxi and Inner Mongolia in terms of GDP and urban changes due to their obvious geographical and political advantages. It can be seen from the light data that the economy of Beijing-Tianjin-Hebei region has a rapid trend, while parts of Inner Mongolia and Shanxi are growing slowly.
引文
[1]李峰,米晓楠,王粉鸽,等.基于DMSP-OLS和Landsat8数据的省域GDP空间化方法--以北京市为例[J].重庆师范大学学报(自然科学版),2016,33(01):138-142.
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[4]山西统计局.2015-2018.山西统计年鉴2014-2018[M].北京:中国统计出版社.
[5]北京统计局.2015-2018.北京统计年鉴2014-2018[M].北京:中国统计出版社.
[6]天津统计局.2015-2018.天津统计年鉴2014-2018[M].北京:中国统计出版社.
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[8]梁友嘉,徐中民.基于夜间灯光辐射数据的张掖市甘州区GDP空间分布建模[J].冰川冻土,2013,35(1):249-254.
[9]钟洋,胡碧松.夜间灯光数据的长江中游城市群空间格局演变[J].测绘科学,2018,43(09):68-75.
[2]河北统计局.2015-2018.河北统计年鉴2014-2018[M].北京:中国统计出版社.
[3]内蒙古统计局.2015-2018.内蒙古统计年鉴2014-2018[M].北京:中国统计出版社.
[4]山西统计局.2015-2018.山西统计年鉴2014-2018[M].北京:中国统计出版社.
[5]北京统计局.2015-2018.北京统计年鉴2014-2018[M].北京:中国统计出版社.
[6]天津统计局.2015-2018.天津统计年鉴2014-2018[M].北京:中国统计出版社.
[7]易玲,熊利亚,杨小唤.基于GIS技术的GDP空间化处理方法[J].甘肃科学学报,2006,18(2):54-58.
[8]梁友嘉,徐中民.基于夜间灯光辐射数据的张掖市甘州区GDP空间分布建模[J].冰川冻土,2013,35(1):249-254.
[9]钟洋,胡碧松.夜间灯光数据的长江中游城市群空间格局演变[J].测绘科学,2018,43(09):68-75.