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基于DMSP/OLS数据的全国空气污染物时空演变研究
引用本文:基于DMSP/OLS数据的全国空气污染物时空演变研究.基于DMSP/OLS数据的全国空气污染物时空演变研究[J].山东科学,2010,33(2):97-105.
作者姓名:基于DMSP/OLS数据的全国空气污染物时空演变研究
作者单位:南京工业大学 测绘科学与技术学院,江苏 南京 211800
基金项目:国家自然科学基金(41401185);江苏省研究生科研与实践创新计划(KYCX19_0848)
摘    要:基于美国国防气象卫星搭载传感器DMSP/OLS的夜间灯光遥感影像,从2000—2013年选取4年进行影像采集、影像校正等操作后,提取了灯光总量、灯光面积数据,根据年份间夜间灯光数据的增长量开展了全国各区域间的差异分析,结合空气污染物排放量进行了相关度分析。研究结果发现:(1)整体上全国夜间灯光量增幅变大,且增幅受相关年份政策影响。(2)夜间灯光总量与空气污染物排放量呈现正相关性,且两者相关系数较高;工业空气污染物与夜间灯光量相关性不断降低,同时生活空气污染物与夜间灯光量相关性不断提高。(3)夜间灯光总量与空气污染的高/高集聚区域一致性稳步提升。结合夜间灯光影像数据与空气污染数据,通过比较夜间灯光数据差异探讨空气污染物的时空演变,为我国空气污染的综合治理提供了一个新的视角。

关 键 词:卫星遥感影像  夜间灯光  空气污染  时空演变  
收稿时间:2019-10-14

Spatial-Temporal evolution of national air pollutants basedon DMSP/OLS data
WU Yun-qing,TAO Yu-ting,ZHANG Yun-peng,MA Jing.Spatial-Temporal evolution of national air pollutants basedon DMSP/OLS data[J].Shandong Science,2010,33(2):97-105.
Authors:WU Yun-qing  TAO Yu-ting  ZHANG Yun-peng  MA Jing
Institution:College of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211800, China
Abstract:Based on DMSP/OLS night-time light remote sensing imagery, the authors selected four years from the fourteen-year period of 2000 to 2013 to perform image acquisition and correction and extract data including the total amount of the light and the area of the light. Based on the annual growth of the light data, the differences among regions in the country were analyzed, and the correlation analysis was performed with regard to air pollutants. Experimental results show that:(1) As a whole, the amount of night-time light has increased nationwide, and the range of increase was affected by the policies of the relevant year. (2) There is a positive correlation between the total amount of night-time light and the air pollutants, and the correlation coefficient between the two is high. The correlation between industrial air pollutants and night light is decreasing, whereas the correlation between domestic air pollutants and night light is increasing. (3) The consistency between the total amount of night-time light and air pollution high/high concentration area has steadily enhanced. In this paper, we combine the night-time light imagery data and air pollution data to explore the temporal and spatial evolution of air pollutants through the comparison of the variations of night-time light data and provide a novel perspective for the comprehensive treatment of air pollution in China.
Keywords:remote sensing imagery  nighttime light  air pollution  spatial-temporal evolution  
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