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基于“珞珈一号”夜光遥感影像的郑州大都市区城市空间格局分析

Urban Spatial Pattern Analysis of Zhengzhou Metropolitan Area Based on“LJ1-01”Nighttime Light Remte Sensing Data W
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摘要 利用“珞珈一号”夜光遥感影像,得到郑州大都市区的夜间灯光分布图。在此基础上获取各个区域的夜间灯光总量指数(total nighttime light index,TNLI)和夜间平均灯光指数(average nighttime light index,ANLI),并分析其空间分布格局。研究表明:整体来看,郑州市TNLI和ANLI均为最高,超过其他4市总和;郑州大都市区内的城市重心位于郑州市中心东南方向,各地市的城市重心均位于各自主城区附近;郑州市的社会经济区位度在郑州大都市区内为最高,证明其在区域内独一无二的首位度,而其他城市与之差距较大。郑州大都市区的不均衡现象较为突出,区域内协同融合发展的程度还有待加强。 "LJ1-01"nighttime light remote sensing data were used to map the spatial distribution of socio-economic index in the Zhengzhou metropolitan area.The total nighttime light index(TNLI)and average nighttime light index(ANLI)were calculated by spatial statistics analysis in the whole and by individual.On the basis of comprehensive assess,it was concluded that Zhengzhou city possesses the highest TNLI and ANLI more than the other cities combined in the area,which means Zhengzhou city has the highest level of economic development among them.The nighttime light center of the metropolitan area is located around the southeast part of Zhengzhou city,and the light center of the individual city is lied near their main urban area.Meanwhile,Zhengzhou city has the supreme socio-economic location index,and the other cities are far from it.All of the above indicate that Zhengzhou city has incomparable advantages.All in all,the imbalance in this region is prominent,which should be promoted in the future.
作者 王戈飞 职露 邓荣鑫 WANG Gefei;ZHI Lu;DENG Rongxin(Yellow River Engineering Consulting Co.,Ltd.,Zhengzhou 450003,China;School of Geography and Tourism,Zhengzhou Normal University,Zhengzhou 450044,China;School of Data and Target Engineering,Information Engineering University,Zhengzhou 450000,China;College of Surveying and Geo‐informatics,North China University of Water Resources and Electric Power,Zhengzhou 450046,China)
出处 《测绘地理信息》 CSCD 2023年第4期35-40,共6页 Journal of Geomatics
基金 国家自然科学基金(31971723)。
关键词 郑州大都市区 “珞珈一号” 夜光遥感影像 城市空间格局 引力模型 Zhengzhou metropolitan area "LJ1-01" nighttime light remote sensing data urban spatial pattern gravity model
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