青藏高原城镇化水平时空动态及影响因素基于长时间序列夜间灯光数据的分析

Spatial-temporal changes in urbanization level and influencing factors on the Tibetan Plateau: perspectives from long-term time series nighttime light data

  • 摘要: 基于长时间序列夜间灯光数据集构建复合灯光指数(compounded night light index,CNLI),量化了青藏高原1992—2018年城镇化水平动态变化.在省级行政区、地级行政区、县级行政区和流域等多个尺度上分析了青藏高原城镇化水平变化过程,揭示了青藏高原城镇化水平空间集聚特征以及不同时间段城镇化水平的影响因素.结果表明:青藏高原1992—2018年的总体城镇化水平呈加速增长趋势并且内部存在显著的空间差异,CNLI由1.03×10−4增长到4.46×10−3,大约增长了42倍;青藏高原高城镇化水平聚集区面积和数量均显著增大,在西宁周边、拉萨周边和区域的东南边缘形成了3大高城镇化水平聚集区;此外,青藏高原城镇化水平动态变化主要受到交通和地形的影响,交通要素的影响在不断加强.本研究基于长时间序列夜间灯光数据集的城镇化水平动态变化分析方法具有普适性,可用于其他统计资料不完善的地区的城镇化水平分析.

     

    Abstract: It is of great theoretical and practical significance to accurately quantify changes in urbanization on the Tibetan Plateau, to understand economic, social and ecological responses in the region.Due to imperfect social and economic statistical data of the Tibetan Plateau, relevant research has not been done on urbanization level dynamics.The recently released long-term nighttime light data provides an opportunity to study changes in urbanization level on the Tibetan Plateau.The dynamics of urbanization level on the Tibetan Plateau was quantified from such data from 1992-2018.Changes have been analyzed on multiple scales: provincial-level administrative regions, prefecture-level administrative regions, county-level administrative regions, as well as watersheds.Spatial agglomeration characteristics and influencing factors in different time periods were analyzed.The overall urbanization level on the Tibetan Plateau showed an accelerated growth trend from 1992-2018, significant spatial differences were found.From 1992-2018, CNLI increased from 1.03×10−4 to 4.46×10−3, with an average annual increase of 1.67×10−4.The area and number of high-level urbanization clusters increased significantly.Three areas with high level of urbanization have formed around Xining, Lhasa, and southeast edge of the region.The urbanization levels are mainly affected by traffic and topography, influence of traffic factors is constantly increasing.It is concluded that quantification of urbanization from long-term nighttime light data is effective and can be applied to other areas with imperfect statistical data.

     

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