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基于多源时空信息的西宁和拉萨近70年来城市扩展过程重现及地表覆盖变化分析
引用本文:郭长庆,张学霞,侯亚丽,匡文慧.基于多源时空信息的西宁和拉萨近70年来城市扩展过程重现及地表覆盖变化分析[J].遥感技术与应用,2022,37(2):342-353.
作者姓名:郭长庆  张学霞  侯亚丽  匡文慧
作者单位:1.北京林业大学水土保持学院 水土保持国家林业局重点实验室,北京 100083;2.中国科学院地理科学与资源研究所 陆地表层格局与模拟重点实验室,北京 100101;3.中国科学院大学,北京 100049
基金项目:第二次青藏高原综合科学考察研究项目(2019QZKK0608)
摘    要:西宁和拉萨城市作为青藏高原人类活动的热点地区,其发展历程对青藏高原社会经济发展具有重要影响。研究基于遥感影像、城市规划图和历史地图等资料重建了西宁和拉萨城市1949基准年、1978基准年、1990年、2000年、2010年和2018年城市扩展及2000年以来城市不透水层和绿地空间组分数据,分析了1949基准年以来西宁和拉萨主城区城市扩展的时空特征,揭示了社会经济因素和政策因素对城市土地利用/覆盖变化的影响。研究结果表明:①新中国成立以来,西宁和拉萨主城区持续扩展,均呈现非线性的增长态势,城市土地面积分别从1949基准年的1.98 km2和1.10 km2增长到2018年的79.26 km2和77.04 km2;西宁主城区城市扩展呈现十字状的扩展态势,拉萨呈现出圈层外延式的扩展模式;②自2000年来,西宁和拉萨城市绿化水平显著提升。2000~2018年,西宁和拉萨城市不透水层面积分别从36.91 km2和21.56 km2增加到55.34 km2和48.21 km2,城市绿地空间面积分别从10.78 km2和8.48 km2增加到19.21 km2和20.35 km2,年均扩展速度分别为0.47 km2/a和0.66 km2/a;主城区城市不透水层比例分别从74.09%和66.21%下降到69.82%和62.58%,城市绿地空间比例从21.64%和26.05%上升到24.24%和26.41%;③西宁和拉萨城市人口增长、经济发展和国家相关政策与主城区城市扩展及其土地利用/覆盖变化密切相关,主城区城市扩展阶段与人口增长、经济发展阶段以及国家相关政策实施时间接近吻合。主城区土地利用/覆盖变化与城市规划相关政策高度相关,尤其是园林绿化建设,显著增加了城市绿地空间面积,城市绿地空间面积比例较2000年显著提升。

关 键 词:城市扩展  城市土地利用/覆盖变化  不透水层  遥感监测  
收稿时间:2020-11-09

Reconstructing Urban Expansion and Analyzing Land Cover Change of Xining and Lhasa in the Past 70 Years based on Multi-source Spatiotemporal Information
Changqing Guo,Xuexia Zhang,Yali Hou,Wenhui Kuang.Reconstructing Urban Expansion and Analyzing Land Cover Change of Xining and Lhasa in the Past 70 Years based on Multi-source Spatiotemporal Information[J].Remote Sensing Technology and Application,2022,37(2):342-353.
Authors:Changqing Guo  Xuexia Zhang  Yali Hou  Wenhui Kuang
Abstract:The cities of Xining and Lhasa are hot spots of human activities on the Qinghai-Tibet Plateau, and their development process has an important impact on the socio-economic development of the Qinghai-Tibet Plateau. This paper reconstructed urban expansion in Xining and Lhasa cities based on remote sensing images, urban planning maps and historical maps in circa 1949, circa 1978, 1990, 2000, 2010 and 2018, and urban impervious surface and green space component information since 2000. We analyzed the temporal and spatial characteristics of urban expansion in built-up area of Xining and Lhasa since circa 1949, and revealed the characteristics of the impact of socioeconomic factors and policy factors on urban land use/cover changes. The results show that: (1) Since the founding of the People's Republic of China, built-up area of Xining and Lhasa has continued to expand, showing a non-linear growth trend. The urban land area has increased from 1.98 km2 and 1.10 km2 in circa 1949 to 79.26 km2 and 77.04 km2 in 2018. The urban expansion of Xining’s built-up area presents a cross-shaped expansion trend, and Lhasa presents a circle-extensive expansion mode; (2) Since 2000, the urban greening level of Xining and Lhasa has improved significantly. From 2000 to 2018, the urban impervious surface area of Xining and Lhasa increased from 36.91 km2 and 21.56 km2 to 55.34 km2 and 48.21 km2, and the urban green space area increased from 10.78 km2 and 8.48 km2 to 19.21 km2 and 20.35 km2, and the average annual expansion rates were 0.47 km2/a and 0.66 km2/a. The percentage of impervious surface in the built-up area has dropped from 74.09% and 66.21% to 69.82% and 62.58%, and the proportion of urban green space has increased from 21.64% and 26.05% to 24.24% and 26.41%; (3) Xining and Lhasa's urban population growth, economic development and relevant national policies are closely related with the urban expansion of the main urban area and its land use/cover changes. The urban expansion stage of the built-up area is related with the population growth, economic development stage and the implementation time of relevant national policies. Land use/cover change in built-up area is highly related with urban planning-related policies, especially landscaping construction, which has significantly increased the area of urban green space, and the proportion of urban green space has increased significantly compared with 2000.
Keywords:Urban expansion  Urban land use/cover change  Impervious surface  Remote sensing monitoring  
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