海上丝绸之路超大城市空间扩展遥感监测与分析

发布时间：2018-01-20 08:39

本文关键词： 海上丝绸之路超大城市面向对象的SVM 不透水层景观格局城市化　出处：《遥感学报》2017年02期 　论文类型：期刊论文

【摘要】：以海上丝绸之路沿线的11个超大城市为例,基于长时间序列的Landsat MSS/TM/ETM+/OLI和HJ-1卫星CCD数据,利用基于面向对象的支持向量机SVM(Support Vector Machine)分类方法提取20世纪70年代到2015年的城市不透水层,并结合景观格局指数—最大斑块指数LPI(Largest Patch Index)、斑块密度PD(Patch Density)和欧几里得最邻近距离ENN(Euclidean Nearest Neighbor Distance)分析了超大城市的发展模式。研究结果表明:基于面向对象的SVM分类方法能够高效提取城市不透水层;平均总精度高于87.9%,平均Kappa系数高于0.87;过去40余年,各超大城市的面积扩张了4—13倍,中国和印度的超大城市扩张最快,广州、上海超过12倍;各城市以"中心—边缘"或"沿海—内陆"的方向扩张,表现为"扩散—聚集—再扩散"的扩张模式;总体来看,沿线的城市化进程仍处于上升期。本研究为建设"21世纪海上丝绸之路"提供了科学依据,对当地生态环境保护和新型城镇化建设具有重要意义。
[Abstract]:Taking 11 mega-cities along the maritime Silk Road as an example, Landsat MSS/TM/ETM / OLI and HJ-1 satellite CCD data are based on a long time series. An object-oriented support vector machine (SVM(Support Vector Machine) classification method is used to extract the impermeable layer from 1970s to 2015. Combined with landscape pattern index-the largest patch index LPI(Largest Patch index. Patch density (PD(Patch density) and Euclidean nearest distance (ENN). Euclidean Nearest Neighbor distance. The development pattern of mega-cities is analyzed. The results show that the object-oriented SVM classification method can extract the impermeable layer efficiently. The average total precision is higher than 87.9, and the average Kappa coefficient is higher than 0.87. Over the past 40 years, the size of each megacities has expanded 4-13 times, China and India's megacities expand fastest, Guangzhou, Shanghai more than 12 times; Each city expands in the direction of "center-edge" or "coastal-inland", which is the expansion mode of "diffusion-agglomeration-rediffusion"; Overall, the process of urbanization along the route is still on the rise. This study provides a scientific basis for the construction of the "Maritime Silk Road of 21th century", and is of great significance to the protection of the local ecological environment and the construction of new urbanization.
【作者单位】：山东科技大学测绘学院;中国科学院遥感与数字地球研究所数字地球重点实验室;海南省地球观测重点实验室;湖南师范大学资源与环境科学学院;
【基金】：国家自然科学基金(编号:41201357) 中国科学院遥感与数字地球研究所“一三五规划项目”(编号:Y4SG0500CX);中国科学院国际合作局对外合作重点项目(编号:131C11KYSB20160061) 国家重点研发计划“全球变化及应对”重点专项课题(编号:2016YFA0600302)~~
【分类号】：TU984.113;TP79
【正文快照】： 引用格式:禹丝思,孙中昶,郭华东,赵相伟,孙林,吴孟凡.2017.海上丝绸之路超大城市空间扩展遥感监测与分析.遥感学报,21(2):169 181Yu S S,Sun Z C,Guo H D,Zhao X W,Sun L and Wu M F.2017.Monitoring and analyzing the spatial dynamicsand patterns of megacities along th

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