基于微光数据的城市化水平测度研究

发布时间：2018-10-24 20:54

【摘要】：进入二十一世纪以来,中国城市化进程开始加速推进。遥感技术能够便捷、客观、连续地反映土地利用与覆盖情况,结合城镇用地行政单元统计数据,是当前估算城市化水平的有效手段。夜间灯光(Nighttime Light,NTL)遥感图像以其宏观、经济、可直观准确反映人类活动等诸多特点,成为大尺度城市化研究的一种新技术手段并受到广泛关注。本文以中国大陆地区为研究区域,采用DMSP/OLS夜间灯光数据为主要数据源,开展了基于生物物理指数的城市用地空间分布信息提取方法的研究,并根据提取结果,对2000-2012年中国大陆地区城市化水平时空变化进行了分析。论文的主要研究内容和结论如下:(1)确定了2000-2012年非辐射定标夜间灯光数据的相互校正参数,并对其进行了相互校正,使得多时序夜间灯光数据的DN值具有可比性。(2)NDVI很难有效区分不透水面和土壤,以其作为辅助信息结合夜间灯光数据提取城市用地信息存在一些弊端。针对这一情况,结合对城市下垫面有增强作用的生物物理指数(BCI),采用分区思想和SVM分类法,提出了基于夜间灯光数据和BCI指数的城市用地信息提取方法。并选取典型城市样本与基于NDVI的SVM分类法的提取结果进行精度评价和对比分析。经对比,基于BCI的SVM分类法的平均总体精度和Kappa系数分别达到0.9228和0.6780,均高于基于NDVI的SVM分类法的分类精度。(3)利用基于BCI的SVM分类法提取中国大陆城市用地信息,根据提取结果,选取中国大陆总体、八大经济区以及麦肯锡城市群中的六个典型城市群为研究对象,对2000-2012年12年期间中国城市化水平时空变化进行分析。结果表明:中国大陆城市化水平整体呈现东高西低、沿海高于内陆的格局;京津冀、杭州、呼和浩特城市群在此期间城市化进程整体较快,哈尔滨-长春、成都、南昌城市群则相对较慢。
[Abstract]:Since entering the 21 century, China's urbanization process began to accelerate. Remote sensing technology can reflect the situation of land use and land cover conveniently, objectively and continuously, combined with the statistical data of urban land administrative unit, which is an effective means to estimate the level of urbanization at present. Night lighting (Nighttime Light,NTL) remote sensing images have become a new technique in the study of large-scale urbanization because of their macroscopical, economical, intuitive and accurate reflection of human activities and so on. In this paper, the spatial distribution information extraction method of urban land based on biophysical index is studied by using DMSP/OLS night light data as the main data source in mainland China, and based on the results of extraction, the method of extracting urban land spatial distribution information based on biophysical index is presented. The temporal and spatial changes of urbanization level in mainland China from 2000 to 2012 were analyzed. The main research contents and conclusions are as follows: (1) the mutual correction parameters of non-radiometric night lighting data from 2000 to 2012 are determined and corrected. It is difficult for NDVI to distinguish impermeable surface from soil effectively. It is difficult to extract urban land information by using it as auxiliary information combined with nighttime lighting data. (2) it is difficult to distinguish impermeable surface from soil effectively by NDVI. In view of this situation, combined with the biophysical index (BCI), which can enhance the underlying surface of the city, a method of extracting urban land information based on night lighting data and BCI index is proposed by using the method of zoning and SVM classification. And select the typical city samples and SVM classification based on NDVI for accuracy evaluation and comparative analysis. By comparison, the average total precision and Kappa coefficient of SVM classification based on BCI are 0.9228 and 0.6780, respectively, which are higher than that of SVM classification based on NDVI. (3) using SVM classification based on BCI to extract urban land information in mainland China. In this paper, six typical urban agglomerations in China, eight economic zones and six typical urban agglomerations from 2000 to 2012 are selected to analyze the spatial and temporal changes of urbanization level in China during the 12 years from 2000 to 2012. The results show that the overall urbanization level in mainland China is lower in the east, higher in the west and higher in the coastal areas than in the inland, and the urbanization process of the Beijing-Tianjin-Hebei, Hangzhou and Hohhot urban agglomerations is relatively fast during this period, Harbin-Changchun, Chengdu, Harbin, Changchun, Chengdu, Nanchang urban agglomeration is relatively slow.
【学位授予单位】：中国石油大学(华东)
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F299.2;P237

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