地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (11): 1522-1529.doi: 10.3724/SP.J.1047.2017.01522

• 遥感科学与应用技术 • 上一篇    下一篇

城市建成区多源遥感协同提取方法研究

李治1,2,3(), 杨晓梅2,*(), 孟樊2, 陈曦1, 杨丰硕2,3   

  1. 1. 中国科学院新疆生态与地理研究所 荒漠与绿洲生态国家重点实验室,乌鲁木齐 830011
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    3. 中国科学院大学,北京 100049
  • 收稿日期:2017-04-30 修回日期:2017-08-25 出版日期:2017-11-10 发布日期:2017-12-08
  • 通讯作者: 杨晓梅 E-mail:lizhi@lreis.ac.cn;yangxm@lreis.ac.cn
  • 作者简介:

    作者简介:李 治(1986-),男,博士生,研究方向为多源遥感信息协同提取、城市景观生态分析。E-mail: lizhi@lreis.ac.cn

  • 基金资助:
    国家重点研发计划项目(2016YFB0501404);国家自然科学基金项目(41671436、41421001)

The Method of Multi-source Remote Sensing Synergy Extraction in Urban Built-up Area

Li Zhi1,2,3(), Yang Xiaomei2,*(), Meng Fan2, Chen Xi1, Yang Fengshuo2,3   

  1. 1. State Key Laboratory of Desert and Oasis Ecology , Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences,Urumqi, Xinjiang 830011, China
    2. State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101, China
    3.University of Chinese Academy of Sciences,Beijing 100049, China
  • Received:2017-04-30 Revised:2017-08-25 Online:2017-11-10 Published:2017-12-08
  • Contact: Yang Xiaomei E-mail:lizhi@lreis.ac.cn;yangxm@lreis.ac.cn

摘要:

城市建成区边界是城市研究重要的基础信息,也是落实城市功能空间布局、实施界限管控的前提。DMSP/OLS夜间灯光数据已被广泛应用于城市建成区的提取,但由于受饱和、扩散及低分辨率问题的影响,导致仅依靠DMSP/OLS NTL映射城市建成区仍然是一个巨大的挑战。本文以京津冀为例,采用MODIS NDVI和DMSP / OLS夜光数据相结合解决NTL影像的饱和及扩散问题,提取城市建成区潜在范围,并辅以Landsat NDVI数据,采用本文提出的最大自相关双阈值方法进行自适应修正,最后采用目视解译对结果进行验证。实验结果表明,多源遥感协同方法提取城市建成区的总体精度和kappa系数分别为92.9%和0.88,在空间分布和统计数据中均有较高的有效性和可靠性。

关键词: DMSP/OLS夜光数据, 城市建成区, 多源遥感数据, 最大自相关双阈值法, 京津冀区域

Abstract:

The urban built-up area boundary is important basic information for urban studies, and is also the premise of the implementation of urban function space layout, the implementation of boundaries control. Accurate extract urban built-up area for urban construction, management and research has important guiding significance, but also reflects the city's comprehensive economic strength and the level of urbanization, one of the important indicators.The DMSP/OLS night light data has been widely used in the extraction of urban built-up areas. But due to the effects of saturated, diffuse, and low resolution problems, it is still a huge challenge to rely on the DMSP/OLS NTL mapping the urban built-up areas. In order to overcome the limitations of the data source itself, In this study, the application of hierarchical expert knowledge analysis, multi-source data extraction of the thematic information layer by layer into the extraction process, the construction of urban built-up area for the level of expert knowledge model to achieve the city built-area refinement extraction. The urban index (VANUI) was constructed by combining 250 m MODIS NDVI data with 1 km DMSP/OLS data. Based on the administrative boundary, the statistical area of the area is divided into the administrative boundary of each prefecture-level city, and the optimal segmentation threshold of each administrative unit VANUI feature image is calculated according to the regional segmentation method, so as to obtain 250 m urban boundary space information range. Meanwhile, Due to the low spatial resolution of the DMSP/OLS luminous data and the narrow range of light and light values, there is still a large gap between the optimal segmentation threshold and the built-up area. Therefore, this study proposed the maximum autocorrelation double threshold extraction method. The 30m Landsat 5 NDVI data were fused to obtain the maximum autocorrelation quadratic NDVI threshold in each 30m seed region by multi-scale segmentation of the regional threshold segmentation. According to the maximum autocorrelation threshold of each potential built-up area, each potential built-up area is revised one by one, and finally 30m urban built-up area is obtained. This paper takes the Beijing-Tianjin-Hebei region as the research area, the experimental results show that the total precision of extracting urban built-up area by multi-source remote sensing cooperative method is 92.9%, and it has higher validity and reliability in spatial distribution and statistical data. The results show that the results of the urban built-up area extracted by this method are not only the overall accuracy, but also the spatial extent of the visual interpretation, and the relative error of the statistical area in each prefecture-level city is small, which verifies the reliability and validity of the method in spatial distribution and statistical data, and avoids the error caused by subjective threshold selection. DMSP/OLS data can be used not only for urban area extraction, but also for the intensity and scope of human activities. Therefore, in the follow-up study, based on the identification of urban built-up area boundary, combined with the quantitative analysis of luminous data and evaluation of urban development area outside the expansion trend and internal dynamic changes for the DMSP/OLS luminous data to give full play to its effectiveness, Economic and historical values play a positive role in promoting.

Key words: DMSP/OLS, urban built-up area, multi-source remote sensing data, the biggest autocorrelation double threshold value method, Beijing-Tianjin-Hebei Region