地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (7): 1074-1085.doi: 10.12082/dqxxkx.2019.180600

• 遥感科学与应用技术 • 上一篇    下一篇

基于DMSP/OLS夜间灯光影像的中国东部沿海地区城市扩展动态监测

林中立1,2(), 徐涵秋2,3,*(), 黄绍霖4   

  1. 1. 福建工程学院 建筑与城乡规划学院,福州 350118
    2. 福州大学环境与资源学院,福州大学遥感信息工程研究所,福州 350116
    3. 福建省水土流失遥感监测评估与灾害防治重点实验室,福州 350116
    4. 深圳市铁汉生态环境股份有限公司,深圳 518040
  • 收稿日期:2018-11-23 修回日期:2019-03-05 出版日期:2019-07-25 发布日期:2019-07-25
  • 作者简介:

    作者简介:林中立(1989-),男,福建福州人,博士,讲师,主要从事环境与生态遥感研究。E-mail: linzl@fjut.edu.cn

  • 基金资助:
    国家重点研发计划专项课题(2016YFA0600302);国家自然科学基金项目(41501469);福建工程学院科研启动基金(GY-Z18164)

Monitoring of the Urban Expansion Dynamics in China's East Coast Using DMSP/OLS Nighttime Light Imagery

Zhongli LIN1,2(), Hanqiu XU2,3,*(), Shaolin HUANG4   

  1. 1. College of Architecture and Urban Planning, Fujian University of Technology, Fuzhou 350118, China
    2. College of Environment and Resources, Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350116, China
    3. Fujian Provincial Key Laboratory of Remote Sensing Soil Erosion and Disaster Protection, Fuzhou University, Fuzhou 350116, China
    4. Shenzhen Techand Ecology & Environment Company Limited, Shenzhen 518040, China
  • Received:2018-11-23 Revised:2019-03-05 Online:2019-07-25 Published:2019-07-25
  • Contact: Hanqiu XU
  • Supported by:
    National Key Research and Development Project of China, No.2016YFA0600302;National Natural Science Foundation of China, No.41501469;Scientific Research Foundation of Fujian University of Technology, No.GY-Z18164

摘要:

美国国防气象卫星搭载的业务性线性传感器(DMSP/OLS)所获取的夜间灯光影像数据,能够客观地反映人类对城市建成区的开发建设范围与强度,已广泛地应用于城市扩展的动态监测。本文利用不变目标区域法对长时间序列DMSP/OLS夜间灯光影像进行辐射校正,基于校正后的影像对2001-2013年中国东部沿海地区的城市建成区范围进行提取,结果表明:① 建成区面积从2001年的7550 km2,增加到2013年的21 650 km2,共扩展了14 100 km2,虽然建成区面积呈逐年增加的趋势,但其扩展速率则在逐步减缓,城市重心逐渐向南转移;② 在空间上形成了京津唐、长江三角洲和珠江三角洲3城市群,研究发现京津唐的中小城市面临难以获得发展资源的问题,导致了该地区发展的不平衡;③ 综合分析建成区扩展和经济统计数据,结果表明人口和经济是建成区扩展的主要驱动因子,但同时城市快速扩展也给东部沿海地区带来了一定程度的用地浪费问题;④ 由于DMSP/OLS夜间灯光影像受到自身空间分辨率的限制和灯光过饱和的影响,易造成城市建成区边缘细节部分的错提。新一代Suomi NPP/VIIRS夜间灯光影像在空间和光谱分辨率上均有较大提高,在后续的研究中应充分挖掘其数据优势,以期提供更加精准的城市扩展动态监测。

关键词: 中国东部沿海, DMSP/OLS, 夜间灯光影像, 城市扩展, 遥感

Abstract:

The Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) nighttime light (NTL) imagery can objectively reflect the impacts of human activities on the scope and intensity of urban built-up areas. Therefore, the DMSP/OLS imagery have been widely used in monitoring urban expansion dynamics. In this paper, the invariant region method was used to calibrate the DMSP/OLS time series NTL imagery. Then, we used the calibrated DMSP/OLS imagery to extract the urban built-up areas in China's east coast from 2001 to 2013. The result shows that the built-up areas in China's east coast increased from 7550 km2 in 2001 to 21 650 km2 in 2013, with a net increase of 14 100 km2. Although the built-up areas have increased year by year, the increase rate has slowed down. The gravity center of the built-up areas has gradually moved south. The Beijing-Tianjin-Tangshan area, the Yangtze River Delta, and the Pearl River Delta are the three major urban agglomerations in the east coast. The Beijing-Tianjin-Tangshan area was unbalanced in regional development, where the small and medium sized cities faced shortage of development resources. The relationship between urban expansion and economic growth was explored. We conclude that population and economy are the two main driving factors for the expansion of urban built-up areas in China's east coast. The rapid urban growth in China's east coast has caused land resource waste to a certain extent. Moreover, we also found that the edges of urban built-up areas were easily mis-extracted, due to the coarse spatial resolution and saturation problem in DMSP/OLS NTL imagery. The new generation of Suomi NPP/VIIRS NTL imagery has greatly improved in spatial and spectral resolutions. In future studies, the advantages of Suomi NPP/VIIRS should be fully explored to provide more accurate monitoring of urban expansion dynamics.

Key words: China's east coast, DMSP/OLS, nighttime light imagery, urban expansion, remote sensing