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基于“珞珈一号”夜光遥感影像的粤港澳大湾区城市空间形态分析

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  • 1. 武汉大学 测绘遥感信息工程国家重点实验室, 武汉 430079;
    2. 广州市城市规划勘测设计研究院, 广州 510060

收稿日期: 2019-11-01

  网络出版日期: 2020-06-11

Urban Spatial Form Analysis of GBA Based on “LJ1-01” Nighttime Light Remote Sensing Images

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  • 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Guangzhou Urban Planning Survey and Design Institute, Guangzhou 510060, China

Received date: 2019-11-01

  Online published: 2020-06-11

摘要

利用“珞珈一号”夜间灯光影像,分别采用简单阈值法与植被调节的城市夜间灯光指数法提取粤港澳大湾区城市建成区.对比两种提取方法,植被调节的城市夜间灯光指数法可以削弱“珞珈一号”影像的过饱和现象,减少由于影像的“溢出”导致的误提取.计算并对比大湾区内城市建成区的景观指数发现,不同城市的建成区分布存在不同模式:广州、深圳、香港作为大湾区发展核心,城市区域向外扩展;东莞、佛山、澳门、中山、珠海的城市建成区紧凑性高,空间分布组成完整;肇庆、江门、惠州在大湾区内的发展程度低于其他城市,城市建成区斑块面积小,相距较远.研究证明了利用“珞珈一号”夜光遥感影像可以有效揭示粤港澳大湾区的城市空间形态,为该地区城市规划政策提供了依据.

本文引用格式

张雨欣, 李熙, 宋杨, 李长辉 . 基于“珞珈一号”夜光遥感影像的粤港澳大湾区城市空间形态分析[J]. 应用科学学报, 2020 , 38(3) : 466 -477 . DOI: 10.3969/j.issn.0255-8297.2020.03.012

Abstract

In this paper, “LJ1-01” nighttime light (NTL) images are used to extract urban built-up areas of Guangdong-Hong Kong-Macao greater bay area (GBA) by employing simple threshold method and vegetation adjusted NTL urban index (VANUI). Comparing the two methods, VANUI is capable of reducing the over-saturations in LJ1-01 images, thus reducing misclassifications caused by “blooming”. The landscape indices of the urban builtup areas in GBA are calculated and analyzed. It is found that there are different patterns in distribution of built-up areas in different cities. As the cores of the development of GBA, Guangzhou, Shenzhen and Hong Kong have expanding urban areas. The urban built-up areas, like Dongguan, Foshan, Macao, Zhongshan and Zhuhai, are highly compact and integrated in spatial distribution. And the urban built-up areas of less developed cities, including Zhaoqing, Jiangmen and Huizhou, are small and separated. This study proves that the LJ1-01 nighttime light images can effectively reveal the urban spatial form of GBA, providing a basis for urban planning policy of GBA.

参考文献

[1] 庞前聪.大湾区城市群空间协同策略研究——基于珠海与粤港澳大湾区互动的视角[J].城市发展研究,2019, 26(7):50-58. Pang Q C. The strategy research of urban agglomeration spatial collaboration on the greater bay area:based on the interaction between Zhuhai and Hong Kong-Zhuhai-Macao bay area[J]. Urban Development, 2019, 26(7):50-58.(in Chinese)
[2] 梁经伟,毛艳华,江鸿泽.影响粤港澳大湾区城市群经济发展的因素研究[J].经济问题探索, 2018(5):90-99. Liang J W, Mao Y H, Jiang H Z. Research on the factors influencing the economic development of regional urban agglomeration in Guangdong, Hong Kong and Macao[J]. Inquiry Into Economic Issues, 2018(5):90-99.(in Chinese)
[3] 陈章喜,吴振帮.粤港澳大湾区城市群土地利用结构与效率评价[J].城市问题,2019(4):29-35 Chen Z X, Wu Z B. Land use structure and land use efficiency evaluation on GuangdongHong Kong-Macao greater bay area urban agglomeration[J]. Urban Problems, 2019(4):29-35(in Chinese)
[4] 汪行东.粤港澳大湾区城市群空间整合分析与展望[J].广东行政学院学报,2019, 31(2):76-86. Wang X D. Outlook and analyses on the spacial integration of Guangdong-Hong Kong-Macao greater bay agglomeration[J]. Journal of Guangdong Administration College, 2019, 31(2):76-86.(in Chinese)
[5] 李郇,周金苗,黄耀福,等.从巨型城市区域视角审视粤港澳大湾区空间结构[J].地理科学进展,2018, 37(12):1609-1622. Li X, Zhou J M, Huang Y F, et al. Understanding the Guangdong-Hong Kong-Macao greater bay area from the perspective of mega-city region[J]. Progress in Geography, 2018, 37(12):1609-1622.(in Chinese)
[6] 邱坚坚,刘毅华,陈浩然,等.流空间视角下的粤港澳大湾区空间网络格局——基于信息流与交通流的对比分析[J].经济地理,2019, 39(6):7-15. Qiu J J, Liu Y H, Chen H R, et al. Urban network structure of Guangdong-Hong Kong-Macao greater bay area with the view of space of flow[J]. Economic Geography, 2019, 39(6):7-15.(in Chinese)
[7] 陈世栋.粤港澳大湾区要素流动空间特征及国际对接路径研究[J].华南师范大学学报(社会科学版),2018(2):27-32. Chen S D. Research on the spatial characteristics of factor flow and its international integration Path in Guangdong-Hong Kong-Macao bay area[J]. Journal of South China Normal University (Social Science Edition), 2018(2):27-32.(in Chinese)
[8] 武文霞.粤港澳大湾区城市群协同发展路径探讨[J].江淮论坛,2019(4):29-34. Wu W X. Discussion on the path of coordinated development of urban agglomerations in Guangdong-Hong Kong-Macao greater bay area[J]. JAC Forum, 2019(4):29-34.(in Chinese)
[9] 徐芳燕,方译.粤港澳大湾区城市群空间结构与经济绩效研究[J].吉林工商学院学报,2018, 34(3):5-13. Xu F Y, Fang Y. A study on spatial structure and economic performance of Guangdong-Hong Kong-Macau greater bay area urban agglomeration[J]. Journal of Jilin Institute of Business and Technology, 2018, 34(3):5-13.(in Chinese)
[10] 杨智威,陈颖彪,吴志峰,等.粤港澳大湾区城市热岛空间格局及影响因子多元建模[J].资源科学,2019, 41(6):1154-1166. Yang Z W, Chen Y B, Wu Z F, et al. Spatial pattern of urban heat island and multivariate modeling of impact factors in the Guangdong-Hong Kong-Macao greater bay area[J]. Resources Science, 2019, 41(6):1154-1166.(in Chinese)
[11] 林媚珍,周汝波,钟亮.基于景观格局变化的粤港澳大湾区生态系统服务变化研究[J].广州大学学报(自然科学版),2019, 18(2):87-95. Lin M Z, Zhou R B, Zhong L. Research on the changes of ecosystem services in GuangdongHong Kong-Macao greater bay area based on the change of landscape pattern[J]. Journal of Guangzhou University (Natural Science Edition), 2019, 18(2):87-95.(in Chinese)
[12] 国务院.粤港澳大湾区发展规划纲要[EB/OL]. 2019-02-18[2019-11-01]. http://www.gov.cn/gongbao/content/2019/content_5370836.htm
[13] 司长强,黄奕.粤港澳大湾区文化产业发展的环境、策略及价值[J].特区经济,2019(8):26-30. Si C Q, Huang Y. Environment, strategy and value of cultural industry development in Dawan District of Guangdong, Hong Kong and Macao[J]. Special Zone Economy, 2019(8):26-30.(in Chinese)
[14] 李德仁,李熙.论夜光遥感数据挖掘[J].测绘学报,2015, 44(6):591-601. Li D R, Li X. An overview on data mining of nighttime light remote sensing[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6):591-601.(in Chinese)
[15] 李德仁,余涵若,李熙.基于夜光遥感影像的"一带一路"沿线国家城市发展时空格局分析[J].武汉大学学报(信息科学版),2017, 42(6):711-720. Li D R, Yu H R, Li X. The spatial-temporal pattern analysis of city development in countries along the belt and road initiative based on nighttime light data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6):711-720.(in Chinese)
[16] Elvidge C D, Baugh K E, Dietz J B, et al. Radiance calibration of DMSP-OLS low-light imaging data of human settlements[J]. Remote Sensing of Environment, 1999, 68(1):77-88.
[17] Elvidge C D, Imhoff M L, Baugh K E, et al. Nighttime lights of the world:1994-1995[J]. Journal of Photogrammetry and Remote Sensing, 2001, 56(2):81-99.
[18] Elvidge C D, Baugh K, Zhizhin M, et al. VIIRS nighttime lights[J]. International Journal of Remote Sensing, 2017, 38(21):5860-5879.
[19] Miller S D, Mills S P, Elvidge C D, et al. Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities[J]. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(39):15706-15711.
[20] Liu X P, Hu G H, Ai B, et al. A normalized urban areas composite index (NUACI) based on combination of DMSP-OLS and MODIS for mapping impervious surface area[J]. Remote Sensing, 2015, 7(12):17168-17189.
[21] Li X C, Zhou Y Y. Urban mapping using DMSP/OLS stable nighttime light:a review[J]. International Journal of Remote Sensing, 2017, 38(21):6030-6040.
[22] Li X, Li X Y, Li D R, et al. A preliminary investigation of Luojia-1 nighttime light imagery[J]. Remote Sensing Letters, 2019, 10(6):526-535.
[23] Li X, Liu Z M, Chen X L, et al. Assessing the ability of Luojia 1-01 imagery to detect feeble nighttime lights[J]. Sensors, 2019, 19(17):3708.
[24] Zhang G, Guo X Y, Li D R, et al. Evaluating the potential of LJ1-01 nighttime light data for modeling socio-economic parameters[J]. Sensors, 2019, 19(6):1465.
[25] Li C, Zou L Q, Wu Y J, et al. Potentiality of using Luojia1-01 nighttime light imagery to estimate urban community housing price-a case study in Wuhan, China[J]. Sensors, 2019, 19(14):3617.
[26] Li X, Zhao L X, Li D R, et al. Mapping urban extent using Luojia 1-01 nighttime light imagery[J]. Sensors, 2018, 18(11):3665.
[27] 何春阳,史培军,李景刚,等.基于DMSP/OLS夜间灯光数据和统计数据的中国大陆20世纪90年代城市化空间过程重建研究[J].科学通报,2006(7):856-861. He C Y, Shi P J, Li J G, et al. Research on urbanization space process reconstruction in mainland China in the 1990s based on DMSP/OLS nighttime light data and statistical data[J]. Chinese Science Bulletin, 2006(7):856-861.(in Chinese)
[28] Xie Y H, Weng Q H. Updating urban extents with nighttime light imagery by using an object-based thresholding method[J]. Remote Sensing of Environment, 2016, 187:1-13.
[29] Li K N, Chen Y H. A genetic algorithm-based urban cluster automatic threshold method by combining VIIRS DNB, NDVI, and NDBI to monitor urbanization[J]. Remote Sensing, 2018, 10(2):277.
[30] Ma W T, Li P J. An object similarity-based thresholding method for urban area mapping from visible infrared imaging radiometer suite day/night band (VIIRS DNB) data[J]. Remote Sensing, 2018, 10(2):263.
[31] Zhou Y Y, Smith S J, Elvidge C D, et al. A cluster-based method to map urban area from DMSP/OLS nightlights[J] Remote Sensing of Environment, 2014, 147:173-185.
[32] Lu D S, Tian H Q, Zhou G M, et al. Regional mapping of human settlements in southeastern China with multisensor remotely sensed data[J]. Remote Sensing of Environment, 2008, 112(9):3668-3679.
[33] Zhang Q L, Schaaf C, Seto K C. The vegetation adjusted NTL urban index:a new approach to reduce saturation and increase variation in nighttime luminosity[J]. Remote Sensing of Environment, 2013, 129:32-41.
[34] 汤佳. 2008-2016年南昌市景观时空演变特征及驱动力分析[J].环境监测管理与技术,2019, 31(5):16-20. Tang J. Analysis of temporal and spatial characteristics and driving forces of landscape change in Nanchang from 2008 to 2016[J]. The Administration and Technique of Environmental Monitoring, 2019, 31(5):16-20.(in Chinese)
[35] 黄梦娜,马廷.中国道路网引起的景观破碎格局及其对保护区的影响[J].地球信息科学学报,2019, 21(8):1183-1195. Huang M N, Ma T. Assessing the impacts of China's road network on landscape fragmentation and protected areas[J]. Geo-Information Science, 2019, 21(8):1183-1195.(in Chinese)
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