地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (5): 1153-1160.doi: 10.12082/dqxxkx.2020.190549

• “空间综合人文学与社会科学”专辑 • 上一篇    下一篇

民航客机平台夜光遥感方法在香港经济活动变化检测中的应用

王永全1,2, 汪驰升1,2,3,*(), 王乐涵1, 佘佳霓1, 李清泉1   

  1. 1.广东省城市空间信息工程重点实验室,深圳大学建筑与城市规划学院,深圳 518060
    2.自然资源部大湾区地理环境监测自然资源部重点实验室,深圳大学,深圳 518060
    3.自然资源部城市国土资源监测与仿真重点实验室,深圳 518060
  • 收稿日期:2019-09-25 修回日期:2020-03-24 出版日期:2020-05-25 发布日期:2020-07-25
  • 通讯作者: 汪驰升 E-mail:wangchisheng@163.com
  • 作者简介:王永全(1994— ),男,安徽五河人,硕士生,主要从事系留无人机和遥感数据分析及应用研究。E-mail:1058309323@qq.com
  • 基金资助:
    深圳市科创委研究项目(KQJSCX20180328093453763);深圳市科创委研究项目(JCYJ20180305125101282);国家自然科学基金项目(41974006);自然资源部城市国土资源监测与仿真重点实验室(KF-2018-03-004);深圳大学教师启动项目(2018073)

Preliminary Application of Night Light Remote Sensing based on Passenger Aircraft in Hong Kong Economic Activity Zone Changes Identification

WANG Yongquan1,2, WANG Chisheng1,2,3,*(), WANG Lehan1, SHE Jiani1, LI Qingquan1   

  1. 1. Guangdong Key Laboratory of Urban Informatics, School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
    2. Key Laboratory for Geo-Environmental Monitoring of Great Bay Area of Ministry of Natural Resources, Shenzhen University, Shenzhen 518060, China
    3. Key Laboratory of Urban Land Resources Monitoring and Simulation of Ministry of Natural Resources, Shenzhen 518060, China
  • Received:2019-09-25 Revised:2020-03-24 Online:2020-05-25 Published:2020-07-25
  • Contact: WANG Chisheng E-mail:wangchisheng@163.com
  • Supported by:
    Shenzhen Scientific Research and Development Funding Program(KQJSCX20180328093453763);Shenzhen Scientific Research and Development Funding Program(JCYJ20180305125101282);National Nature Science Foundation of China(41974006);Key Laboratory of Urban Land Resources Monitoring and Simulation of Ministry of Natural Resources(KF-2018-03-004);Shenzhen University NatureScienceFunding Program(2018073)

摘要:

大规模持续的示威游行活动会影响一个城市的经济活动。自2019年6月开始,香港地区持续性的示威游行活动对多个行业产生冲击,香港地区经济受到一定程度影响。快速准确地识别出经济活动受影响区域将有助于政府进行准确损失评估和制定有效的经济恢复政策。本文首次提出使用民航客机夜光遥感结合VGI数据识别经济活动受影响区域的方法。首先在民航客机平台上用手机获取了研究区域2019年8月28日的高度重叠的照片,然后基于摄影测量技术对照片进行拼接处理生成夜光遥感影像,再与珞珈一号-01星夜光遥感影像、POI密度图对比初步筛选出受影响区域。最后通过VGI照片数据进行验证,检测出观塘区有2个经济活动下降的区域,并做了定量分析,发现在观塘区有2个区域的DN值相关比例分别下降了9.52%和19.42%。利用本文的方法能快速识别香港经济活动受影响区域,对于研究其他城市的经济变化有着借鉴意义,在城市精准治理方面也有重要的应用价值。

关键词: 民航客机, 夜光遥感, 志愿者地理数据, 游行示威活动, 社会经济变化, 影响区识别, 光亮度, 珞珈一号

Abstract:

Large-scale sustained demonstrations will seriously affect the stability of social order. Since June 2019, Hong Kong's economy has been affected to some extent by the impact of continuous demonstrations on various industries. Rapid and accurate identification of areas affected by demonstrations plays a very important role in loss assessment, economic recovery, and government governance. In this paper, we proposed a novel method to identify the affected areas using night light remote sensing and VGI data. Firstly, we captured the highly overlapping photographs of the study area by a mobile phone on passenger aircraft on August 28, 2019. Following regular photogrammetry steps, night light remote sensing image was generated. Then we compared it with POI density maps and Luojia-01 night light image, and initially marked the affected areas, which were further validated by VGI photos. We finally confirmed two affected areas in Kwun Tong District. A simple quantitative analysis was performed to assess the influence on affected areas. We conclude that the proposed method can quickly identify the areas where economic activities are affected in Hong Kong. Our method can also be used to study economic changes in other cities, which is of great application value in precise urban governance.

Key words: passenger aircraft, night light remote sensing, VGI data, protest movements, socio-economic changes, impact area identification, brightness, Luojia 1-01