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

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。

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

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.