Uncertainties and Challenges in Daily Nighttime Light Time Series Data
ID:2182 View Protection:ATTENDEE Updated Time:2024-04-12 10:08:19 Hits:1692 Invited speech

Start Time:2024-05-18 13:20(Asia/Shanghai)

Duration:15min

Session:S7 主题7、遥感与地理信息科学 » S7-2主题7、遥感与地理信息科学 专题7.17、专题7.19(18日下午,303)

No files

Abstract
Nighttime light (NTL) remote sensing data offer unique capabilities to characterize both the extent and intensity of human activities and have been extensively used to understand urbanization. The recent proliferation of daily NTL time series data products provides new opportunities to unveil temporal change patterns of human activities and urbanization process at a finer temporal scale,compared with the traditional yearly and monthly composite NTL data. However, the high temporal variation and intertwined uncertainties of daily NTL time series data have formed formidable challenges. In this talk, I will share my analysis and perspectives on the key uncertainties and challenges in daily NTL time series data and their impacts on NTL-based urban applications.
Keywords
nighttime light data
Speaker
郑启明
The Hong Kong Polytechnic University

Submission Author
郑启明 The Hong Kong Polytechnic University
Submit Comment
Verify Code Change Another
All Comments
Important Date
  • Conference Date

    May 17

    2024

    to

    May 20

    2024

  • Mar 31 2024

    Draft paper submission deadline

  • Mar 31 2024

    Contribution Submission Deadline

  • May 20 2024

    Registration deadline

Sponsored By
青年地学论坛理事会
Organized By
厦门大学近海海洋环境科学国家重点实验室
中国科学院城市环境研究所
自然资源部第三海洋研究所
Contact Information
Previous Conferences