1. A Prolonged Artificial Nighttime-light Dataset of China (1984-2020).
- Author
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Zhang, Lixian, Ren, Zhehao, Chen, Bin, Gong, Peng, Xu, Bing, and Fu, Haohuan
- Subjects
PANDAS ,GROSS domestic product ,REMOTE sensing ,SOCIOECONOMICS ,DATA quality - Abstract
Nighttime light remote sensing has been an increasingly important proxy for human activities. Despite an urgent need for long-term products and pilot explorations in synthesizing them, the publicly available long-term products are limited. A Night-Time Light convolutional LSTM network is proposed and applied the network to produce a 1-km annual Prolonged Artificial Nighttime-light DAtaset of China (PANDA-China) from 1984 to 2020. Assessments between modeled and original images show that on average the RMSE reaches 0.73, the coefficient of determination (R
2 ) reaches 0.95, and the linear slope is 0.99 at the pixel level, indicating a high confidence in the quality of generated data products. Quantitative and visual comparisons witness PANDA-China's superiority against other NTL datasets in its significantly longer NTL dynamics, higher temporal consistency, and better correlations with socioeconomics (built-up areas, gross domestic product, population) characterizing the most relevant indicator in different development phases. The PANDA-China product provides an unprecedented opportunity to trace nighttime light dynamics in the past four decades. [ABSTRACT FROM AUTHOR]- Published
- 2024
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