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Published April 25, 2023 | Version v1
Dataset Open

Reconstructed Three-decade Global Fine-Grained Nighttime Light Observations

  • 1. Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University & Shanghai Qizhi Institute
  • 2. Institute for Interdisciplinary Information Sciences, Tsinghua University & Shanghai Qizhi Institute
  • 3. Institute of Atmosphere Physic, Chinese Academy of Sciences & Shanghai Qizhi Institute
  • 4. Institute of Environmental Physics, University of Bremen

Description

Nighttime light (NTL) is a foundational data source for studying human activities from a remote sensing perspective. This dataset from 1992 to 2019 is the first global long-term and fine-grained NTL observations. It represents a milestone in facilitating the study of human activities. It is created by a new super-resolution model DeepNTL which converts DMSP-OLS images into NPP-VIIRS images. Compared with baseline models, including RCAN, SwinIR and AutoEncoder, DeepNTL has the hightest accuracy and best generalization ability for untrained years. It provides a good extension of NPP-VIIRS to the early years, and the future annual NPP-VIIRS data can be directly appended to this dataset by users own. More information about the dataset can be found in the "read_me.txt" file. Technical details and evaluations are presented in our paper. Any questions are welcome to be sent to guojy@sqz.ac.cn.

Files

read_me.txt

Files (5.6 GB)

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