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A harmonized global nighttime light dataset 1992-2018.

Xuecao Li1, Yuyu Zhou2, Min Zhao1

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Summary
This summary is machine-generated.

This study integrates nighttime light data from DMSP and VIIRS satellites, creating a consistent 1992-2018 global dataset. This harmonized nighttime light (NTL) data supports research on human activities like electricity consumption and urban growth.

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Area of Science:

  • Earth Observation
  • Remote Sensing
  • Geospatial Analysis

Background:

  • Nighttime light (NTL) data from satellites like DMSP/OLS and VIIRS are valuable for monitoring human activities globally.
  • Existing NTL datasets from DMSP (1992-2013) and VIIRS (2012-2018) have inconsistencies, limiting their combined historical analysis.
  • The full potential of historical NTL archives remains underexplored due to data discrepancies.

Purpose of the Study:

  • To generate an integrated and consistent global nighttime light dataset spanning from 1992 to 2018.
  • To harmonize inter-calibrated DMSP NTL observations with simulated DMSP-like VIIRS NTL observations.
  • To provide a reliable, temporally extended NTL dataset for diverse human activity studies.

Main Methods:

  • Inter-calibration of DMSP/OLS NTL data.
  • Simulation of DMSP-like NTL observations from VIIRS data.
  • Harmonization of DMSP and VIIRS NTL data to create a consistent time-series.

Main Results:

  • A globally consistent NTL dataset from 1992 to 2018 was successfully generated.
  • The integrated dataset exhibits consistent temporal trends across the extended period.
  • The resulting DMSP NTL time-series data supports long-term monitoring.

Conclusions:

  • The harmonized NTL dataset bridges the gap between DMSP and VIIRS, enabling comprehensive historical analysis.
  • This extended dataset is crucial for studying long-term dynamics of human activities, including electricity consumption and urban expansion.
  • The study unlocks the potential of historical NTL archives for global environmental and socioeconomic research.