https://ore.exeter.ac.uk/repository/bitstream/10871/40052/1/Levin%20NTL50yr%20paper%2020190916%20w%20FIGS%20compressed%20clean.pdf

Remote sensing of night lights: A review and an outlook for the future

Understanding an urbanizing planet: Strategic directions for remote sensing

. The nighttime light (NTL) satellite data have been widely
used to investigate the urbanization process. The Defense Meteorological
Satellite Program Operational Linescan System (DMSP-OLS) stable nighttime
light data and Suomi National Polar-orbiting Partnership Visible Infrared
Imaging Radiometer Suite (NPP-VIIRS) nighttime light data are two widely
used NTL datasets. However, the difference in their spatial resolutions and
sensor design requires a cross-sensor calibration of these two datasets for
analyzing a long-term urbanization process. Different from the traditional
cross-sensor calibration of NTL data by converting NPP-VIIRS to
DMSP-OLS-like NTL data, this study built an extended time series (2000–2018)
of NPP-VIIRS-like NTL data through a new cross-sensor calibration from
DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL
data (2013–2018). The proposed cross-sensor calibration is unique due to the
image enhancement by using a vegetation index and an auto-encoder model.
Compared with the annual composited NPP-VIIRS NTL data in 2012, our product
of extended NPP-VIIRS-like NTL data shows a good consistency at the pixel
and city levels with R2 of 0.87 and 0.95, respectively. We also found
that our product has great accuracy by comparing it with DMSP-OLS radiance-calibrated NTL (RNTL) data in 2000, 2004, 2006, and 2010. Generally, our
extended NPP-VIIRS-like NTL data (2000–2018) have an excellent spatial
pattern and temporal consistency which are similar to the composited
NPP-VIIRS NTL data. In addition, the resulting product could be easily
updated and provide a useful proxy to monitor the dynamics of demographic
and socioeconomic activities for a longer time period compared to existing
products. The extended time series (2000–2018) of nighttime light data is
freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et
al., 2020).

/pdf/an-extended-time-series-2000-2018-of-global-npp-viirs-like-sh12iaftfi.pdf

An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration

Nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite provide a great opportunity for monitoring human activities from regional to global scales. Despite the valuable records of nightscape from DMSP (1992-2013) and VIIRS (2012-2018), the potential of the historical archive of NTL observations has not been fully explored because of the severe inconsistency between DMSP and VIIRS. In this study, we generated an integrated and consistent NTL dataset at the global scale by harmonizing the inter-calibrated NTL observations from the DMSP data and the simulated DMSP-like NTL observations from the VIIRS data. The generated global DMSP NTL time-series data (1992-2018) show consistent temporal trends. This temporally extended DMSP NTL dataset provides valuable support for various studies related to human activities such as electricity consumption and urban extent dynamics.

/pdf/a-harmonized-global-nighttime-light-dataset-1992-2018-2t8i35g6lb.pdf

A harmonized global nighttime light dataset 1992-2018.

A global record of annual urban dynamics (1992-2013) from nighttime lights

https://data.fs.usda.gov/research/pubs/iitf/ja_iitf_2018_Roman.pdf

Gary Lin

Papers

NASA's Black Marble Nighttime Lights Product Suite