DMSP OLS: Global Radiance-Calibrated Nighttime Lights Version 4, Defense Meteorological Program Operational Linescan System (NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4)

Version Version 4

The Defense Meteorological Program (DMSP) Operational Line-Scan System
(OLS) has a unique capability to detect visible and near-infrared (VNIR)
emission sources at night.

This collection contains global nighttime lights images with no sensor
saturation. The sensor is typically operated at a high-gain setting to
enable the detection of moonlit clouds. However, with six bit quantization
and limited dynamic range, the recorded data are saturated in the bright
cores of urban centers. A limited set of observations at low lunar
illumination were obtained where the gain of the detector was set
significantly lower than its typical operational setting (sometimes by a
factor of 100). Sparse data acquired at low-gain settings were combined
with the operational data acquired at high-gain settings to produce the set
of global nighttime lights images with no sensor saturation. Data from
different satellites were merged and blended into the final product in order
to gain maximum coverage. For more information, see this
file from the provider.

avg_visAverage digital band numbers from observations with cloud-free light detection.
cf_cvgCloud-free coverages, the total number of observations that went into each 30-arc second grid cell. This image can be used to identify areas with low numbers of observations where the quality is reduced.


NOAA (producer, licensor)
Google Earth Engine (host)
STAC Version 0.6.2
Keywords calibrated, dmsp, imagery, lights, nighttime, noaa, ols, radiance, visible, yearly
License proprietary
Temporal Extent 3/15/1996, 4:00:00 PM - 7/30/2011, 5:00:00 PM
Type image_collection
GSD arc secondsm
cube:dimensions {"x":{"type":"spatial","axis":"x","extent":[-180,-180]},"y":{"type":"spatial","axis":"y","extent":[-65,75]},"temporal":{"type":"temporal","extent":["1996-03-16T00:00:00Z","2011-07-31T00:00:00Z"]},"bands":{"type":"bands","values":["avg_vis","cf_cvg"]}}