How use VIIRS Data

NASA has developed the “Black Marble” satellite product that delivers data originally retrieved from the VIIRS day/night band sensor.

As you can read on the NASA page, the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is a component of the Suomi National Polar-orbiting Partnership (NPP) satellite. VIIRS consists of 22 spectral bands from ultraviolet to mid-infrared, one of which is capable of observing night lights, the day-night (DNB) band. DNB is a panchromatic band sensitive to visible and near-infrared wavelengths.

Despite the acquisition of these data being good news, our purpose is to offer as much scientific information as possible and be careful in the use of this data, if you are looking for and need data for your studies, on the amount of light.

But first, we need to understand the scenario we are in in order to obtain the best possible data for our studies.


Scientific studies reveal that the growth of light pollution is a real challenge: between 1992 and 2017 it was estimated that it increased by at least 49%.

But not only has urban growth and development, along with an increase in lighting, made this increase possible, but it has also been shown that the change in technology to solid-state light-emitting diodes (LED) has only made the situation worse.

Therefore, it seems necessary to work with data that can measure this change well (from sodium lamps to LED), otherwise the estimation of the amount of light, and for many studies, the evolution of light pollution, will be wrong.

What about VIIRS

Since December 2011, the Visible Infrared Imaging Radiation Suite (VIIRS) day/night band (DNB) aboard the NASA/NOAA Suomi National Polar Orbiting Partnership (Suomi-NPP) satellite has provided a product Radiance calibration with global coverage and has a higher dynamic range without saturation, allowing comparison between images and detection of change even within brightly lit areas. It has a higher spatial resolution (740 m), and the archived cloud-free composite products suffer less from errors in georeferencing and “blooming” effects.


While it is true that the VNP46 product suite has corrections (VIIRS calibrated radiances, cloud mask, recovery aerosol), there have been comparative tests (Detection Limit and Robustness, VIIRS Night Cloud Mask Performance, Pixel-Based Variations in NTL), with the idea only to provide a relative assessment of the performance of the product.

That is, it is important not to work with this data until it is error-free or until known sources of error are eliminated by reprocessing the product. It must be emphasized that it is necessary to work with accurate data, whatever the source, especially when, based on these data, studies are carried out, whether environmental or social.

Another important fact is that it cannot reliably capture the technological transition of street lighting from conventional.
For several decades, outdoor lighting has primarily used High Pressure Sodium (HPS), Low Pressure Sodium (LPS), Metal Halide (MH) and fluorescent lamps. However, there are now widespread shifts towards ‘white’ light-emitting diode (LED) lamps, which are projected to soon become the dominant source, and whose emissions have repeatedly been found to have more severe environmental impacts (Davies et al. ., 2017, Davies et al., 2014).

As confirmed in previous studies, the RSR of the VIIRS DNB does not include the peak blue light emission from white LEDs (Cao and Bai, 2014; Falchi et al., 2016), and therefore use the VIIRS data to analyzing light pollution, especially when there has been a change in technology, is not the most sensible thing to do.

In the following image you can see how the VIIRS data is blind in the blue spectrum.

Example using VIIRS data without analysis

Probably the best known recent conversion of a streetlight system has been in 2015 in the city of Milan during which high pressure sodium lamps were replaced with LEDs.

This change, and analyzing the VIIRS images, before and after, it could be deduced that light pollution had been reduced by 50%.

In the scientific article “Colour remote sensing of the impact of artificial light at night (I): The potential of the International Space Station and other DSLR-based platforms”, Sánchez de Miguel et al. (2019) showed that using the ISS images in those same years, light pollution had not decreased, but increased.

In the analysis, they focused on two environmental measures: photopic intensity and Melatonin Supression Impact (MSI).
For the first, there were no measurable changes in photopic intensity, and this is because the streetlight conversion was designed to produce the same luminance level as the original streetlights. By contrast, there was an increase in MSI values of 37% in Milan.

Images ISS032-e-012145(2012) and ISS043-e-093509(2015) taken from Sánchez de Miguel et al. (2015) and downloaded from NASA’s Gateway to Astronaut Photography of Earth (
Images taken from the ISS corrected to represent MSI.

What can we do if we want to work with the VIIRS VNP46 product?

As we mentioned, the excellence in this product is the daily time series that can be obtained. The drawbacks, those already mentioned. But, there is an alternative, and thus likely vitally important, source of remotely sensed spatial and temporal data on the spectrum of artificial nighttime lighting is photographs taken by astronauts on the International Space Station (ISS). Nocturnal images are available from 2003 to the present, although their temporal and spatial distributions are variable. Between 2003 and 2010, a total of 35,995 nighttime images were taken, with a further 423,520 between 2011 and November 2014. Of these, at least 30,000 images are of cities at night (Sánchez de Miguel et al., 2014, Sánchez de Miguel, 2015).

So, one way to use the VIIRS data is by combining this product with the color images provided by the ISS. Through this process, a better product can be obtained, in color and with a higher resolution.


VIIRS is a good way to confirm established empirical relationships with a wide variety of patterns and processes related to human activity. So how much to use the VIIRS data? In simple words, VIIRS temporal data can be more useful to define if there is light or not, for example, in the observations of:


  1. Electrification of urban settlements and stability of electrical fluid
    highway expansion.
  2. Studies of behavior and urban development
  3. Economic growth (as long as there are no technology transitions).
  4. Migrations
  5. Armed conflicts
  6. Weather phenomena, etc.