Night-time lighting as a new source of data


Night-time lighting is being promoted as a new data source for energy and other applications in NASA’s Black Marble initiative.

Black Marble is a daily calibrated product suite drawing on night-time satellite images of the Earth showing artificial lighting. These are then offered as a data source for investigating a whole range of interactions between human systems and the environment.

The images are collected on the Suomi National Polar-orbiting Partnership satellite, a weather satellite that orbits Earth about 14 times per day.

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The images are processed to remove cloud contamination and corrected for atmospheric and other effects and then validated against ground measurements so they can be used effectively.

The daily product provides a 15arcsec resolution, while the moonlight corrected product is 500m resolution, with both available from January 2012.

A wide range of applications are touted from the images, which can stand alongside GIS and other remote sensed data, ranging from light pollution to fires and disaster recovery among others.

“Thanks to [the images], we can now monitor short-term changes caused by disturbances in power delivery, such as conflict, storms, earthquakes and brownouts,” says NASA Earth Scientist and Black Marble Principal Investigator Miguel Román.

“We can monitor cyclical changes driven by reoccurring human activities such as holiday lighting and seasonal migrations. We can also monitor gradual changes driven by urbanisation, out-migration, economic changes and electrification.”

Puerto Rico outage restoration

A specific application of the data has been to create spatially disaggregated power outage estimates, which have been applied to investigate restoration efforts in Puerto Rico following the Hurricane Maria caused a blackout in September 2017.

The results show an 80% decrease in lights, in total, immediately after Hurricane Maria.

During the recovery, a disproportionate share of long-duration (>120 days) power failures are observed to have occurred in rural municipalities and in the northern and eastern districts.

Notably, large disparities were apparent in electricity recovery between neighbourhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, who are the most vulnerable to increased mortality and morbidity risks from power losses, appeared to shoulder the longest outages because they lived in less dense, detached housing where electricity restoration lagged.