Lab 4 - Night Time Lights

Part 1: Loading Nighttime Lights Data

To begin, add this code to your script and run it:

var lights93 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F101993');

print('Nighttime lights', lights93);

Map.addLayer(
    lights93,
    {
        bands: ['stable_lights'],
        min: 0,
        max: 63
    },
    'Lights');

Understanding the code:

• ee.Image() - Loads a single nighttime lights image from 1993
• stable_lights - The band containing persistent artificial light sources
• min: 0, max: 63 - The data range for this sensor (0 = dark, 63 = brightest)

The first line of the code calls the NOAA Nighttime Lights Time Series. You can learn more about it here: NOAA DMSP-OLS Nighttime Lights Catalog

The global nighttime lights image represents the average brightness of nighttime lights at each pixel for a calendar year. For those of us who have sat by a window in an airplane as it descends to a destination at night, the scene may look vaguely familiar. But the image is very much an abstraction. It provides us with a view of the planet that we would never be able to see from an airplane or even from space. Night blankets the entire planet in darkness. There are no clouds. In the "stable lights" band, there are no ephemeral sources of light. Lightning strikes, wildfires, and other transient lights have been removed. It is a layer that aims to answer one question about our planet at one point in time: In 1993, how bright were Earth's stable, artificial sources of light?

Part 2: Creating a Temporal Composite

Now we can use the additive color system to make an RGB composite that compares stable nighttime lights at three different slices of time. Add the code below to your script and run it.

var lights03 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152003')
    .select('stable_lights').rename('2003');

var lights13 = ee.Image('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182013')
    .select('stable_lights').rename('2013');

var changeImage = lights13.addBands(lights03)
    .addBands(lights93.select('stable_lights').rename('1993'));

print('change image', changeImage);

Map.addLayer(
    changeImage,
    {
        min: 0,
        max: 63
    },
    'Change composite');

Understanding the code:

• .select('stable_lights') - Extracts just the stable lights band
• .rename('2003') - Renames the band to indicate the year
• .addBands() - Combines multiple images into a single multi-band image
• The order matters: 2013 → Red, 2003 → Green, 1993 → Blue

Part 3: Interpreting the Composite

We can now read the colors displayed on the layer to interpret different kinds of changes in nighttime lights across the planet over two decades:

Use the Inspector panel to verify your interpretations. Click on the Inspector tab, then click on a pixel. Look under the Pixel category for the "Change composite" layer. The pixel value for each band should match your color interpretation.

When you zoom out from Shanghai, you will likely notice that each map layer redraws every time you change the zoom level. In order to explore the change composite layer more efficiently, use the Layer manager panel to not show (uncheck) all of the layers except for "Change composite." Now the map will respond faster when you zoom and pan.

Part 4: Patterns Beyond Cities

In addition to urban change, the layer also shows changes in resource extraction activities that produce bright lights. Often, these activities produce lights that are stable over the span of a year (and therefore included in the "stable lights" band) but are not sustained over the span of a decade or more.

Example 1: Fishing Fleets

In the Korean Strait (between South Korea and Japan), you can see geographic shifts in fishing fleets that use bright halogen lights to attract squid and other sea creatures toward the water surface and into their nets. Bluish pixels were likely fished more heavily in 1993 and became used less frequently by 2003, while greenish pixels were likely fished more heavily in 2003 and less frequently by 2013.

Example 2: Gas Flaring

Similarly, fossil fuel extraction produces nighttime lights through gas flaring. If you pan to North America, red blobs in Alberta and North Dakota and a red swath in southeastern Texas all represent places where oil and gas extraction were absent in 1993 and 2003 but booming by 2013.

As you explore this image, remember to check your interpretations with the Inspector panel by clicking on a pixel and reading the pixel value for each band. Refer back to the additive color figure to remember how the color system works.