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Using a Digital Camera to Measure Skyglow

Difficulty
Time Required Long (2-4 weeks)
Prerequisites You'll need a digital camera that take pictures in manual mode with exposure times of up to 15 seconds. You will need to know how to change the shutter speed, lens aperture, and ISO setting. A tripod for the camera is nice to have, but not absolutely essential. You will also need a computer.
Material Availability Readily available
Cost Very Low (under $20)
Safety Adult supervision required for night photography.

Abstract

This is a great project for someone that is interested in both stargazing and photography. Bright city lights and even the light of the full moon obscure the dimmest stars, which can make identifying constellations more difficult. This project shows you a way to measure the amount of background light (skyglow) in the night sky. It can be a great way for you to quickly compare the star viewing quality for different locations, or for the same location at different times of the year.

Objective

The goal of this project is to measure skyglow (also known as light pollution) in the nighttime sky using a digital camera.

Credits

Andrew Olson, Ph.D., Science Buddies

Sources

This project is based on an article in Sky & Telescope magazine:

    Flanders, T., 2006. "Measuring Skyglow with Digital Cameras," Sky & Telescope, February, 2006: 99–104.

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Last edit date: 2013-01-10

Introduction

If you've ever had the chance to see the clear night sky somewhere "out in the country" and away from city lights, you know that there are many more stars to see under these darker conditions. In urban and suburban areas, artificial lights create a skyglow that is bright enough to obscure dimmer stars.

Skyglow is scattered light in the atmosphere from artifical light sources on the surface. In the daytime, the bright light of the sun obscures any light from more distant stars. Skyglow acts in a similar way to obscure starlight. In urban areas, bright skyglow obscures light from all but the brightest stars.

An experienced stargazer can estimate the amount of skyglow in a given location by noting what features of the night sky can and cannot be seen. The Bortle Dark Sky Scale is a recent example of this type of skyglow measurement (Bortle, 2001; NOVAC, date unknown). A problem with any such scale is that familiarity with the night sky is required in order to use it. If you are just starting out in astronomy, you won't have that knowledge.

This project shows you how to use a digital camera to get a quantitative measure of skyglow. You could use the information you collect in this project to find out what stars you could expect to see in a new location, after taking a reading in the new location with your digital camera.

Terms and Concepts

To do this project, you should do research that enables you to understand the following terms and concepts:

  • pixel gray levels,
  • saturation,
  • dynamic range,
  • apparent magnitude (measurement for brightness of stars),
  • zenith,
  • horizon,
  • altitude.

Questions

  • Which is brighter, a star with an apparent magnitude of 6 or a star with an apparent magnitude of 1?
  • For the same two stars, how much brighter is the brighter one?

Bibliography

  • This project is based on an article in Sky & Telescope magazine:
    Flanders, T., 2006. "Measuring Skyglow with Digital Cameras," Sky & Telescope, February, 2006: 99–104.
  • This website has information on night sky brightness all over the world:
    Cinzano, F., 2000. "The Night Sky in the World," Istituto di Scienza e Tecnologia dell'Inquinamento Luminoso (Light Pollution Science and Technology Institute) [accessed February 19, 2007] http://www.lightpollution.it/dmsp/index.html.
  • You can find information about local observing conditions for locations all over North America from this website, which uses forecast information from the Canadian Meteorological Centre:
    Danko, A., 2007. "The Clear Sky Clock Home Page," [accessed February 19, 2007] http://www.cleardarksky.com/csk/.
  • Here are two references on star magnitudes:
  • ImageJ is a public domain Java image processing program that runs on any computer with a Java 1.4 or later virtual machine. Downloadable distributions are available for Windows, Mac OS, Mac OS X and Linux. The webpages below are the ImageJ home page, the ImageJ download page, and the ImageJ installation instructions page:
  • For information on the Bortle Dark Sky Scale, see:
    • Bortle, J., 2001. "Introducing the Bortle Dark-Sky Scale," Sky and Telescope February, 2001: 126.
    • NOVAC, date unknown. "John Bortle's Light Pollution Scale," Northern Virginia Astronomy Club [accessed April 2, 2007] http://www.novac.com/lp/def.php.

Materials and Equipment

To do this experiment you will need the following materials and equipment:

  • digital camera that can take reasonably long (10–20 s) exposures under full manual control,
  • computer,
  • imaging software that can create histograms of pixel values from digital photos:
    • this project uses a freely available, multi-platform program called ImageJ,
    • if you have Adobe Photoshop it will also work, but you will need to figure out how to create the histograms on your own (should be pretty easy);
  • one or more locations to take photos of night sky,
  • sheet of white paper,
  • tripod (useful, but not absolutely necessary).

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Experimental Procedure

  1. Use the following procedure to measure your camera's dynamic range (its range of response to different light levels).
    1. Set up a piece of white paper so that it is uniformly illuminated by indirect sunlight.
    2. Set up the camera so that the paper fills the field of view. Mount the camera on a tripod, if you have one. Otherwise, place the camera on a solid support. (Many of the exposures you will take will be too long for hand-holding the camera.)
    3. Put the camera in manual mode. If the camera has a manual focus mode, use it to set the correct focal distance. (The auto focus system may have difficulty focusing on the blank white paper, and you want the camera set at a constant focal distance.)
    4. Set the camera's sensitivity to ISO 200.
    5. Set the aperture to f/2.8.
    6. Take a series of photos at different shutter speeds, varying by a factor of 2 each time. For example: 8, 4, 2, 1, 1/2, 1/4, 1/8, 1/15, 1/30, 1/60, 1/125, 1/250, 1/500, 1/1000 s.
    7. To avoid shaking the camera when you take the photo, use the camera's self-timer feature, if available.
    8. Repeat the sequence twice. This is a control to make sure that the ambient light level is constant. You should get very similar results each time. If not, repeat the test. Avoid changing light conditions, such as when the sun is periodically dimmed by clouds.
  2. Follow your camera's instructions to download the photos to your computer.
  3. Use an image processing program to measure the average pixel intensity of each photo. We used ImageJ, a freely available, multi-platform scientific image analysis program (Rasband, 1997–2006a). Here's how:
    1. Follow the instructions on the ImageJ website to download and install the program (Rasband, 1997–2006b; Rasband, 1997–2006c).
    2. Start the ImageJ program. You'll see a small window similar to the one in the screenshot below (the 'skin' may look slightly different on your system). This window is the ImageJ menu bar.

      screenshot of ImageJ menu bar window

    3. Use the "File/Open..." menu command to open your first image file.
    4. Use the "Analyze/Histogram" menu command (or type "H") to create a histogram of pixel values for the image.
    5. The histogram will pop up in its own window, similar to the screenshot below:

      screenshot of ImageJ histogram window

    6. Make a table in your lab notebook to keep track of the pixel intensity information for each file. For example:
      Filename Shutter Speed
      (from your camera's photo-browsing software)
      Pixel Gray Level Statistics
      Mean Std. Dev. Min Max Mode
                   
                   
    7. Use "File/Open Next" (keyboard shortcut "Shift+O") to open the next image file.
    8. Repeat steps 3d–3g until you have analyzed all of your calibration files.
  4. Make a graph of average pixel gray level vs. shutter speed.
    1. Which 'average' value should you choose for plotting on the y-axis? The short answer is: either the mean or the mode should work fine. (See the Science Buddies How-To materials on Summarizing Your Data for more information.)
    2. Since you are using a logarithmic series of shutter speeds, your x-axis should be logarithmic.
    3. Use semi-log graph paper, or set up your graphing program to use a logarithmic axis for the x-values.
    4. Here is an example graph, plotting the mode of the gray levels (blue circles) vs. shutter speed for a series of photos (two trials for each shutter speed). The shutter speeds are plotted on a logarithmic scale. The red squares illustrate a linear series of gray levels, for comparison (each successive point is twice the gray level of the previous one). The red bars show the regions of saturation, and the green bar shows the available dynamic range of the camera.

      gray scale calibration graph: mode of gray levels vs. shutter speed

  5. Here are some camera setup tips for taking skyglow photos.
    1. You need to use manual mode, so that you have full control over the shutter speed and aperture.
    2. Set the aperture to its largest f-number (widest opening).
    3. Typical settings for a reasonably dark sky would be 15 seconds at f/2.8.
    4. If your camera has a manual focus option, use it to set the focal length at infinity.
    5. Set the camera's sensitivity to ISO 200.
    6. If your camera has a black-and-white mode, use it.
    7. Set the image resolution to a low setting (e.g., 640 × 480).
    8. To avoid shaking the camera when you take the photo, use the camera's self-timer feature, if available.
    9. A tripod is helpful, but not absolutely necessary. Typically, you want to take a picture straight up, so you can simply lay the camera down on the ground (padded with an old towel, perhaps) facing up.
  6. Write the location, date and time of each picture in your lab notebook for future reference. You'll be able to match the location to the picture using the date and time information saved in the image file. (Make sure your camera's date and time are set correctly!)
  7. Follow the instructions in step 3 to measure the average pixel gray level in the center of each skyglow image.
    1. The only difference is that instead of using a histogram for the entire image, you'll select a rectangular area from the center of the image.
    2. Using the rectangular selection tool, click and drag to create a rectangular selection at the center of the image.
    3. Use the same rectangle for each image (note the size and location in your lab notebook for future reference). If you follow the instructions above for stepping through the images one by one, this is easy to do.
  8. Here are some ideas for different skyglow experiments you could try:
    1. compare different locations (e.g., urban vs. suburban vs. rural),
    2. compare the same location at different times of night,
    3. compare the same location different weather conditions (e.g., clear vs. foggy vs. high clouds vs. heavy clouds),
    4. compare the same location during different seasonal conditions (e.g., snow on the ground vs. not, leaves on trees vs. not, Milky Way visible vs. not).

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Variations

  • For a much more basic experiment on light pollution, see the Science Buddies project Where Did All the Stars Go?
  • If you are located on the outskirts of an urban center, you may find that the skyglow in your area is much stronger in one direction than another. How does skyglow change in different parts of the sky? How does skyglow change with angle from the horizon? A tripod with a pan-tilt head that has marked angles is required for this variation.
  • Advanced. The gray scale calibration covered in this project established the dynamic range for your digital camera. However, you still don't know where that dynamic range falls in terms of absolute light levels. The Sky & Telescope article by Tony Flanders describes a method for calibrating the camera using photographs of stars of known magnitudes (Flanders, 2006). If you know the night sky well enough to identify some constellations and individual stars, you might be interested in trying this. You'll need to get a copy of the Flanders article, and study especially the section under the heading, "Calibration."
  • Super advanced. "Starlight, airglow, scattered moonlight and various kinds of artificial lights have different spectral signatures. It should be possible to tease out a huge amount of information about those by comparing the readings of the red, green, and blue pixels. Anybody interested in the challenge?" (Flanders, 2006) Can you use spectral information from your camera (i.e., red, green, and blue values) to identify the source of the skyglow?

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