Light pollution and sky glow: [Essay Example], 503 words GradesFixer

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Light pollution and sky glow

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  1. Set up a piece of white paper so that it is equally illuminated by indirect natural light. Choose a place where the light is bright. The most important thing is that the paper is illuminated evenly. Choose a time and place during which it is unlikely there will be any changes in how much light is present.
  2. Set up your digital camera so that the white paper fills the entire field of view. The distance from the camera to the paper is not important.
  3. Put the camera in manual mode and make the following changes:
    • Adjust the focus so that the camera is focused on the white piece of paper. Once you set the focus, do not change it.
    • Set the camera’s sensitivity to ISO 200.
    • Set the aperture to f/2.8.
    • Set the image resolution to a low setting.
    • If your camera has a self-timer feature, set it so that the camera shutter opens a few seconds after you take a picture. This minimizes shake.
  4. Now that your camera is focused on the paper, with the settings adjusted correctly, take a series of photos at different shutter speeds, changing by a factor of 2. (I used: 30, 15, 8, 4, 2, 1, 1/2, 1/4, 1/8, 1/15, 1/30, 1/60, 1/125, 1/250, 1/500, and 1/1,000 sec shutter speeds.)
  5. Repeat step 4. This will give you two sets of calibration photos. You will compare these later in this procedure.
  6. Download all of the calibration photos onto your computer.
  7. Make two data tables in your lab notebook to keep track of the pixel value for each calibration photo. One data table will be for the first set of calibration photos, the other for the second.
  8. Measure the average pixel intensity of each photo using ImageJ.
    • Start ImageJ.
    • Open the first photo using “File/Open”… command.
    • Click on “Analyze” and select “Histogram”.
    • A histogram of the pixel values in the photo will open in its own window. You will use the histogram to measure the average pixel gray value in each photo.
    • Record the Mean, StDev, Min, Max, and Mode in your data tables. StDev is short for “standard deviation”. Min and Max are short for minimum and maximum, respectively. Mean is another name for the average. The mean of this histogram is the average pixel value.
    • Click on “File” and select “Open Next” to open the next file.

    Repeat steps 3.d.–3.f. until you have analyzed all images in both sets of calibration photos.

  9. Make a calibration curve by graphing the average pixel value (the mean of the histogram) on the x-axis and exposure time (in seconds) on the y-axis. Your graph will have two data series, one for each set of calibration photos.
    • This is a “semi-log” plot.
  10. Look at your graph and check the calibration curves from each set. The two curves should cross or only be a little bit apart. If there is a large amount of space between the two calibration curves or if one of the curves has a drastically different shape from the other, you will need to repeat steps the whole process, making sure that the lighting conditions are the same for both sets.

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