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Working with a Broader Spectrum of Light John Pickle, Don Blair, Mort Sternheim Student Guide, June 2013 Objectives: Explore the Visible and Near Infrared spectrum with modified digital cameras. Use ADI tools to create useful images. Overview: Infrared Light (from http://dew.globalsystemsscience.org/key-messages/near-infrared- and-the-electromagnetic-spectrum ) Wavelength bands within the visible spectrum are defined by color. The range of wavelengths that span the infrared spectrum is roughly 40 times greater than that of the visible spectrum. Because the infrared region is so large, there is quite a bit of confusion when one uses the term "infrared" or IR. Technologies that deal with the near infrared, which is quite close to the red visible spectrum and quite far from the thermal infrared wavelengths, which is commonly referred to as "heat." Although our bodies do emit IR, the wavelengths are in the far or thermal IR region. The IR detected with digital cameras and light emitting diodes (LEDs) in TV remote controls is in the near IR region, which is generated from very hot light sources. All objects emit light, but cooler objects emit light of longer wavelengths. Hotter bodies emit light of shorter wavelengths. For example, blue stars are hotter than red stars (blue is a shorter wavelength than red). The wavelength corresponding to the maximum emission is inversely proportional to the absolute or Working with a Broader Spectrum Page 1

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Page 1: Working with a Broader Spectrum_dwbedit.doc.docxumassk12.net/.../Summer2013/john/WorkingwithaBroa… · Web viewWorking with a Broader Spectrum of Light John Pickle, Don Blair, Mort

Working with a Broader Spectrum of LightJohn Pickle, Don Blair, Mort Sternheim

Student Guide, June 2013

Objectives:

● Explore the Visible and Near Infrared spectrum with modified digital cameras.

● Use ADI tools to create useful images.

Overview: Infrared Light (from http://dew.globalsystemsscience.org/key-messages/near-infrared-and-the-electromagnetic-spectrum)

Wavelength bands within the visible spectrum are defined by color. The range of wavelengths that span the infrared spectrum is roughly 40 times greater than that of the visible spectrum. Because the infrared region is so large, there is quite a bit of confusion when one uses the term "infrared" or IR. Technologies that deal with the near infrared, which is quite close to the red visible spectrum and quite far from the thermal infrared wavelengths, which is commonly referred to as "heat."

Although our bodies do emit IR, the wavelengths are in the far or thermal IR region. The IR detected with digital cameras and light emitting diodes (LEDs) in TV remote controls is in the near IR region, which is generated from very hot light sources. All objects emit light, but cooler objects emit light of longer wavelengths. Hotter bodies emit light of shorter wavelengths. For example, blue stars are hotter than red stars (blue is a shorter wavelength than red). The wavelength corresponding to the maximum emission is inversely proportional to the absolute or Kelvin temperature. The sun is at 6000 K, while our bodies are at about 300 K.

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Overview: Sensing Light with a Digital Camera (from http://dew.globalsystemsscience.org/tools/digital-cameras-overview)

Near infrared doesn't make it to the camera sensor because it is blocked by the infrared-blocking filter, which lets the visible light through.

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The visible light reaching the sensor is controlled by small color filters. The red filter lets red light through, so only this light is hitting the small sensor underneath it. Similarly, the green and blue filters control the wavelengths of light reaching the sensors beneath them.

Effect of Removing the Near Infrared Filter from a Digital Camera:

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Activities:

Step 1: Observe your world using the book of filters and the infrared goggles. Record your observations.

Step 2: Observe your world with a digital camera that sees in both the visible and near infrared.

First, connect your USB camera to your computer and open Google Chrome. Use the filters and the infrared goggles to take photos with your camera.

Examples: Visible light only, with proper balance of red, green, and blue light.

Visible and near infrared light are reaching the camera sensor.

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Only the near infrared light is reaching the camera sensor. The color is caused by the three sets of small colored filters inside the camera letting different amounts of near infrared through. The reddish tint suggests that the red filters pass greater amounts of infrared than the other two, with the blue filter letting more through than the green, as indicated by the purplish tint to the sky.

Only the near infrared light is reaching the camera sensor. The color tinting caused by the colored filters letting different amounts of infrared through has been removed with the ADI software.

Step 3: Expanding on Mort's Albedo analysis. Now we are going to expand to include visible and near-infrared light (which are each nearly 50% of the sun's spectrum). Take photos of the same location (preferably one with grass, dirt, and pavement in the scene) using the WebCam Toy plug-in while running Google Chrome using the infrared goggles or the exposed film, the blue filter (handed out), and the infrared-blocking filter (we only have a few, so these need to be shared). Tip 1: place your camera in such a way as it won't move when photographing a scene. Tip 2: As with the earlier experiment, try to have 50% of the scene covered by the white copy paper. Suggestion: Include a fake/plastic plant in your scene.

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Step 4: Using ADI and either the line or area tools, repeat the calculation of albedo of each surface/land cover in the photographs. Assume the paper's albedo in visible and near-infrared is 0.6. How did the values change compared to only visible light? Consider the effects on Earth's energy budge.

Step 5: Using ADI, create a Red vs. Blue (normalized) image of the photo that used the blue filter. Save the image using the option in the File Menu, Save Picture.

Step 6: Using ADI, create a Red vs. Blue (normalized) image of the photo that used the infrared-blocking filter. Save the image using the option in the File Menu, Save Picture.

Step 7:

A) Using ADI, create an average gray-scale image of the photo that used the infrared goggles or the exposed film. Save the image using the option in the File Menu, Save Picture.

B) Using the photo the used the infrared-blocking filter, save the enhanced image created using Red as Gray.

C) Use the Utilities option, Combine Images, to add the Near-IR image (step A) to the red layer, and add the Red as Gray image to the Blue layer. Use this combined image to create a Red vs. Blue (normalized) image and save.

Step 8: Compare the 3 images created using Red vs. Blue (normalized). Note: Steps 5-8 are research, so we don't know the final results! Two of these images, the ones that include near-infrared, are called Normalized Difference Vegetation Index, or NDVI.

Applications: Assessing the Health of Plants

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, 06/25/13,
Don Blair:Added in this graphic -- might be useful by way of explaining NDVI
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Arrow width of the spectra above are proportional to the amount reflected from a healthy leaf. Image: publiclab.org

NGB = Near Infrared intensity measurements shown in the Red layer, Green intensity measurements displayed as Green, and Blue intensity measurements are shown in the Blue layer. NDVI image uses a different enhancement than what we will create with ADI. Image: publiclab.org

For more information about NDVI, see:

- Public Lab’s DIY near-infrared camera designs and background information on NDVI: http://publiclab.org/wiki/near-infrared-camera

- A list of inexpensive digital cameras that are easy to modify for near-IR imagery: http://publiclab.org/wiki/near-infrared-camera

- Lawrence Hall of Science’s NDVI guide: http://www.lawrencehallofscience.org/gss/dew/software/guides/NDVIfromDigitalCamera.pdf.

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, 06/25/13,
Don Blair:Added in some description of these links here