PART I: Collecting data from National Earth Observations

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1 Investigation: Air Pollution In this investigation, you are going to explore air pollution around the world for an entire calendar year. We will be using three tools, the National Earth Observations (NEO) Database, ImageJ, and Google Earth to aide in our studies. PART I: Collecting data from National Earth Observations 1. Launch the following website: 2. Cick on the Atmosphere tab under the blue marble image of the Earth. 3. Choose the following Dataset: Aerosol Optical Thickness You may pick either the TERRA/MODIS Satellite or AQUA/MODIS Satellite. They have different orbital patterns. The data from both of these satellites goes back to Pick a year, and then choose a month to View. In the end you will have one twelve month time period. 5. Create a folder for your images from this investigation on your H-Drive called LastNameAOTyear (example: BuggeAOT2003) then download the image to your folder (select the 0.5 degrees option). You will want to rename the file ##MonthYear.jpg (example: 03March10.jpg) 6. Repeat for eleven other months. 7. What color represents the highest aerosol concentrations? What color represents the lowest aerosol concentrations? 8. Once you have these twelve images, launch ImageJ.

2 PART II: Introduction to ImageJ ImageJ can display two or more images in a single window, as a stack. The images or layers that make up a stack are called slices. Stack windows have a scroll bar across the bottom to cycle through the slices, and you can animate the images at speeds from one frame every 10 seconds to over 1000 frames per second. To stack a set of images, they must all be the same width, height, and bit depth. The number and size of the images you can stack depend on the amount of memory in your computer. What are stacks used for? Stacks are used to display and analyze images that relate to each other in some way, such as by time (temporal), space (spatial), or color (spectral). Stacking temporal images allows you to animate them to rapidly display them in sequence making changes over time easier to see and understand, and allowing you to precisely measure the same regions of the image over time. Creating a Time-Series Stack with ImageJ 1. Choose File > Import > Image Sequence and navigate to the LastNameAOTyear folder where you stored the monthly images. 2. Select the folder then click the Open button.

3 3. Specify the Sequence Options. Use all twelve slices, beginning with the first slice and incrementing by one. Do not scale the images. Check the Sort Names Numerically option and click OK 4. All twelve images will be imported into a stack named LastNameAOTyear. The individual images in a stack are called slices in ImageJ. The window s status bar shows the number of the current slice and total slices (in this case 1/12 or 1 of 12), the width and height of the image in pixels, and the memory occupied by the stack, in this case 12 MB. 5. Choose File > Save to save the stack as LastNameAOTyear.tif The Aerosol Optical Thickness images are now assembled into a stack.

4 Animate the Stack You can step through a stack one slice at a time, or you can animate it like a repeating movie look. ImageJ lets you control the speed to the animation, so you can show it at a speed that is best suited for viewing. 1. Click and drag the scroll bar at the bottom of the stack widow to move forward and backward through the stack. As you scroll through the stack, notice the changing slice counter and image label at the top of the stack window. Slice 1 is labeled 1/12, slice 2 2/12, and so on. 2. You can also use Next Slice (>) and Previous Slice (<) keyboard shortcuts to move forward and backward through the stack. Try each method of scrolling before moving on. 3. Choose Image > Stacks > Tools > Start Animation to animate the stack. 4. The animation is probably going too fast to see what s going on. To slow it down, choose Image > Stacks >Tools > Animation Options

5 5. Set the Speed to 5 frames per second, and click OK. 6. Experiment with changing the speed of the animation, carefully observing the Aerosol Optical Thickness changes that occur during the year. What do you observe happen to the concentration of aerosols as the seasons change? Which seasons have the largest concentrations? Which countries have the largest concentrations? How is the Aerosol Optical Thickness for the eastern United States? Does this make sense to you? Record your observations. 7. When you are satisfied with your animation, go to Image > Type > 8-Bit Color to convert the images for animation. 8. When you are satisfied with your animation, go File > Save As to save the images as LastNameAOTyear.gif in your folder. The Aerosol Optical Thickness images have been converted to 8-bit color. The Aerosol Optical Thickness images are now saved as an animated gif.

6 Create a Montage from a Stack Stacks are great on your computer screen, but how do you represent the image series in a printed report? The solution is to create a montage rows and columns of thumbnail images on a single page to save and import into your report. 1. Choose Image > Stacks > Make Montage 2. Experiment with the various options in the Make Montage window to discover how each option affects the montage image. Make sure you scale to at least 0.50 and label the slices.

7 3. Here is what a montage should look like. 4. When you have a montage you are satisfied with, go File > Save to save the Montage as LastNameAOTyearMontage.tif in your share folder. PART III: Try it yourself! 1. Once you have recorded some observations, you are ready to try and create stacks for yourself. Return to the Atmosphere category in NEO and pick another aspect of the atmosphere that AQUA and TERRA explore. a. Choose from: Water Vapor, Carbon Monoxide, or Aerosol Particle Radius. b. Create a new folder: LastNameDataSetYear (example: BuggeWV2003) and save all 12 images here. c. Follow the direction in part 2 to create a stack and a montage. Save them to your folder. 2. Post your stack and montage to your blog as a new entry. 3. Along with the images explain: a. The purpose of this data set b. What the colors mean c. Any observations you make/patterns you see and connections to what we have learned so far about air quality.

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