Part 5—Explore in ICE the Relationship of AOT and CO

Step 1 " Load Two Datasets into NEO/ICE

We will use the Image Composite Explorer (ICE) of NEO to compare the Aerosol Optical Thickness Data to the Carbon Monoxide Data. It requires Java to run on your computer.

Select datasets for use with this tool from the Atmosphere tab where we downloaded datasets for Parts 2 - 4. A maximum of three datasets may be analyzed in the ICE tool at one time. We will choose to look at a specific date in time, September 2005, for the two datasets AOT and CO.

  1. Go to the NASA Earth Observations (NEO) homepage.
  2. Find the September 2005 Aerosol Optical Thickness data in the NEO by using Next at the bottom of the page. Select it for analysis by clicking (+) to expand it and then by choosing Analyze this image.
  3. Find the Carbon Monoxide (MOPITT) dataset in NEO and select it for analysis.
  4. Choose September 2005, as you did for AOT dataset. Use (+) to expand the options and then click Analyze this image. There should now be two datasets on the right-hand section of the screen. Then click on configure/launch analysis.
    choose the two files config/launch analysis

Step 2 " Launch and Configure for ICE by Choosing an Area of High CO and AOT Values

  1. When the analysis configuration launches a new page, it will display your selected dataset(s) on the left side of this window. Datasets can be added or removed.
  2. Some actions you can take on this page are to select a subset of the image (Select Area), choose an analysis mode, adjust the file size, or download the dataset and the analysis tool for offline analysis.
  3. On this new page, click on the Select Area tab to choose a subset of the world which will decrease the image's file size for purposes of the ICE tool. This is very helpful if your Internet connection is slower. Using the cursor on the map, you can click and drag a box around your area of interest or you can type in the latitude and longitude limits.
  4. Drag a box around the South American area of high CO, which also seems to have high Aerosol Optical Thickness values. Be sure to click the Select button in the Select Area frame. This will cause the tool to load only the data for your area of interest, such as South America, instead of the worldwide dataset.
  5. Click on Launch Analysis.

Step 3 " Use Basic ICE Tools to Explore the Data

In ICE, explore the selected Aerosol Optical Thickness dataset using the Zoom and Pan, Probe, Plot Transect, Distance, Select and Outline Region tools.

  1. Select Probe and then move the cursor over the image to see what the optical depth values for each of the selected (at most 3) ICE datasets are for the pixel and the location of that pixel. Note that "no data" pixels are represented by "---". No data can occur because of continuous coverage by clouds of that area or the inability of the algorithm to compute a data value with the information available. Select the Probe again to turn the data value display off.
  2. To use the zoom and pan feature, click Zoom & Roam and then click in the image to zoom in. Continue to click within the image to zoom in further. You can right click (or command-click on the Mac) to zoom out.
  3. The Plot transect tool is used to graph the data for a select line. Select Plot transect and hold down the mouse and drag a line across an area of interest, releasing the mouse button at the line's end.
  4. To measure the distance on the image for the length of the line, select Distance and hold down the mouse and drag across the image. The measurement is in units of kilometers.
  5. To outline (trace) a non-rectangular area in the image, select Outline region.. Do this by holding down the mouse as you move the cursor around the desired area. As with Select region, the area inside the outline and the average optical thickness are displayed on the map.

Step 4 " Compare Histograms and Scatter Plots

  1. Launch Analysis from the configuration page. A new page will display with your images at the top. The analysis tools are along the right as buttons and check boxes.
  2. When you click on the Probe button and move your cursor across the image, the values of both datasets and a location are displayed.
  3. You can display either image, AOT or CO. Click on the thumbnail to switch between them.
  4. Next, choose Select region and trace the area of highest AOT (or CO) values.
  5. Click back and forth between the two images to see how well the outline fits high values in both datasets.
  6. Choose the Select region or Outline region tool.
  7. Select Histogram. The plot (y values) are the number of pixel values which fall in a range of limits on the two color-coded x axes labeled for each dataset.
  8. Choose the Scatter button which plots the AOT on one axis and the CO on the other axis.

Step 5 - Reflect on the Data Relationships

Here are some things to notice about the scatter and histogram plots of this area for September 2005.

  1. The values in the scatter plot seem to cluster in the upper right quadrant, which means that when one of these parameters is high, so is the other. They vary directly. If you select a region that has a range of color, you can see at a glance on the scatter plot the range of values for each dataset quickly.
  2. The histogram shows that the two datasets AOT and CO generally agree that the highest number of pixels within the outline drawn on the image have the highest values of aerosol particulates and highest carbon monoxide (in ppb).
  3. Since you looked at the animation stack files for AOT and CO, you should compare some monthly data on fires globally to them. Here is a MODIS Fire Data stack (TIFF 8.9MB Jun30 10) for 2008 you can animate in ImageJ. This stack is called fire2008.tif. Load it into ImageJ and combine with each of the stacks to notice any patterns.

Where and When are the Fires Happening?

There are several possibilities to explain the occurrence, location and severity of the fires:

  • land being cleared for agriculture
  • natural weather patterns that bring electrical storms that start fires in remote forests where it is hard to reach with fire crews
  • strong winds that come seasonally and spread fires quickly

Look at specific areas and time frames, like the September 2005 data, to narrow the search for evidence that explains dense clouds of data points with high values. There are some links to articles in the Teaching Notes that can help you with this September 2005 analysis.