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Tora Johnson & Michael Lachance University of Maine at Machias Remote Sensing & Image Analysis Tutorial Land Cover Change Analysis with ArcGIS 10 Maine is the nation’s largest producer of wild blueberries, and blueberry farms, called barrens, are common in Downeast Maine where the thin, acidic soil is especially suited to this crop. In recent years, the price of blueberries has risen, prompting farmers to clear additional land for blueberry production. Also, many farmers are removing rocks and flattening their barrens to allow for machine harvesting as migrant labor has become more scarce. They are installing below-ground irrigation systems to help manage the barrens with automated watering for increased yields. These changes in the types and extent of blueberry culture in Maine have prompted several questions that may be addressed with remote sensing. First, blueberry culture near waterways can negatively impact water quality with erosion, removal of shade trees, and run-off of pesticides. Such damage can be particularly problematic for the area’s rare and endangered fish populations and coastal shellfish areas. Also, because blueberries account for a sizable portion of the area’s economy, economists and agricultural scientists predict annual yield and advise growers and buyers on pricing. Remote sensing can help us see not only the extent and type of blueberry culture but also how it is changing over time. This allows for better management, pricing and planning for the future of the industry and the region. In this exercise, you will use Landsat data for Downeast Maine to look for changes in vegetation cover over a four year period. The scenes for this exercise have already been downloaded for you in the data package that comes with this module, along with a shapefile defining the study area and a model to use in ArcMap for preprocessing.Prepare for this exercise by reading “How are satellite images different from photographs?” The tutorial folder contains a PDF version (compositor_pf.pdf), or you may access it online at http://landsat.gsfc.nasa.gov/education/compositor/index.html. This reading explains how the Landsat satellite takes photographs of land features that may be invisible to the human eye. It also discusses the concept of band combinations, a method we can use to reveal these hidden features in the landscape. 1. First you will add the 1999 Landsat image to your map. Start by opening a new document in ArcMap. Click the Catalog tab on the right side of the ArcMap window. In the Catalog window, click the Connect to Folder button. Navigate to the RS_Workshop folder and select it. Click OK. The 1999 and 2008 folders should now be visible in the Catalog window. Double click the 1999 folder to open it, then drag the layer called “L7_09_27_1999_subset” to the Table of Contents. 2. Now you will add the 2008 Landsat image. In the Catalog window, click the Location pull-down menu, and select the

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Page 1: Remote Sensing & Image Analysis Tutorial Land Cover Change …€¦ · problematic for the area’s rare and endangered fish populations and coastal shellfish areas. Also, because

Tora Johnson & Michael LachanceUniversity of Maine at Machias

Remote Sensing & Image Analysis Tutorial

Land Cover Change Analysis with ArcGIS 10Maine is the nation’s largest producer of wild blueberries, and blueberry farms, called barrens, are common in Downeast Maine where the thin, acidic soil is especially suited to this crop. In recent years, the price of blueberries has risen, prompting farmers to clear additional land for blueberry production.

Also, many farmers are removing rocks and flattening their barrens to allow for machine harvesting as migrant labor has become more scarce. They are installing below-ground irrigation systems to help manage the barrens with automated watering for increased yields.

These changes in the types and extent of blueberry culture in Maine have prompted several questions that may be addressed with remote sensing. First, blueberry culture near waterways can negatively impact water quality with erosion, removal of shade trees, and run-off of pesticides. Such damage can be particularly problematic for the area’s rare and endangered fish populations and coastal shellfish areas. Also, because blueberries account for a sizable portion of the area’s economy, economists and

agricultural scientists predict annual yield and advise growers and buyers on pricing. Remote sensing can help us see not only the extent and type of blueberry culture but also how it is changing over time. This allows for better management, pricing and planning for the future of the industry and the region.

In this exercise, you will use Landsat data for Downeast Maine to look for changes in vegetation cover over a four year period. The scenes for this exercise have already been downloaded for you in the data package that comes with this module, along with a shapefile defining the study area and a model to use in ArcMap for preprocessing.Prepare for this exercise by reading “How are satellite images different from photographs?” The tutorial folder contains a PDF version (compositor_pf.pdf), or you may access it online at http://landsat.gsfc.nasa.gov/education/compositor/index.html. This reading explains how the Landsat satellite takes photographs of land features that may be invisible to the human eye. It also discusses the concept of band combinations, a method we can use to reveal these hidden features in the landscape.

1. First you will add the 1999 Landsat image to your map. Start by opening a new document in ArcMap. Click the Catalog tab on the right side of the ArcMap window. In the Catalog window, click the Connect to Folder button. Navigate to the RS_Workshop folder and select it. Click OK. The 1999 and 2008 folders should now be visible in the Catalog window. Double click the 1999 folder to open it, then drag the layer called “L7_09_27_1999_subset” to the Table of Contents.

2. Now you will add the 2008 Landsat image. In the Catalog window, click the Location pull-down menu, and select the

Page 2: Remote Sensing & Image Analysis Tutorial Land Cover Change …€¦ · problematic for the area’s rare and endangered fish populations and coastal shellfish areas. Also, because

RS_Workshop folder. Double click the 2008 folder, and drag the “L7_09_19_2008_subset” layer to the Table of Contents below the 1999 image, as shown here.

If ArcMap asks you to create pyramids, select Yes if you have copied the workshop data to your hard drive and No if you are working from a CD. The image may appear strange or dark when it is added to your data frame; we'll work with the image to make it look better.

These are Landsat images taken in autumn of 1999 and 2008. Comparing the two images will allow us to see changes between the two time frames.

Hint: When adding images with multiple bands to your map using the Catalog window, be sure to click once on the layer name to highlight the image file. Double clicking on the image will allow you to add the bands separately, in which case you will be unable to make band combinations. If you do double click on the image and see the individual bands listed, simply click the Up One Level button to return to the folder containing the image itself.

3. Now you will symbolize the 1999 image to mimic natural color. Right click the “L7_09_27_1999_subset.tif” layer in the Table of Contents and choose Properties. In the Properties window, click the Symbology tab. In the Band column, use the pull-down menus to change the bands associated with each channel so that Red = 3, Green = 2, and Blue = 1. Make sure the Stretch Type is set to the image to Standard Deviation with n = 2. Your settings should appear as shown below. Click OK to apply the changes and dismiss the Properties window. Notice how this changes the image.

4. Repeat the symbolization process with the “L7_09_19_2008.tif” layer. Turn the top layer on and off by click its check box in the table of contents to view the changes between 1999 and 2008. Use the magnification tools to zoom in and inspect the images more closely.

Check it out! What areas of the image changed the most in that time period? What might have caused the changes?

5. There are many different ways to symbolize these images through the use of band combinations. A band is assigned to each of the red, green, and blue channels of the image, and the color composite of these channels shows details in the landscape pertaining to the three bands that were chosen.

The band combination 3-2-1, with settings as shown above, reveals the image in “natural color.” This combination shows the land much as the human eye would see it from above, using visible wavelengths of light: red, green and blue. Another common band combination is known as “false color,” where the band

Page 3: Remote Sensing & Image Analysis Tutorial Land Cover Change …€¦ · problematic for the area’s rare and endangered fish populations and coastal shellfish areas. Also, because

order is 4-3-2. This combination uses the near-infrared band (band 4) in the red channel. Since green vegetation strongly reflects near-infrared light, lush and healthy vegetation appears as a dark red instead of green; the darker the red the color, the healthier the vegetation. Now you will change the band combination for one of the image files to show the image in false color.

6. Right click on the 1999 image in the Table of Contents and select Properties. Choose the Symbology tab and select. Use the Band drop-down menus to set the red channel to band 4, the near-infrared band. For the green channel, choose band 3, and for the blue channel, choose band 2. Click OK. Repeat this step for the 2008 image, then examine the images to see the result. Remember, vegetation will appear red in a false color image.

Check it out! Common band combinations are documented in the reading accompanying this exercise. You may also try your own combinations and see which features pop out as a result of your choices. Use the Spectral Sensitivity table in the reading to try to figure out why certain features are more prominent as a result of your chosen band combination. Discuss your findings with your partner.

Scientists often use Landsat imagery to analyze and quantify land cover types and changes in land cover over time, and they've developed indices that compute ratios of reflectance among in different bands to discern land cover in any given location. For example, the normalized difference vegetation index (NDVI) is an index based on the relative reflectance of the red (band 3) and near infrared (band 4).

7. Now you will use the Image Analysis tools to calculate NDVI for each of the two time frames. In ArcMap, click the Windows pull-down menu, and choose Image Analysis. In the Image Analysis window, click on the “L7_09_27_1999_subset.tif” layer to select it for analysis. In the Processing pane,

click the NDVI button . A new layer will appear showing the NDVI calculation for the 1999 image. Note that vegetation is shown in green—the darker the green, the more dense the vegetation, and non-vegetated areas are shown in red.

8. Repeat the NDVI process for the 2008 image.

9. Now you will use display tools in the Image Analysis window to explore the data further. First, in the Image Analysis window, click the 2008 NDVI layer. In the

Display pane, click the Swipe button . Then click at the top of the map and drag the cursor down. This will reveal the 1999 NDVI layer beneath the 2008 layer, so you can compare them more easily. Zoom into areas where you see a lot of human activity in the image, and swipe again.

What do you notice? Try the Flicker button to flash between the two layers quickly.

Check it out! Read up on NDVI. This site offers a clear and concise overview of commonly used vegetation indices: http://rst.gsfc.nasa.gov/Sect3/Sect3_4.html

10. Now, you will compute a difference map to clearly show changes in the landscape. In the Image Analysis Window, click the 2008 NDVI layer, hold down your Shift key and click the 1999 NDVI

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layer. Once you have both NDVI layers highlighted, click the Compute Difference button . This will create a layer by calculating the difference in NDVI value for each pixel in the two images. This allows us to easily see and analyze where vegetative cover has changed in the nine years between images.

11. Now, let's symbolize the difference layer to see the changes more clearly. In the Table of Contents, right click the Diff_NDVI layer and choose Properties. In the Symbology tab under Show, select Stretched. Select a color ramp with two distinct colors at the ends, such as the one shown here. Under Stretch Type, select Standard Deviations, and ensure that n = 2. If you are asked whether to compute statistics, click Yes. Click OK and close the Image Analysis window.

Check it out! Take a moment to examine the map by zooming, panning and swiping.Note that areas with significantly less vegetation have negative values and are brown in our example, while areas with significantly more vegetation have positive values and are dark blue. The lighter colors indicate little or no change. New areas have been cleared for blueberry barrens, and associated roads have been built in the area shown between 1999 and 2008. Blueberry barrens that are more vegetated in the 2008 image are most likely being irrigated to increase productivity.

Take it further! Here are some ideas for further study:

Download Landsat data from the GLOVIS website for another area or another time frame. You will need to use ArcMap's Composite Bands tool to create a multispectral layer. Check out the help menu for tips.

This site lists lots of band combinations. Try several and discuss your findings: Band Combinations, Portland State Univ. http://web.pdx.edu/~emch/ip1/bandcombinations.html

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Development of these curriculum materials was funded, in part, by grants from the National Science Foundation Department of Undergraduate Education and the National Aeronautics and Space Administration's Maine Space Grant Consortium. Opinions expressed are not necessarily those of the National Science Foundation or the National Aeronautics and Space Administration.

Natural Color3, 2, 1

False Color4, 3, 2

Normalized Difference Vegetation Index (NDVI)

using bands 3 (red) & band 4 (near infrared)

Difference Map: 1999 to 2008Dark brown is less vegetated, dark blue is more vegetated, & lighter colors show little or no change

1999 2008

Detail of an area with significant change