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Case Study: Losing the Rainforest, One Tree at a Time Synthetic Aperture Radar (SAR) satellite images are used to study change in the Amazon rainforest.

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Presentation on theme: "Case Study: Losing the Rainforest, One Tree at a Time Synthetic Aperture Radar (SAR) satellite images are used to study change in the Amazon rainforest."— Presentation transcript:

1 Case Study: Losing the Rainforest, One Tree at a Time Synthetic Aperture Radar (SAR) satellite images are used to study change in the Amazon rainforest.

2 There are three great reasons for using SAR images to look at the rainforest. 1.The rainforest is a cloudy place! Regular cameras cannot take a picture through clouds, but SAR can see right through those clouds – clouds are invisible to SAR. 2.The rainforest is huge! If you were to visit the rainforest in person it would seem endless. So we need to study the "big picture" to tell what changes have occurred, and satellite images give us the biggest picture of all. 3.Third, satellite images are taken of exactly the same places each time the satellite circles the Earth, so images from different years match up. Users compare SAR images of the exact same area from three different years to measure how much forest area was lost from a part of the Amazon rainforest between 1994 and 1996.

3 Change over time 1.Consider this: Using this technique measures how much forest was lost in just three years. People have been cutting rainforest trees for a long time, with no sign of stopping. What do you think that means for the forest?

4 Rainforest Plants courtesy of National Biological Information Infrastructure (NBII) Library of Images from the Environment

5 Clearing the Rainforest with a machete, courtesy of National Biological Information Infrastructure (NBII) Library of Images from the Environment

6 The roads, the dark bands, are cutting across the forest like the tributaries of a river.

7 1/3 in the upper left corner of the stack. This indicates that you are looking at the first of three images in a stack.

8 Use Image > Color > Stack to RGB to create an RGB (red, green, blue) color composite image from the stack.

9 The color composite image should look like this.

10 Interpret results

11 Given how primary colors add together, what is your interpretation of what the colors mean on the color composite image? Black means that these areas are dark on all the three images. Thus, black represents areas that are forested in 1994, 1995, and 1996. White means that these areas are bright on all the three images. Thus, white represents roads that were developed prior to 1994 and that continued to exist through 1996 and possibly beyond. Cyan, which is a combination of green and blue, represents areas that were dark (forested) in 1994, but were cleared between the time the 1994 and 1995 images were acquired. These areas are bright in 1995 and were assigned to the green channel and are also bright in 1996 and were assigned to the blue channel. Therefore, these areas show up as cyan in the color composite image. Blue shows us the most recently deforested areas. Because the 1996 image was assigned to the blue channel, blue in the color composite image shows areas where deforestation took place after the 1995 image was acquired.


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