Going Further

Variations

This study can also be carried out without computers and digital image processing techniques.

Download and print the following PDF files, showing the SAR images of the study area from 1994, 1995 and 1996:
PDF version of 1994 image (Acrobat (PDF) 603kB Dec25 09)
PDF version of 1995 image (Acrobat (PDF) 598kB Dec25 09)
PDF version of 1996 image (Acrobat (PDF) 593kB Dec25 09)


Download and print three copies of the following graph sheets on transparency sheets:
Graph sheet paper - 1 km (Acrobat (PDF) 5kB Dec25 09)
Graph sheet paper - 2 km (Acrobat (PDF) 5kB Dec25 09)
Remember that the size of the grid is an approximation.


Overlay the 2 km graph sheets on each of the SAR images. Use the differences in tone (shades of grey) on the image for visual interpretation. Deforested areas appear as very dark tones on the SAR images. Use a marker pen to color all grid cells on the transparency that correspond to deforested areas (if a grid cell is covered more than half by dark shades then count it as deforested). Count the number of grid cells that are deforested and calculate the total area (remember each grid cell is 2 km x 2 km representing an area of 4 sq km). Repeat this process for all three dates. Estimate the percentage of deforested area for each year. Report the increase in deforestation.

Refine your estimate by using the 1 km graph sheets, following the same procedure as outlined above.

Discuss:

  • What are the problems you encounter while making a visual analysis?
  • What are the problems you encounter using the graph sheets?
  • Why do the results vary when you use different size grid cells in graph sheets?
  • What are the advantages and disadvantages of using a finer scale graph sheet?
  • Compare your results with your friends' results. Do they vary? If yes, explain the reasons for the differences.


Other data

For studying deforestation in the Amazon rainforest using Landsat satellite images, visit the NASA Earth Observatory.

To see another related study "Deforestation in Tierras Bajas, Bolivia" using a different data set visit the NASA Earth Observatory.


Related Case Studies

Other EET chapters that utilize ImageJ as a tool and satellite imagery as a data source include the following:

Annotating Change in Satellite Images—Use time-series images to produce a map documenting landuse changes in China.

Analyzing the Antarctic Ozone Hole—Measure and graph the area of depleted ozone from Total Ozone Mapping Spectrometer (TOMS) images.

Measuring Distance and Area in Satellite Images—Use ImageJ to quantify change over time in satellite images.

Using NASA NEO and ImageJ to Explore the Role of Snow Cover in Shaping Climate—Use ImageJ to explore and animate satellite images of land surface temperature, snow cover, and reflected shortwave radiation downloaded from the NASA Earth Observation (NEO) Web site. Then use NEO's Image Composite Editor (ICE) to observe, graph, and analyze the relationship between these three variables.

Whither Arctic Sea Ice?—Animate thirty years of sea ice images, measure the ice extent each year, and then graph and analyze the results.


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