Forest Cover Loss 2000-2012 in Colorado, Oklahoma, and Saskatechewan

  • Released Wednesday, September 10, 2014
  • Updated Thursday, March 29, 2018 at 8:22AM
  • ID: 4209

This visualization shows the cumulative forest cover loss from 2000 through 2012 for Colorado, Oklahoma, and Saskatechewan. The movie starts with a view of the United States using landsat data showing tree cover data. Then, the movie zooms into Colorado where forest loss from 2000 through 2001 is highlighted. Next, the cumulative loss from 2000 through 2002 is displayed with the most recent loss shown in bright red. The frame sequence continues to show the total cumulative loss from 2000 through 2012 with the latest loss in bright red and the earlier loss in yellows and greys.

Next the camera zooms into Oklahoma to see the cumulative forest cover loss from 2000 through 2012 in that region. Finally the camera goes to Saskatchewan, Canada to see the forest cover loss in that region between 2000 and 2012.

Twelve years of global deforestation, wildfires, windstorms, insect infestations, and more are captured in a new set of forest disturbance maps created from billions of pixels acquired by the imager on the NASA-USGS Landsat 7 satellite. The maps are the first to measure forest loss and gain using a consistent method around the globe at high spatial resolution, allowing scientists to compare forest changes in different countries and to monitor annual deforestation. Since each pixel in a Landsat image represents a piece of land about the size of a baseball diamond, researchers can see enough detail to tell local, regional and global stories.

Hansen and colleagues analyzed 143 billion pixels in 654,000 Landsat images to compile maps of forest loss and gain between 2000 and 2012. During that period, 888,000 square miles (2.3 million square kilometers) of forest was lost, and 308,900 square miles (0.8 million square kilometers) regrew. The researchers, including scientists from the University of Maryland, Google, the State University of New York, Woods Hole Research Center, the U.S. Geological Survey and South Dakota State University, published their work in the Nov. 15, 2013, issue of the journal Science.

Key to the project was collaboration with team members from Google Earth Engine, who reproduced in the Google Cloud the models developed at the University of Maryland for processing and characterizing the Landsat data; Google Earth Engine contains a complete copy of the Landsat record. The computing required to generate these maps would have taken 15 years on a single desktop computer, but with cloud computing was performed in a few days.

Since 1972, the Landsat program has played a critical role in monitoring, understanding and managing the resources needed to sustain human life such as food, water and forests. Landsat 8 launched Feb. 11, 2013, and is jointly managed by NASA and USGS to continue the 40-plus years of Earth observations.

To view the forest cover maps in Google Earth Engine, visit: http://earthenginepartners.appspot.com/google.com/science-2013-global-forest
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Forest Cover Loss History Colorbar

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Wildfires in the western United States are increasing in frequency and duration, accompanying a growing season that is 18-21 days longer since 1900.

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This image showing the forest loss history in Oklahoma where trees are crops. The area around the reservoir is protected so it is not logged like the surrounding region.

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Saskatchewan forest loss comes from many causes including, harvest, fires and insect damage.

This is the same frame sequence as the above sequence without the date or colorbar overlay.

This sequence has the burned in date, but no colorbar.

This is the date frame sequence alone.

Credits

Please give credit for this item to:
NASA's Goddard Space Flight Center, using data from Hansen, Potapov, Moore, Hancher, et al., Science Nov. 15, 2013.High-Resolution Global Maps of 21st-Century Forest Cover Change. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Missions

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Datasets used in this visualization

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