Woods Hole Research Center debuts new image mosaic that will strengthen global forest ...( Much of the discussion at the upcomi...)

Much of the discussion at the upcoming United Nations Climate Change Conference in Bali, Indonesia, will focus on monitoring tropical deforestation and the critical role that remote sensing systems will play in the development of REDD (Reduced Emissions from Deforestation and Degradation) mechanisms policies designed to compensate rainforest nations for avoiding deforestation. Using synthetic aperture radar (SAR) data acquired over a six-week period by the Japanese Advanced Land Observing Satellite (ALOS), scientists at the Woods Hole Research Center have just completed the first-of-its-kind, large-scale, wall-to-wall image mosaic at 25 m resolution for a portion of the Amazon basin spanning some 400,000 square kilometers. Images acquired globally over narrow timeframes provide for true snapshots of deforestation activities, giving leverage to monitoring programs that hinge on timely and accurate observations of forests throughout the world.

Dr. Josef Kellndorfer, who is leading the project for the Center, says, The Japanese Space Agency JAXA has launched an amazing sensor which exhibits unprecedented geometric and radiometric accuracies allowing us to generate high quality cloud free radar image mosaics with nearly no user interaction required. The ALOS observation plan will ensure, that these high-resolution data are acquired several times per year for years to come. With a strong sensitivity of the ALOS radar imaging sensor to vegetation structure, this marks a new era in remote sensing of natural resources.

The image mosaic is a composite of 116 individual scenes acquired by the Phased Array L-Band SAR (PALSAR) carried on board ALOS. The acquisition was made over the Xingu basin in Mato Grosso, Brazil, between June 8 and July 22, 2007. From the mosaic, Dr. Kellndorfers group has generated a preliminary land cover classification with emphasis on producing an accurate forest/nonforest map. In the forested areas, the sensitivit
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