File:SIR-C X-SAR Raco, Michigan collage.jpg

English: (Left: P-43882; top right: P-43922; bottom right: P-43923)

At left is a false-color composite of the Raco, Michigan area, centered around 46 degrees north latitude and 85 degrees west longitude. Acquired by SIR-C/X-SAR on April 9, 1994, during the 6th orbit of the space shuttle Endeavour (STS-59), the image has been used by science team members at the University of Michigan to produce detailed maps of land cover in Raco. Accurate information about land cover is important for area resource management and for scientific models used to understand global change.

The area shown is approximately 24 by 40 kilometers (15 by 25 miles). Located at the eastern end of Michigan's upper peninsula, at the boundary between boreal and northern temperate forests, Raco occupies a transitional zone that may be ecologically sensitive to possible global changes resulting from climatic warming. In the image, darker areas represent smooth surfaces such as frozen lakes or other unforested areas. Colors relate to the types of trees; brightness relates to the amount of plant material (forest biomass) covering the surface. The black area in the upper right corner is an ice-covered part of Lake Superior.

At top right is a vegetation map of Raco. Each 30- by 30-meter (98- by 98-foot) spot is identified as water surface and bare ground (clear), short vegetation (red), deciduous forest (yellow), lowland conifer (blue), or upland conifer (green). The different types of ground cover have varying effects on chemical, water, and energy cycles. By cataloging ground cover in a specific region, scientists expect to better understand the processes of these cycles in that region.

At bottom right is a biomass map of Raco. Areas with little or no vegetation are shown as red, while areas with dense vegetation are shown as blue. Seasonal growth of terrestrial plants, and forests in particular, leads to temporary storage of large amounts of carbon that could directly affect changes in global climate. To accurately predict global change, scientists need details about the distribution of vegetation types and the amount of biomass around the globe. While optical techniques to determine biomass can be limited by chronic cloud cover, SIR-C/X-SAR can penetrate through cloud cover with little signal loss.