"The study of bird habitats has entered a new era," said Goetz. "Until recently, predicting bird habitat was limited. We've known for many years that the composition of trees and shrubs determines habitat quality, which in turn influences a species' presence and population density. But this study uses remote sensing to accurately predict which habitats birds prefer to use year after year, over many square miles of complex terrain."
According to Goetz, NASA's Laser Vegetation Imaging Sensor (LVIS, pronounced Elvis), was key to the team's success. The instrument sends pulses of laser light down from an airplane toward the forest canopy and records the points at which signals bounce back from leaves, branches, and land surfaces. Goetz and colleagues analyzed the data to confirm things like canopy height the difference between the top of a tree and the ground and the top-to-bottom density of tree canopies.
"We're doing the same thing our predecessors did, but in much more detail and over a much broader area," said Betts. "We have new metrics now that just weren't possible before."
When combined with data from the NASA-built Landsat satellite which can indicate seasonal changes in the amount of vegetation -- the LVIS data indicated not only the height of the trees but whether they have mostly high branches or lots of canopy layers beneath tree tops.
For the study published this month, the team made field observations of the Black-throated Blue Warbler, a small songbird that prefers lower-lying vegetation. Using four years of LVIS data, the researchers ranked various forest habitats as good, fair, or poor based on canopy structure. Their "good" rankings for the warbler matched actual ground data -- showing the actual presence of the species in each habitat -- 90 percent of the time.
"For predicting species across
|Contact: Sarah DeWitt|
NASA/Goddard Space Flight Center