Cryptic deforestation

Desforestación amazónica (Fuente: J. C. Winnie)

While clear-cuts and burn-offs are readily detectable by conventional satellite analysis, selective logging is masked by the Amazon's extremely dense forest canopy. "We've been working for eight years to develop analytical techniques that can detect this very cryptic form of deforestation," Asner says. "Using satellite data, we developed a model that detects the physical changes to the forest. We started to have success about three years ago at a scale of about 200 hundred square miles. This was the first solid, quantitative detection of logging-related damage to forest canopies."

By late 2004, the research team had refined its technique into a sophisticated remote-sensing technology called the Carnegie Landsat Analysis System (CLAS), which processes data from three NASA satellites—Landsat 7, Terra and Earth Observing 1—through a powerful supercomputer equipped with new pattern-recognition approaches designed by Asner and his staff.

"Each pixel of information obtained by the satellites contains detailed spectral data about the forest," Asner explains. "For example, the signals tell us how much green vegetation is in the canopy, how much dead material is on the forest floor and how much bare soil there is. Extracting those data has been a Holy Grail of remote sensing. With CLAS, we've been able to obtain a spatial resolution of 98 feet by 98 feet for the Brazilian Amazon Basin. That's huge."