The scientists at CINCIA, based in the Madre de Dios region of Peru, have developed a new data fusion method to identify areas destroyed by this small- or artisanal-scale mining. Combining existing CLASlite forest monitoring technology and Global Forest Change data sets on forest loss, this new deforestation detection tool is 20-25 percent more accurate than those used previously.

Both CLASlite and the Global Forest map use different kinds of information from light waves to show changes in the landscape. “Combining the two methods gives us really good information about the specific kind of deforestation we’re looking for,” said Miles Silman, associate director of science for CINCIA and director of Wake Forest’s Center for Energy, Environment, and Sustainability (CEES). Silman has researched biodiversity and ecology in the Western Amazon and Andes for more than 25 years.

Artisanal-scale gold mining has been hard to detect because its aftereffects can masquerade as natural wetlands from a satellite view. But the damage is extensive. Small crews of artisanal miners don’t expect to hit the mother lode. Rather, miners set out to collect the flakes of gold in rainforest.

“We’re not talking about huge gold veins here,” Fernandez said. “But there’s enough gold in the landscape to make a great deal of money in a struggling economy. You just have to destroy an immense amount of land to get it.”

To get the gold, they strip the land of trees or suck up river sediment, and then use toxic mercury to tease the precious metal out of the dirt. The results are environmentally catastrophic.