Forests are notoriously difficult to manage. Trees grow slowly, under the influence of variables ranging from global climate to local soil. Yet invasive species, native pests or catastrophic wildfires can spread lasting destruction within days. With 305.5 million hectares of forest in the U.S. alone, monitoring that much woody real estate has traditionally been largely a guessing game.

A new movement in forest management is trying to change this, coupling satellite images with tree-counting algorithms and other technologies in ways that promise to give foresters, ecologists and lumber companies the lay of the land quickly and more comprehensively. Knowledge of what is growing where is essential for removing invasive species, scheduling sustainable timber harvests or planning fuel-wood thinning to keep forest fires at bay.

Demographic information about tree populations in remote and densely wooded areas has always been particularly hard to come by. Someone had to go to the woods on foot every few years to count and measure a large, representative number of trees by hand.

Those days may be coming to an end. Over the past five years, foresters have begun analyzing large stores of satellite imagery using relatively inexpensive computers and software running on the cloud. One company pioneering this technique is SilviaTerra, a forest analytics firm based in Cambridge, Mass., founded by Max Nova and Zack Parisa. They are among the growing number of foresters more at home in coffee shops than saw mills.

On cloud-networked computers Nova and Parisa use software algorithms they have written to integrate information that more traditional foresters painstakingly gather by hand with data derived from satellite images. Flush green leaves from a stand of oak trees absorb different wavelengths of light—and hence look different in satellite pictures—than do the pine needles of mature hemlocks, for example. By combining these two sources of data, foresters can now dramatically reduce the number of arduous ground measurements that must be taken. Ground measurements are indispensible to this process, as they provide the scaffold on which satellite data can build. (An algorithm cannot tell the difference between pine and oak without good, local measurements of each.) Pushed together, these two data sources “make it 100 to 1,000 times more efficient” to survey forests, Nova says.

Such new techniques also take advantage of the fact that forests growing across a large region do not typically vary terribly much. “A 10,000-acre property might have 100 different forest types in it,” Nova explains. “You blow that up to a half million acres and you still might have only 100 or 150 forest types. When we’re looking at an entire landscape we can ask, ‘Did we measure that shade of green somewhere else?’” If they find a matching shade of green elsewhere on the map, their algorithm simply plugs tree cover data from that region into the new location. This approach has enabled Nova and Parisa to survey several million hectares of U.S. forest in just a few years. In that same time they would have struggled to cover a mere 20,000 hectares using conventional means.

These techniques can determine not just the type of tree but also its size. “We get longer-wavelength images that scatter more on bigger or denser trees,” Parisa says. That is useful information to SilviaTerra’s main clients: companies that buy or invest in timber who want to know where the largest reserves may be. Currently such companies own forested lands worth as much as $90 billion. Based on interest in the market, analysts say these companies could soon double their landholdings.

Parisa and Nova are not the only ones approaching the forest data problem this way. Companies are doing similar work in Canada, Israel and Ireland as well as in other parts of the U.S. “Ten years from now there’s going to be amazing information available for forests anywhere you want to point your mouse on a computer or anywhere you want to walk,” Parisa remarks.

This new technology could be a blessing to forest landowners and managers who will soon be able to better track their land’s response to climate change or spot invasive species sooner.

Of course there will likely always be traditional foresters like Shane Hetzler who provide data from the field to complement data harvested from satellite images. Hetzler, who works for small landowners in coastal New England, prefers the conventional means of studying forests. He hasn’t completely forsaken new technology, however. Hetzler uses smartphone apps to log the height, width, location and species of the trees he encounters during his long treks through the woods. The old way was a “rite of passage” he says, logging data in the field with pen on paper, “hoping that it wasn’t going to rain.” But, he has to admit, the new data tools “are pretty great.”