- Remote sensing tools and algorithms bring transparency to land use.
- Datasets and land use alerts find a market among government and non-governmental agencies.
- Management tools protect endangered lands, raising awareness about drivers of land use.
Growing up in central Indiana, Matthew Hansen would sometimes visit the old growth forests left in the state.
“It was like being in a scene out of the Lord of the Rings,” he recalls with fondness. “Sycamores without understory, leaves on the ground, and just this big, big open space under these towering trees. It was awesome, like going into a cathedral.”
These experiences must have left an indelible mark on his psyche, because decades later he finds himself a leader in land use management.
Hansen is now a professor at the University of Maryland, where he heads up the Global Land Analysis and Discovery (GLAD) laboratory. His work uses remote sensing tools and algorithms to keep track of land use across multiple scales. His team produces datasets and maps that inform and empower land resources management.
“We’re pushing transparency and having a reliable record of our natural resources. We document, and then everyone can argue about what it means, and then decide how best to move forward. We think our datasets empower downstream science and downstream policy.”
Hansen’s team at GLAD tracks many aspects of land use; among the most important subjects they study is the change to forests around the world.
Thanks to the well-calibrated instruments launched into Earth orbit by agencies like NASA, GLAD has been able to fine tune algorithms that can extrapolate images and document what’s going on in the forests.
To do so, Hansen’s team collates satellite images and delivers annual reports on a variety of land use metrics that summarize a year’s worth of alteration to a nation’s land. In between these annual reports, Hansen’s team sends out alerts.
“We look at the land pixel by pixel, and when we get a quality-assured land observation, we run an algorithm to test if there’s a forest disturbance in that pixel. It is a management-enforcement product that is meant to bring a timely, actionable observation to those issues.”
GLAD alerts government agencies to issues like illegal logging and mining or incursions into protected areas, such as indigenous reserves or animal habitats.
"Our datasets empower downstream science and downstream policy." ~ Matthew Hansen
Peru’s use of GLAD's alert products is particularly encouraging, Hansen says, as their Ministry of the Environment has built a website that receives the alerts and communicates them to the various regions of the state. In addition to the information system Peru has constructed to disseminate environmental data, they’ve also directed their prosecutors to use Hansen’s alerts to enforce their forestry code.
Russia also makes great use of the alerts, albeit from a different motivation.
“The Russian government seems to be very interested in this because they lose a lot of tax revenue with far east logging. Something like 90 percent goes out of the country without official sanction,” Hansen says.
The Jane Goodall Institute also employs Hansen’s alerts to help stave the dwindling chimpanzee habitat. Chimpanzees are forced into narrow riparian zones alongside rivers and are feeling so much pressure they have become nocturnal animals to steal corn out of fields.
Though an alert at that stage may be too late, most of the time the alerts do make a difference.
“Remote sensing data tells you about places you are not witnessing first hand, so it fills in all the gaps. One of the things we see is that loggers and others exploiting the forest change their behavior in response to these signals and alerts.”
His remote sensing alerts feed into a synoptic overview of what’s going on in a region or particular swath of land. This perspective provides a record that can address a whole host of issues.
Hansen's tools have supported NASA climate models that create a global perspective of bio-geo chemical cycles and climate dynamics. They have been used to demonstrate that greater tree cover provides a more resilient and diverse supply of food stuffs, with better health outcomes as a result. Hansen’s datasets have also been used to show correlation between Indonesian decentralization and deforestation.
“The thing about our datasets is that they brings transparency to the idea of forest change,” Hansen observes. “Transparency means also understanding what are the drivers of those forest changes and what are the connections that pushed that forest to be cleared: palm oil, soybean, rubber, whatever. We need to make those connections and bring understanding to the public.”