Data is the basis of scientific processes

Written by Drone

As many as possible, as precisely as possible. Data is the basis of scientific processes. Obtaining them is therefore essential for the conception and success of research projects. But the larger the area under observation, the more difficult it becomes to collect sufficiently detailed data. To counter this problem, a symbiosis of science, citizens, and drones is supposed to lead to positive results on several levels in the “Undercover Ice Agents” project.

Whether extreme weather conditions, natural disasters, or ozone holes, tangible consequences of greenhouse gas emissions and global warming, there is already a lot. How dramatic and above all self-accelerating the effects can be can be seen, for example, from the changes in polar permafrost regions such as the Canadian Arctic. Because here, climate change ensures that permafrost areas that formed in the last Ice Age or shortly thereafter continue to thaw and release the organic sediments that are preserved in them like a gigantic freezer. With devastating consequences. The carbonaceous material is broken down by microorganisms and gigantic amounts of carbon dioxide and methane are released into the atmosphere. Experts assume that up to 1,500 gigatons of carbon are bound in the permafrost areas, which make up around 25% of the exposed land area in the northern hemisphere. And thus almost twice as much as can currently be found in the atmosphere. The greenhouse gases accelerate global warming, which in turn results in the melting of permafrost areas. A fatal vicious circle for the world’s climate.

The aim of “Undercover Ice Agents” at the DLR Institute of Data Science is to improve the database on thawing permafrost with the help of high-resolution drone and satellite images together with citizen scientists, especially schoolchildren. And that on both sides of the Atlantic. In the summer months, residents of the 600-strong community of Aklavik, north of the Arctic Circle, will fly around 10 square kilometers with the help of DJI drones. The high-resolution image data obtained in this way are put together using photogrammetric methods to create a three-dimensional surface model as well as an overall image, which is to be the basis for later analysis by students from Canada and Germany.

But what should the so-called “citizen scientists” – because, in addition to young people, adults can of course also contribute to the success of the project via the MapSwipe app – are they actually looking for? How do you recognize permafrost zones that are protected by a thaw layer up to 2 meters thick and protrude below the surface to a depth of more than 1,000 meters? “Permafrost in the soil can be recognized by specific phenomena on the soil surface. The most prominent is the polygon structures that are created by repeated melting and freezing processes. Christian Thiel, sub-project leader and scientist in the Citizen Science Department at the DLR Institute for Data Science. “Here, polygons are lined up, with the boundary of each polygon at the same time representing the boundary of the neighboring polygon. These patterns are also known as solidified basalt in the form of basalt columns. In degraded permafrost areas, these patterns are less pronounced, disappear completely and there are larger breaks at the edges of slopes. Thermokarst lakes can also arise. These changes can happen within a few years and with a little practice, you can quickly learn to tell the difference between intact and damaged permafrost.

In the extreme cold of the arctic winter, the frozen ground contracts, and fine cracks appear. When the weather thaws, meltwater penetrates into these and freezes in the permafrost layers, so that, piece by piece and over many years, vertical ice channels are created. In the summer months, the resulting polygon structures are clearly visible from the air. If the permafrost disappears or the thaw layer grows so strong that it no longer completely freezes through even in winter, the characteristic landscape drawings also disappear. Can we use drones to monitor data?

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