Jason Lopez: LIDAR stands for laser imaging detection and ranges by measuring the return of laser light. The technology can create 3d maps of the earth from above, usually from airplanes. It's a critical tool for scientists studying geology, earthquakes, forestry, and many other disciplines and car makers use it in navigation systems in autonomous vehicles to detect and avoid objects. But in Miller's research, he's using LIDAR data, to determine the micro changes in altitude of the rolling Hills in Iowa carpeted with corn and soybeans. It tells him how much topsoil is being lost. As it moves downhill on a long march to the Gulf of Mexico.
Bradley Miller: When we see the difference in elevation from 2009 to 2020, we can say, okay, we observe this amount in of elevation change. And then the question is, can our models starting with 2009 as the baseline, will they actually predict what happened in that 11-year span?
Jason Lopez: If Miller's research can show the model's work, it could have enormous implications for understanding how to preserve the topsoil. The world needs to grow food. What was once humanly impossible to measure in this case? Massive numbers of survey points on 30 million acres of Iowa farmland is now doable.
Bradley Miller: So you cover a large area with that. That's a large amount of information. And then that gets multiplied by the time steps that we're looking at, just the validation data being 2009 and 2020 for the project we're doing here in Iowa. That's basically the state of Iowa double over, but as our models make predictions about the different landscape changes over time. Each of those time steps is another representation of the whole area, Iowa, with that amount of detail. So the amount of data gets multiplied by
Jason Lopez: All that, with the technology cocktail of LIDAR cloud and AI Miller and his team are able to see soil properties on a scale, never seen before LIDAR can see the surface changes of soil loss, but it can't see below to the layers expos, as we witnessed earlier, by pounding in a soil sampler to pull out a core, but that's where AI.
Bradley Miller: Can help out. We see relationships with some of the things that are on the surface with what happens below and finding those patterns is really where machine learning comes into play. And then we're going to process models to basically predict what's gonna happen over to time.
Jason Lopez: Professor Miller emphasizes that this work is still ongoing, but the addition of sensing and information technology tools to scientists puts them much closer to understanding the dynamics of topsoil from farm fields of Iowa, to the rest of the world
Bradley Miller: In science, we frequently have this idea that you hold a candle up in a dark room. You can see the light around that, and that's the world you see, but as you increase the brightness of that candle, the world gets bigger. And it's kind of a similar story for a lot of things that we're exploring, whether it be black holes or the human brain, or even soil as we're getting new tools, we have new ways of looking at it and digging pun intended deeper into it. It far as I understand what's happening, the one extra piece maybe for soil is that as you look across the landscape, the soil's different all over the place. There are similar processes happening, but the interactions are happening in different ways. And now I'm gonna show you the difference between the soil on top of this hill, to the bottom of the hill, but go to other Hills, there's gonna be things that are similar, but so different understanding all of that spatial variability is part of the challenge in fully understanding soil
Jason Lopez: Bradley Miller is a soil scientist and head of the geospatial lab for soil informatics at Iowa state university. This is the tech barometer podcast produced by the I'm Jason Lopez. If you like this story, you might want to check out our other forecast stories on technology and science at www.theforecastbynutanix.com.