How scientists are using a space laser to make predictions about wildfire severity
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Lots of scientists here on Earth are studying forest health and biodiversity — but not many of them are doing that work by using a space laser.
Chris Hakkenberg is, though. Hakkenberg's an assistant research professor in the School of Informatics, Computing and Cyber Systems at Northern Arizona University, where he studies how to use remote sensing like lidar to characterize forest structure and then use that information to make predictions on wildfire severity, carbon sequestration and biodiversity.
Hakkenberg joined The Show to talk about his work.
Interview highlights
What exactly is this kind of lidar you're using? What is it, and how does it work?
HAKKENBERG: Well, there's two primary types of lidar that I'm using. The first is airborne, which means it's mounted on a small plane that's flown over over 30 sites across the United States that's run by the National Ecological Observation Network. The second piece of lidar that we're using is GEDI is the acronym that stands for Global Ecosystem Dynamics Investigation, which is a NASA sensor on an International Space Station.
The main difference between the two is that airborne lidar is flown over smaller swaths over landscapes, which we can patch together on the scale of about 100 kilometers to 250 kilometers squared. GEDI, on the other hand, is passing overhead every 90 minutes on the International Space Station. And it samples the entire earth surface minus the extreme high latitudes at the poles. And that's just because the International Space Station doesn't cross that area.
So what are you able to see with that, that you're maybe not able to see and determine from other forms of mapping?
HAKKENBERG: So what's unique about GEDI is that it's the highest resolution and densest sampling of any lidar system that's put into orbit. And it's the first designed specifically to measure canopy structure. So what it enables us to do is to map the three-dimensional volume of the forest from space. And by three-dimensional volume, what I mean is the vertical distribution of everything you can think of in a forest — the branches, the leaves, the needles — from the ground all the way up to the top of the canopy. And what is also unique about GEDI is that it has global coverage.
Does having that kind of consistent coverage also help you determine when there are changes and detect them a little more quickly?
HAKKENBERG: So the power of GEDI and spacebourne lidar in general is the ability to characterize the three-dimensional volume of the forest, which we can use to determine things like carbon stored and carbon sequestered, as well as biodiversity habitat. In terms of high frequency detection of, let's say, things like deforestation, there are other sensors that are better tuned to those sorts of investigations.
So when you talk about the three-dimensional structure of the forest, I assume that means going beyond trees and, and really looking at plants and shrubs and basically anything else that might be in or on the forest?
HAKKENBERG: Exactly. Yeah. So the ground instruments, for example, terrestrial lidar, which is not too different, which is from the Liar technology that's on some autonomous driving cars — is able to give us a wonderful, very high-resolution view of what's immediately surrounding it. At a slightly coarser scale is the airborne lidar that nonetheless gives us a map for a structure over greater extent, from hundreds to 250 kilometers squared.
GEDI gives us a global picture of forest structure. However, at the cost of some of that resolution. So we can get a fairly clear picture of the distribution of branches from the ground to the top, but we're not able to detect individual plants or individual shrubs. We can we get a coarser signal that nonetheless, we can use an aggregate across the globe to be a very powerful indicator of, again, things like carbon sequestration and biodiversity habitat.
On a practical level, how do you anticipate actually deploying this like in what ways might this be useful to people who do what you do?
HAKKENBERG: So it's been incredibly useful for me from a basic science standpoint to look at large scale drivers of forest biodiversity. Because I can use the single sensor to assess forest structure in places like New Hampshire or Puerto Rico or Hawaii or the Pacific Northwest — very different types of forests — and to assess how the forest structure in those places may be driving or constraining the biodiversity therein. And with statistical models, we can predict a continuous surface of biodiversity across the United States in in this study. And in other studies, we've been using this to map the distribution of endangered animals like the clouded leopard in Southeast Asia.
And in other cases, we are using this to be able to determine wildfire risk and severity potential by looking at total amount of fuels that are potentially combustible in a wildfire but also, critically, the vertical and horizontal continuity of those fuels. So, in other words, if there are latter fuels that will enable fuel ... that will enable fire to get up into the canopy. And horizontal continuity refers to fire moving from kind of point A to point B on the landscape, given the appropriate amount of fuel in between. And so, GEDI allows us to map this at large scales in a very consistent manner and critically use it with other types of data.
How cool is it to be able to tell people that you study forest health and what's going on on earth by using space lasers?
HAKKENBERG: I, I'll admit it. It is pretty cool to be able to, yeah, tell the niece and nephew ... what I've been working on. They get a kick out of that, you know, their crazy uncle working with space lasers.
