 Trees are really important to us humans. They produce that delicious oxygen that we love so much. They also clean the air, removing both pesky pollutants and elements like carbon dioxide. You know, those things that have been linked with sad polar bears and warming climates? And if that's not enough of a service to society, trees happily slurp up and filter rainwater as it rungs along the ground, protecting us from floods. And they even block our sensitive human exteriors from those outdoor elements like wind and sun. The importance of trees to us humans inspires scientists to measure and inventory them across the globe to identify where trees are and where they're not, where they've been damaged, cut down, or burned, and where they're growing strong. However, trees cover almost a third of the Earth's surface. That's 29.5% or 9.5 billion acres. That equals 750 million football fields of trees. So how does a scientist measure 750 million football fields worth of trees across the globe? Well, one way to measure trees around the world is to get a whole lot of graduate students together and maybe a few other volunteers in one organized tree measuring effort. But maybe that's not such an efficient approach. A more efficient way to measure trees and other objects, like buildings on the ground, is to use remote sensing technology. Remote meaning to observe and measure something from afar as opposed to with our hands. One type of remote sensing data used to measure tree height over the entire country is called LiDAR, the topic of this video. LiDAR stands for light detection and ranging. A LiDAR system uses light energy emitted from a laser to scan the Earth's surface and record the heights of objects like trees and buildings on the ground. The LiDAR also works together with a global positioning system, or GPS receiver, to identify the location of those things on the ground. The use of a laser to actively produce light energy makes LiDAR an active remote sensing system. While LiDAR technology is exciting, it certainly isn't new. In fact, the earliest laser remote sensing systems date back to the 1960s. During the 1970s, they were used to measure ground elevation and produce the earliest high-resolution elevation maps. But LiDAR still wasn't being used to measure trees. The most common early use of LiDAR data was to produce beautiful high-resolution elevation maps that clearly identified the dips and peaks of hills and mountains with a level of detail that hadn't been seen before in science. And talk about useful, they even documented where stream channels and roads were. The detail and accuracy that LiDAR data provided with these high-resolution elevation data sets made people excited to work with LiDAR-derived elevation maps. How could you not be? Now, in LiDAR's early stages, the vegetation information contained in the data was considered noise. And people worked hard to remove as much of the noise as possible in order to create the most refined topographic maps. But alas, it was realized over time that within that noise was valuable information about vegetation. And soon it was discovered that LiDAR could be used to measure things like tree height and vegetation density and cover. And so the value of LiDAR data to better measure topography, vegetation, and even buildings was realized and the use of LiDAR data in science took off. To make this a modern-day story, we can now use information about vegetation found in LiDAR data to study large-scale ecological issues. For example, we can use LiDAR data to estimate the impact of fire on a forest, identifying how many trees still exist compared to how many burned away. Or we can use LiDAR data to estimate where certain wildlife species might prefer to live and reproduce. We can even use LiDAR-derived tree heights to estimate ecological metrics like vegetation density or biomass over large areas. Information that can help us better understand carbon cycles and in turn relate to changes in our climate. But wait, there's more! We can also collect LiDAR data over the same areas using the same settings over and over again through time. Maps of vegetation created over time allow us to identify and quantify changes that have occurred. If that's not cool enough, LiDAR data allows us to create powerful visual animations that show trends in vegetation as it changes through time. Talk about a powerful ecological tool. So this ability to understand ecosystems over such large areas and through time makes LiDAR data extremely useful to ecologists. And this is why the National Ecological Observatory Network, otherwise known as NEON, is collecting LiDAR data that will be freely available over all of its core sites every year for 30 years. Now we can't wrap this video up without taking a look at some LiDAR data collected using the NEON Airborne Observation Platform. Here are some data collected over Harvard Forest in Massachusetts. Notice how you can pick out and potentially measure individual trees in this video. Now imagine measuring all of those trees by hand.