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UAV LiDAR Mapping the Brazilian Savanna to Help Fight Climate Change
A team of scientists from the Department of Forestry, the University of Brasilia, and other organizations invested in the study of climate change have been using sensors from Phoenix LiDAR Systems to map vegetation biomass by drone, providing key insights into the carbon cycle to help lower carbon emissions and better manage the impacts of climate change.
[Vegetation biomass is the total weight or quantity of plants present in a given area—terms like yield, plant matter, and plant production are also sometimes used in place of biomass.]
Traditionally, scientists collect vegetation biomass data in the field by walking through a sample area and making measurements. These sample measurements can then be extrapolated using mathematical models to create measurements for the entire environment. But this manual approach is incredibly time-consuming and expensive, not to mention potentially bad for the environment, since it requires researchers to walk through the area on foot as they collect data.
To solve the data collection problem, scientists have honed a new approach: using drones equipped with LiDAR sensors.
By using UAVs (Uncrewed Aerial Vehicles, also known as drones), researchers can fly over sample areas and collect detailed LiDAR data in a fraction of the time it would take to do so manually. This data can then be processed using mathematical models to estimate the total biomass for the entire system.
The UAV LiDAR approach has several benefits, including:
- Speed. The approach is much faster than mapping and making vegetation biomass estimates via manual data collection.
- Accuracy. Using drone LiDAR data instead of manually-collected data improves the accuracy of outputs such as tree height, leaf area density, and—the key data point—biomass.
- It’s better for the environment. This approach also minimizes the negative impact data collection can have on the environment, since the drone flies above the vegetation, avoiding the need for people to walk through it on the ground.
So far, the UAV LiDAR approach to mapping vegetation and making biomass estimates has primarily been used in forests, focusing solely on the biomass of trees. But there are other important types of ecosystems that contribute to the planet’s carbon cycles, such as the tropical savanna found in Brazil, called the Cerrado.
The Cerrado is the second largest habitat in South America, and a crucial environment for the global carbon cycle. The team of scientists decided to test UAV LiDAR there for vegetation mapping and biomass calculation, presenting one of the first times the approach has ever been used to study a tropical savanna habitat.
Keep reading to learn how the team adapted its UAV LiDAR data collection methods for the unique environments found in the tropical savanna, and whether the approach was a success.
Why Mapping the Savanna Is So Important
Although rain forests are often the focus when we talk about carbon capture and climate change, tropical savannas make up 20% of the Earth’s surface and also play a key role in the carbon cycle.
In recent years, these savannas have lost a huge amount of vegetation due to human encroachment and increases in fires caused by climate change. In Brazil, for example, the Cerrado has lost almost half of its original vegetation over the last few decades alone, a loss that can primarily be attributed to the growth in agricultural production in the area.
Although previous studies have highlighted the benefits of using UAV LiDAR for estimating biomass in forests by focusing on trees, most of the biomass in tropical savannas comes from things like grass, dead leaves, and plant material on the ground, all of which can have a big impact on the amount of carbon stored in the ecosystem.
To inform policymakers in developing strategies for carbon markets, it’s important to understand how the environment naturally captures and stores carbon, and how much of this is happening in different types of environments across the planet.
This information is crucial for reducing carbon emissions—and that’s why mapping the vegetation biomass in the Cerrado was a point of focus for the team of scientists. If they could develop an approach that worked there it could potentially be applied to other tropical savannas, presenting a major step forward in humanity’s understanding of the global carbon cycle.
How Scientists Used UAV LiDAR to Map the Cerrado
Scientists had already established a method for mapping large areas of forests using UAV LiDAR. The approach involved collecting data in a sample area by drone, then using mathematical models to extrapolate the biomass for the entire environment. But the Cerrado presented a new environment, which meant new models would have to be developed.
The end goal for the team was to estimate and map the total aboveground biomass density (AGBt) of woody, shrubs, and surface vegetation found in the Brazilian savanna—an ambitious endeavor given that the Cerrado spans over two million square kilometers.
Here is the approach they planned to use:
- Identify types of vegetation for mapping. Three major types of vegetation were identified in the tropical savanna: forest, savanna, and grassland.
- Develop a framework. Given that this type of environment hadn’t been mapped with UAV LiDAR before, new frameworks were needed that would allow the scientists to choose the best UAV-LiDAR metrics for building AGBt models.
- Identify areas for data collection. Four locations in the Cerrado biome were selected for data collection, each of which had unique vegetation structures and was representative of different types of vegetation found there in terms of height, width, and species diversity.
- Take measurements. Using UAV LiDAR, scientists would collect measurements at each of the four locations.
- Process the data and make conclusions. After collecting the data, scientists planned to process it using the frameworks and models they had developed. They hoped to make findings regarding the vegetation biomass in the Cerrado, as well as evaluate the UAV LiDAR approach itself to see if it could be used to map other tropical savannas.
The four areas selected for data collection in the Cerrado biome
To ensure thorough data collection, scientists first established field plots of 30 meters by 30 meters, making sure to cover the entirety of each area with the plots.
Plot corners were registered using a Differential Global Navigation Satellite System (DGNSS), and the aboveground biomass density of trees in each area was determined from measurements of all the individual trees within the plot with a diameter at breast height. Similar methods were used to measure shrubs and small trees.
Ground pictures and UAV LiDAR point clouds for three types of vegetation
While these measurements were taken on the ground, scientists also used the GatorEye UAV-LiDAR system to collect data from the air as well. The GatorEye system consists of a DJI Matrice 600 Pro UAV mounted with a Phoenix Scout Ultra core to integrate LiDar with an inertial motion unit, a differential GNSS system, and a Velodyne VLP-32c LiDAR sensor.
The GatorEye UAV-LiDAR System in the Cerrado
Scientists programmed the drone to perform its data collection flights autonomously. In total, the drone flew approximately 600 kilometers of flight lines covering 1,854 hectares. According to the scientists conducting the study, at the time and to the best of their knowledge this was the largest area of UAV-LiDAR ever used in a publication.
After collecting LiDAR data by drone the scientists excluded duplicative measurements, then selected five measurements that were important for understanding the vegetation. These five measurements included the height of the tallest trees, the extent of the tree canopy, and the shape of the vegetation.
By analyzing these measurements they were able to build models that accurately estimated the amount of above-ground biomass vegetation in the area. Using a combination of aerial imagery and advanced analysis techniques, scientists were able to map the biomass in the area and then use that data to estimate the amount of carbon stored in each of the four locations studied.
The uncertainty and errors of the researchers’ estimations were assessed for each vegetation formation separately, resulting in Root Mean Square Errors (RMSEs) of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands, making the grassland data the most uncertain of the three.
Here is depiction of the workflow the scientists followed to perform the AGBt mapping:
Results and Next Steps
The team of scientists found that the use of UAV LiDAR was successful in mapping the tropical savanna environment presented by the Cerrado of Brazil. This success makes the study a benchmark for future efforts to map vegetation biomass, which can help other scientists to generate consistent maps of aboveground biomass density (AGBt) using UAV LiDAR.
In addition to informing future studies, the data can also be used as a baseline for managing fires and climate change impacts in the Cerrado and in other tropical savannas.
Here are some specific findings from the study:
- Savannas and forests stored much more carbon than grasslands
- Savannas were the most common vegetation types in the study areas
- The uncertainty associated with carbon estimates was higher in grasslands than in savannas or forests
The fact that LiDAR-equipped drones can help expedite biomass data collection while also making it more accurate presents a promising new method for this important work to improve our understanding of the global carbon cycle and inform conservation efforts in general.
This study is just the first step toward better understanding tropical savannas using UAV LiDAR. Now that these baseline data have been collected, there is more work to be done.
