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Individual tree detection using UAV-lidar and UAV-SfM data: A tutorial for beginners
May 19, 2023
LiDAR Selection Guide
June 29, 2023

Monitoring the Brazilian savanna with lidar and RGB sensors onboard remotely piloted aircraft systems

May 19, 2023
UAV LiDAR Mapping - Brazilian Savanna

UAV LiDAR Mapping - Brazilian Savanna

UAV LiDAR Automated Vegetation Monitoring of The Brazilian Savanna

In 2017, an international team of Brazilian and U.S. scientists used two UAVs, including a Phoenix LiDAR system, to monitor and analyze degraded parts of the Brazilian Savanna that had previously been surveyed with aircraft and LiDAR. Their goal: to protect the most biologically diverse savanna in the world from further human impacts, restore native species, and increase CO2 absorption to mitigate the effects of climate change, all while balancing the protection and restoration of natural resources with food production.

UAVs are already used extensively in Brazil for a number of other uses. This team gathered both physical and biological information about the vegetation cover using Phoenix LiDAR and also visual (RGB) sensors. Counting trees is a critical metric that enables them to estimate planted seedling survival rates, species density, plant spacing, etc.

This team’s objective was to demonstrate how both Phoenix LiDAR and RGB sensors helped them monitor the vegetation structure (including tree numbers and height) in the Cerrado savanna. Phoenix LiDAR’s accuracy in performing automated measurements of the number and height of the trees was superior to the RGB sensors, though RGB was also useful for identifying tree species.

The international team of researchers is monitoring and analyzing the most biologically diverse savanna in the world to protect it from further human impacts, while balancing food production.

Remotely Piloted Aircraft Systems (RPAS) fitted with Phoenix LiDAR systems and also RGB visual cameras, performed better surveys for less cost, time, and effort. Phoenix LiDAR did a better job counting and measuring the trees in the ten survey plots, compared to the same survey done with an RGB camera.

The researchers collected data for ten plots over three surveys total; comparison monitoring data was collected by aircraft-based LiDAR in 2015, and the two 2017 UAV surveys were one month apart, one using the University of Florida’s GatorEye system (a Velodyne VLP-16 dual-return laser scanner head, capable of 600,000 returns per second, with Phoenix live and post-processing software, mounted on the DJI Matrice 600 Pro hexacopter multi-rotor UAV, with L1/L2 dual-frequency GNSS (PPK mode - Post Processing Kinematic), and the other using a SODA RGB 24 MP camera mounted on a fixed-wing Sensefly UAV.

A Phoenix LiDAR system, including Phoenix live and post-processing software, was mounted on a DJI drone.

This study compared the UAV LiDAR to UAV RGB data, and compared both to the previous 2015 LiDAR data, discussing Phoenix LiDAR’s superior accuracy over RGB’s, and acknowledging additional benefits of the RGB sensor.

This research demonstrates that this kind of research can be done by UAV, and it provides higher-resolution data than the aircraft surveys while reducing cost, time, and effort.

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