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  • Webinar (36)
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  • Whitepaper (21)
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  • Forestry (19)
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  • Scout (26)
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  • Ranger-U120 (4)
  • Ranger-UAV (3)

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Single-pass UAV-borne GatorEye LiDAR sampling as a rapid assessment method for surveying Forest structure
December 1, 2020

This whitepaper examines the efficiency and accuracy of UAV-borne LiDAR, specifically the GatorEye system, for high-resolution forest data acquisition, comparing it to traditional aircraft-borne LiDAR in the Apalachicola National Forest, USA. The study assesses the effectiveness of single-pass flight plans for generating digital terrain models (DTMs) and canopy height models (CHMs).

Results indicate that DTMs derived from UAV LiDAR showed less than 1 meter difference compared to aircraft-derived DTMs within a 145° field of view (FOV). CHMs provided reliable treetop detection, though tree height underestimations occurred at distances over 175 meters from the flight line. Crown segmentation was effective within a 60° FOV, but shadowing effects hindered its accuracy beyond this range.

The study identifies optimal quality thresholds for various LiDAR products, supporting the development of efficient, cost-effective UAV flight plans for forest monitoring. These findings highlight the potential of UAV-borne LiDAR for detailed, multi-temporal forest structure assessment, offering valuable insights for forest management and conservation strategies.

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Comparing high-resolution satellite and GatorEye UAV lidar data for trail mapping in mixed pine and oak forests in central Florida using a participatory approach
December 1, 2020

This whitepaper explores the effectiveness of UAV-borne LiDAR technology for detecting small trails (less than 2.5 meters wide) in mixed forest canopy ecosystems. Accurate trail mapping is crucial for forest management, monitoring, and conservation, yet current sensor technology for sub-canopy detection is still evolving.

The study compares trail detectability using high-definition surface models from UAV LiDAR data and high-resolution satellite imagery from Google Earth. Through participatory mapping, respondents with limited geospatial experience identified trails on both map types. Results showed higher detection rates on the LiDAR-derived map compared to the satellite imagery. In satellite maps, trail detectability was positively correlated with wider trails and lower canopy cover, whereas LiDAR maps showed increased detectability with wider trails regardless of canopy cover.

This mixed-method approach, combining UAV-mounted LiDAR, satellite imagery, and participatory mapping, enhances the rapid detection of small trails under varying conditions, offering valuable insights for improving forest management and conservation efforts.

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UAS LiDAR System Considerations – Watch Our Presentation from The 2020 Oregon UAS Summit!
November 6, 2020

In this informative presentation by Kory Kellum from Phoenix LiDAR Systems, viewers will gain a comprehensive understanding of UAS LiDAR systems. Kory delves into the essential components of a LiDAR system, such as the LiDAR sensor, GNSS antenna, IMU, data storage, CPU, and optional camera, emphasizing the need for high-quality trajectories through post-processed kinematic (PPK) methods and bore site calibration.

He outlines the critical steps in processing UAS LiDAR data, from mission planning to classification, and categorizes LiDAR systems based on precision, accuracy, point density, and maximum range. Corey also compares multi-laser and single-laser sensors, discusses the selection of GNSS antennas and IMUs, and provides an overview of current LiDAR systems like the Ranger series, and Scout series. The presentation highlights the benefits of co-acquiring imagery and features examples of data outputs to illustrate system performance.

Concluding with a Q&A session, this video is a must-watch for those interested in selecting the right LiDAR system for their specific needs and budget.

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Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar
November 1, 2020

This whitepaper investigates the innovative application of the GatorEye drone-borne LiDAR system for monitoring tropical forest succession through detailed canopy structural attributes. These attributes include canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index, leaf area index (LAI), and understory LAI.

Focusing on nine tropical forest stands in the Caribbean lowlands of northeastern Costa Rica, the study evaluates the relationship between these variables and aboveground biomass (AGB) stocks and species diversity. The analysis reveals that while canopy height and AGB do not show a clear pattern with forest age, gap fraction and spatial heterogeneity increase, and understory LAI decreases as forests age.

Notably, canopy height is strongly correlated with AGB. The study demonstrates that drone-LiDAR systems significantly enhance the characterization of heterogeneous mosaics created by successional forest patches in human-managed landscapes. This technology offers a valuable tool for improving forest recovery assessments and developing mechanistic carbon sequestration models, crucial for tracking progress within the UN Decade on Ecosystem Restoration.

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A Sneak Peek from a Recent Ranger-XL Dataset
October 20, 2020

A few weeks ago we posted a video of a completed Ranger-XL ready for shipment. Here’s a peek at a recent dataset collected by that same Ranger-XL coupled with the 100MP Phase One 4-band Solution. This urban corridor was easily captured with a single pass, creating a stunning dataset with high Imagery and LiDAR resolution. Data specs: 80 Points Per Square Meter Average for LiDAR and 3cm GSD for imagery.

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Phoenix LiDAR Systems has Moved to Austin, Texas!
June 22, 2020

We are excited to announce the opening of our new headquarters based in Austin, Texas! Our new facility offers numerous benefits to advance our operations and meet our customers’ needs:

• More than double the size of our Los Angeles facility
• Spacious conference rooms to accommodate multiple concurrent customer training sessions
• Close proximity to field sites for pilot and acquisition training
• Accommodations for system testing and calibration
• 30 minutes from the Austin-Bergstrom International Airport
• Less than 10 minutes from the Domain, a trendy Austin shopping center and social hotspot

As of Friday, June 26, 2020, all of our Los Angeles operations will be permanently relocated to our new facility located at:

2113 Wells Branch Parkway
Building 1, Suite #4000
Austin, TX 78728

We will not be able to receive mail or other shipments at 10131 National Blvd, Los Angeles, CA 90034 after June 26th. Please let us know if you have any questions.

Sincerely,

The Phoenix LiDAR Team

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Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft-and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil
May 29, 2020

This whitepaper explores the challenges of obtaining high-quality forest structure information in tropical forests, particularly those in difficult-to-access areas. Traditional field-based approaches are often costly and time-consuming, prompting the use of LiDAR technology for efficient and comprehensive structural parameter estimates.

The study compares aboveground biomass (AGB) estimations and products from aircraft-borne LiDAR data collected in 2015 with data from the UAV-borne GatorEye Unmanned Flying Laboratory in 2017 across ten forest inventory plots in the Chico Mendes Extractive Reserve in Acre, southwestern Brazilian Amazon.

Findings indicate that both platforms produce comparable LiDAR products, with the GatorEye system demonstrating higher point density due to its lower and slower flight and increased returns per second. Despite these differences, ground point density remained similar between the systems.

Both sensors yielded analogous results for digital elevation models and estimated AGB. This study validates the effectiveness of UAV-borne LiDAR sensors in accurately quantifying AGB in dense tropical forests and highlights the potential for detailed analyses of crown structure and leaf area density distribution using dense point clouds from UAV systems.

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UAV LiDAR and Hyperspectral Systems
May 21, 2020

The high dimensionality of data generated by Unmanned Aerial Vehicle(UAV)-Lidar makes it difficult to use classical statistical techniques to design accurate predictive models from these data for conducting forest inventories. Machine learning techniques have the potential to solve this problem of modeling forest attributes from remotely sensed data. This work tests four different machine learning approaches – namely Support Vector Regression, Random Forest, Artificial Neural Networks, and Extreme Gradient Boosting – on high-density GatorEye UAV-Lidar point clouds for indirect estimation of individual tree dendrometric metrics (field-derived) such as diameter at breast height, total height, and timber volume.

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Customer Spotlight – Mohawk College LiDAR Scanning at Niagara Falls!
March 31, 2020

Mohawk College recently partnered with the Niagara Parks Commission on a critical project, utilizing their Phoenix LiDAR Scout 32 system to achieve two key objectives. First, they generated a precision high-resolution 3D model of the historic Toronto Power Generation Station. This data is instrumental for the rehabilitation efforts to preserve this architecturally significant structure.

Second, they accurately scanned and geo-located a century-old barge that had been lodged above Niagara Falls since 1918. Dislodged by a powerful storm, the barge moved 150 meters downstream, closer to Horseshoe Falls. Niagara Parks Officials are closely monitoring its potential movement.

UAV LiDAR technology enabled the team to geo-locate the barge with centimeter-level precision and create a detailed cultural heritage preservation model of the power station. This project underscores the critical role of advanced LiDAR technology in historical preservation and environmental monitoring.

Check out their fine work and some incredible footage from the Niagara Falls project here!

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