Join Kory Kellum, Senior Software Engineer at Phoenix LiDAR Systems, as he explores the advanced capabilities of Phoenix LiDAR’s mapping technology in their May 2022 webinar. Phoenix LiDAR specializes in compact, adaptable, survey-grade systems for various platforms like UAVs, cars, and backpacks, and offers robust post-processing software, including LiDARMill and SpatialExplorer Pro.

Phoenix LiDAR, based in Austin, Texas, contrasts with DJI’s recent entry into the LiDAR market. Phoenix offers comprehensive solutions, ensuring high-quality data acquisition and processing, supported by robust customer service. The Recon A system, with its superior APS-C camera sensor and vibration dampening kit, is compared to DJI’s Zenmuse L1, which is limited to the Matrice 300. The Recon A’s IMU is notably more accurate, reducing drift and improving data reliability.

Phoenix LiDAR’s LiDARMill offers advanced features like flight line splitting, ground control adjustments, AI classification, and detailed QC reports, which are not available in DJI’s Terra Pro. This comprehensive processing capability ensures high accuracy and quality in deliverable data products. A comparative analysis of data from DJI’s L1 and Phoenix LiDAR’s Recon A showcases significant differences in accuracy and precision. The Recon A system demonstrated superior performance, particularly in terms of reducing warping and improving overall data quality.

For those seeking accurate, high-quality LiDAR solutions, Phoenix LiDAR Systems provides a superior alternative with extensive support and advanced features.

This whitepaper delves into the innovative use of high-density LiDAR data and Quantitative Structure Modelling (QSM) to estimate individual tree attributes, traditionally predicted by field-derived allometric models. Leveraging LiDAR data collected by Unmanned Aerial Vehicles (UAVs), we evaluated the accuracy of QSM in determining key tree metrics such as diameter at breast height (dbh), tree height, volume, and aboveground biomass components (stem, branch, and total).

Our study compares two QSM approaches: integrating QSM-derived dbh and height into field-based equations for volume estimation, and deriving tree volume directly from QSM. Despite a slight overestimation tendency, the models demonstrated satisfactory performance, highlighting QSM’s potential to provide detailed and extensive tree attribute estimates.

This method offers a promising alternative for forest management decision-making, especially in analyzing tree architecture and biomass. The findings underscore the value of UAV-LiDAR and QSM in enhancing the precision and scope of forest attribute assessments.

Join Phoenix LiDAR Systems and SkySkopes for a quick fly through video focused on the RANGER series of helicopter based mapping solutions. SkySkopes is a top-tier data service provider that operates a wide variety of advanced sensors and aircraft for transmission and distribution line inspections, oil and gas applications, and many other innovative use cases that focus on adding value.

This whitepaper presents a novel approach to forest inventory within integrated crop-livestock-forest systems using high-density UAV-LiDAR point clouds. Focusing on Eucalyptus benthamii seed forest plantations, we utilized the GatorEye UAV-LiDAR system to compare two forest inventory methods: Sampling Forest Inventory (SFI) with various plot arrangements and Individual Tree Detection (ITD).

By analyzing a point cloud with over 1400 points per square meter, we assessed basal area and volume estimates using both field and LiDAR-measured heights. We compared the number of trees, basal area, and volume per hectare across different scenarios, using statistical analysis to evaluate accuracy and equivalence. Our results show that the SFI approach with a 2300 m² area provides estimates comparable to the ITD method, with minimal error and improved processing efficiency.

This study offers valuable insights for selecting optimal plot sizes in forest inventories, enhancing precision in integrated crop-livestock-forest systems.

The December 2021 Phoenix LiDAR Systems webinar focused on LiDAR snow surface mapping for NASA’s SnowEx program. Jeff Rizza from DJ&A detailed a 2021 snow surface mapping project using high-resolution drone LiDAR to capture data in Montana’s prairie biome. Highlighting his experience with UAVs and LiDAR, Jeff discussed DJ&A’s collaboration with NASA and Montana State University to improve snow data collection methods.

The webinar covered Phoenix’s LiDAR systems, cold-weather challenges, and innovative survey methods for accurate snow surface mapping. Jeff showcased data insights on snow dynamics influenced by wind and vegetation and discussed processing challenges using Phoenix’s SpatialExplorer and Terascan software. The Q&A session addressed equipment, data processing, and unique SnowEx project aspects. Jeff also previewed an upcoming white paper comparing LiDAR and photogrammetry, highlighting LiDAR’s advantages in vegetation-dense areas.

Evolving the Capabilities of LiDAR

With the introduction of the RECON series, Phoenix LiDAR Systems is removing barriers to widespread LiDAR remote sensing adoption. The RECON series combines low-cost hardware with Phoenix LiDAR Systems industry leading software, LiDARMill, and is empowering a new generation of professionals like never before.

The RECON series features higher accuracies than competing products (that are based on Applanix or DJI navigation systems), while offering extremely simple, automated post-processing solutions to extract maximum value from each dataset.

Utilizing the LiDARMill online, automated processing platform, raw datasets can be imported straight from a USB drive, with reference and optional ground control data seamlessly integrated. Simple wizards enable advanced processing options like trajectory optimization, LiDAR and camera calibration, AI classification, smart decimation and the creation of high-quality deliverables (contours, DTM/DSM/CHM, pointcloud tiling etc.). A fully registered, colorized pointcloud is produced that is accurate in both relative and absolute terms. Project reports then summarize project performance and verify system accuracy.

Phoenix Lidar Systems is committed to designing the world’s most advanced, complete LiDAR solutions. With the RECON + LiDARMill combination, users can deploy a simple toolkit that is able to derive accurate and reliable datasets in a matter of hours. Powerful, affordable, and comprehensive…the RECON series by Phoenix Lidar Systems is now available, and sure to disrupt the remote sensing industry.

This whitepaper explores a groundbreaking framework for quantifying fuel load in fire-prone regions, focusing on the Brazilian tropical savanna (Cerrado biome), using NASA’s GEDI full-waveform spaceborne LiDAR sensor. Understanding fuel load is crucial for integrated fire management, preserving carbon stock, biodiversity, and ecosystem functioning, and assessing global climate regulation. Traditional remote sensing methods lack the capability to measure vertical vegetation structure accurately.

Our study leverages UAV-collected LiDAR data to simulate GEDI full-waveforms, from which we derive vegetation structure metrics. These metrics are then correlated with field-measured fuel load components using Random Forest models. The resulting models, which predict woody and total fuel loads with high accuracy (R² = 0.88 and 0.71, respectively), provide reliable estimates even for lower strata components.

This innovative approach allows for the creation of fuel load maps for the entire Cerrado and can be extended to other fire-prone regions, enhancing fire management and carbon monitoring efforts. This research showcases the potential of spaceborne LiDAR to revolutionize environmental management and climate initiatives in tropical savannas and beyond.

In recent years, airborne laser scanning has revolutionized the documentation of historic cultural landscapes, extending its applications from natural landscapes to built environments. The integration of unoccupied aerial vehicles (UAVs) with LiDAR systems is a transformative advancement, providing complementary data for precise mapping of targeted areas.

This whitepaper presents the findings from a 2019 study in the Maya Lowlands of Chiapas, Mexico, utilizing UAV LiDAR to capture and analyze data from six archaeologically significant areas. These areas, characterized by diverse environments, land cover, and archaeological features, were studied for their pre-Hispanic settlements and agrarian landscapes. The results confirm the immense potential of UAV LiDAR systems for high-precision archaeological mapping and underscore the importance of multidisciplinary collaboration.

The high-precision data acquired is invaluable for mapping archaeological features and understanding long-term land use and landscape changes in archaeological contexts.

Join the May 2021 Phoenix LiDAR Systems webinar, hosted by Senior GIS Engineer Ira Monkfold, as he dives into survey-grade calibration and accuracies from point cloud data. This insightful session focuses on the LiDAR Snap 4 calibration tool within the SpatialExplorer software. Learn about the essential requirements for achieving precise point cloud data and how Phoenix LiDAR Systems can help you create survey-grade data effortlessly.

Ira explains the critical importance of precise system calibration, covering accurate measurements of lever arms and the alignment of laser, GNSS, and IMU components. He highlights the necessity of mission-specific optimization to address in-flight anomalies, ensuring data accuracy. The integration of surveyed ground control points is emphasized as a vital step for achieving geospatial accuracy, with LiDAR Snap 4 providing comprehensive calibration and reporting tools.

LiDAR Snap 4 revolutionizes the calibration process by combining multiple steps into a single, user-friendly software interface, significantly reducing complexity and time. The software features advanced capabilities such as encoder calibrations and trajectory optimizations, offering users reliable survey-grade point cloud data. The webinar also includes a Q&A session, addressing software capabilities, processing times, and compatibility with various LiDAR systems and platforms.