Log In
Login to Phoenix LiDar System
Remember Me

Environmental Engineering

RANGER-LR | Dense Vegetation River Corridor

Point Density: 320 points per m^2
Height: 80 m AGL 
Speed: 8 m/s  
Data Acquisition Time: 7 minutes

The Benefits of Laser Scanning in Geospatial Engineering

LiDAR technology, a groundbreaking innovation in the realm of surveying and remote sensing, has been a game-changer for many industries. With its ability to provide accurate and detailed data, it’s no wonder that professionals and organizations are rapidly adopting this technology. Among the most notable advancements in this field is the use of drones for LiDAR. This video delves deep into the environmental and technical challenges faced in drone-based LiDAR, drawing insights from industry experts James Kessner and Aaron Handl of Encompass Services.

LiDAR Snow Surface Mapping for the NASA SnowEX Program

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 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 Spatial Explorer 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.

LiDAR in Animal Landscape Ecology Applications

Discover the innovative use of LiDAR technology in animal landscape ecology with Phoenix LiDAR Systems’ November 2020 webinar. This session delves into how remote sensing technologies, like LiDAR, are revolutionizing ecological research, particularly in understanding animal-landscape interactions. Hosted by Kory Kellum, a top GIS engineer at Phoenix LiDAR, the webinar features insights from Evan Hawkeridge, a PhD student from Harvard University’s Davies Lab.

Learn about the role of ecosystem engineers, such as elephants and termites, and how their behaviors influence ecosystems on a regional scale. The discussion covers advanced data collection methods using drones equipped with LiDAR and thermal sensors, challenges faced in field operations, and groundbreaking research projects in Kruger National Park and the Republic of Congo.

Tune in to explore how these technologies provide unprecedented detail and accuracy in ecological studies, offering new perspectives on animal behavior and landscape changes. Perfect for ecologists, researchers, and tech enthusiasts, this webinar showcases the future of ecological monitoring and analysis.

Advanced Imaging Solutions

Join the Phoenix LiDAR Systems webinar on advanced imaging systems, held on April 21, 2021. Hosted by Conrad Conterno, Head of Post-Processing, and Justin Wyatt, VP of Sales at Phoenix LiDAR Systems, along with Nick Nelio, Inspection Sales Manager for Phase One, this session dives into how Phoenix LiDAR’s data collection tools integrate with Phase One’s cutting-edge imaging systems to enhance remote sensing capabilities.

Conrad Conterno opens with an overview of Phoenix LiDAR’s custom mapping solutions, emphasizing sensor integration for superior data acquisition and analysis. He introduces various advanced camera options, including the lightweight custom A6K Light for UAV-based mapping, dual oblique cameras for enhanced colorization, multispectral solutions for detailed vegetation analysis, thermal mapping cameras for environmental monitoring, and hyperspectral sensors for precise spectral analysis.

Nick Nelio then showcases Phase One’s high-resolution, medium-format cameras, focusing on the 4-band solution that combines RGB and near-infrared imagery, ideal for crop analysis and environmental monitoring. He also presents the Phase One P3 payload for inspection applications and the IX Mach 5 controller designed for efficient geospatial missions.

Throughout the webinar, the benefits of direct geo-referencing and the seamless integration of multiple sensors into single payloads are highlighted. The hosts address audience questions on the accuracy of dual-camera systems, post-processing challenges, and the applications of hyperspectral imaging.

The session concludes with Justin Wyatt and Nick Nelio emphasizing their collaborative approach to delivering tailored solutions and inviting viewers to contact them for personalized consultations.

UAV LiDAR and Hyperspectral Systems

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 Ex-

treme 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.

LiDARMill Version 2

We’re excited to announce the release of LiDARMill v2! LiDARMill v2 takes automated post-processing to the next level. In our recent webinar, we covered some of the new improvements and features including:

  • Imagery Processing in LiDARMill
  • Ground Control Reporting and Adjustments
  • Robust Coordinate System Handling
  • A Workflow Overview and Demonstration
  • Multi-Mission Processing Support
  • Advanced Point Cloud Filtering Options
  • RGB Thermal & Fusion
  • Accuracy Reporting
  • Automated LiDAR and Camera Calibration Options
  • Near-Real Time (NRT) Reference Station Positioning for Projects Requiring Less Than 24 Hour Turn-around Time
  • Trajectory Post-Processing Without Reference Stations

If you have any questions or would like to learn more about LiDARMill v2, please don’t hesitate to get in touch. We’d be happy to help!