Category Archives: Agriculture

Measuring Snow Depth in Colorado with Lidar

Research Associate Blake Osborn with the Colorado Water Center/CSU Extension Service explained the various methods used for measuring snow depth in Colorado and how they function at the annual Agriculture Conference at Ski-Hi in Monte Vista Feb. 4. From an … Continue reading

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Canopy Base Height Estimates From Lidar

Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality and forest health as well as a necessary input in fire behavior prediction systems such as … Continue reading

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Automating Plant ID with Laser Scanning and AI

Automated camera systems have enabled scientists to quickly track traits of thousands of plants. Now researchers at the Salk Institute are automating plant identification with 3D laser scanning and machine-learning algorithms. The algorithms teach a computer to analyze three-dimensional shapes … Continue reading

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SAM, LLC Invests in Technology to Enhance Solutions

This is an excerpt from an article on Lidar News that provides an inside look at Surveying and Mapping, LLC – SAM and how technology has helped them become the largest geospatial service company in the U.S. (Originally posted September … Continue reading

Posted in 3D Modeling, Agriculture, airborne LiDAR, archaeology, BIM, Construction, cultural heritage, Environmental, GIS, GNSS, Mapping, remote sensing, Surveying, UAS, UAVs | Tagged , , , , , , | Leave a comment

UAS Lidar – Not a Simple Upgrade from Photogrammetry

It may seem like a fairly straightforward upgrade from UAS photogrammetry to UAS Lidar, but that is simply not the case. It’s really all about a higher level of systems integration and fail-safe, standard operating procedures that most firms are … Continue reading

Posted in 3D Modeling, Agriculture, airborne LiDAR, Conferences, Data, Environmental, Forestry, GNSS, GPS, Hardware, Infrastructure, Inspection, Lidar, Mapping, Photogrammetry, point clouds, remote sensing, Sensors, Software, Structure from motion, Surveying, UAS, UAVs, Visualization | Tagged , , , , , | Leave a comment

Drone Safety in Construction, Utilities, AG and More

November 4-10 was the Federal Aviation Administration‘s (“FAA”) first annual National Drone Safety Awareness Week. The FAA’s mission is to provide the safest, most efficient aerospace system in the world, which it accomplishes by ensuring that all those who utilize the U.S. … Continue reading

Posted in 3D Modeling, Agriculture, AI, airborne LiDAR, artificial intelligence, Business Development, BVLOS, Construction, Consumer, Drones, Environmental, Forestry, Government, Laser Scanning, Lidar, Mapping, Photogrammetry, point clouds, remote sensing, Research, Safety, Surveying, Technology, The Industry, UAS, UAVs, Young Geospatial Professional | Tagged , , , , | Leave a comment

Novel Use of SLAM to Improve Single Scan Data

Precise structural information collected from plots is significant in the management of and decision-making regarding forest resources. Currently, laser scanning is widely used in forestry inventories to acquire three-dimensional (3D) structural information. This paper presents a novel use of SLAM … Continue reading

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Fragmented Forest Canopy Effects Documented with Lidar

With the help of airborne lasers, researchers have discovered what a fragmented forest canopy means in the long-term for tropical trees. From an article in Inverse. Trees at the edges of forests store 22 PERCENT LESS CARBON than trees inside … Continue reading

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Trees Have a Heartbeat – Lidar Proves It

Scientist Diana Beresford Kroeger proved that the biochemistry of humans and that of plants and trees are the same – ie the hormones (including serotonin) that regulate human and plant life are identical. What this means practically is that trees … Continue reading

Posted in 3D Modeling, Agriculture, Data, Environmental, Forestry, Laser Scanning, Lidar, point clouds, remote sensing, Research | Tagged , , | 2 Comments

Vegetation Classification Using Lidar and Hyperspectral

Abstract: The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for dryland vegetation classification with remote sensing. Consequently, the results of a single classification algorithm or … Continue reading

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