Clifford Geometric Algebra-Based Approach for 3D Modeling of Agricultural Images Acquired by UAVs

Three-dimensional image modeling is essential in many scientific disciplines, including computer vision and precision agriculture.

So far, various methods of creating three-dimensional models have been considered. However, the processing of transformation matrices of each input image data is not controlled.

Site-specific crop mapping is essential because it helps farmers determine yield, biodiversity, energy, crop coverage, etc. Clifford Geometric Algebraic understanding of signaling and image processing has become increasingly important in recent years.

Geometric Algebraic treats multi-dimensional signals in a holistic way to maintain relationship between side sizes and prevent loss of information. This article has used agricultural images acquired by UAVs to construct three-dimensional models using Clifford geometric algebra. The qualitative and quantitative performance evaluation results show that Clifford geometric algebra can generate a three-dimensional geometric statistical model directly from UAVs’ RGB (Red Green Blue) images.

Through Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and visual comparison, the proposed algorithm’s performance is compared with latest algorithms. Experimental results show that proposed algorithm is better than other leading 3D modeling algorithms.

Read more:

https://www.researchgate.net/publication/347679848_Clifford_Geometric_Algebra-Based_Approach_for_3D_Modeling_of_Agricultural_Images_Acquired_by_UAVs

UAVs for 3D mapping applications

Unmanned Aerial Vehicle (UAV) platforms are nowadays a valuable source of data for inspection, surveillance, mapping and 3D modeling issues.

As UAVs can be considered as a low cost alternative to the classical manned aerial photogrammetry, new applications in the short- and close-range domain are introduced.

Rotary or fixed wing UAVs, capable of performing the photogrammetric data acquisition with amateur or SLR digital cameras, can fly in manual, semi automated and autonomous modes.

Following a typical photogrammetric workflow, 3D results like Digital Surface or Terrain Models (DTM/DSM), contours, textured 3D models, vector information, etc. can be produced, even on large areas.

This paper explore the use of UAV for Geomatics applications, giving an interesting overview of different UAV platforms and case studies.

https://www.researchgate.net/profile/Fabio_Remondino/publication/260529522_UAV_for_3D_mapping_applications_A_review/links/00b7d532f0e4da131e000000/UAV-for-3D-mapping-applications-A-review.pdf

DroneDeploy launches Thermal Live Map

DroneDeploy, a drone software company with the largest drone data platform in the world, today announced the launch of Thermal Live Map, a real-time mobile mapping solution which delivers insights only thermal imagery can reveal.

A first-of-its-kind feature, Thermal Live Map visualizes temperature range variability and creates instant thermal maps for quick, data-guided decisions on the job site. DroneDeploy is the leading cloud software platform for commercial drones, and is making the power of aerial data accessible and productive for everyone.

Trusted by leading brands globally, DroneDeploy is transforming the way businesses leverage UAVs and aerial data across industries, including agriculture, construction, mining, inspection, and surveying. Simple by design, DroneDeploy enables professional-grade imagery and analysis, 3D modeling and more from any UAV on any device. 

The new solution is particularly valuable for firefighting, giving firefighters the ability to see through smoke and keep track of their personnel in large fire scenes. Thermal Live Map also helps locate precisely where the fire is hottest and provides definitive confirmation the fire is extinguished in specific areas. Thermal Live Map allows first responders to view hundreds of acres in minutes —day or night— penetrating hard-to-reach and hard-to-see terrain where missing or injured persons may be awaiting rescue. 

Thermal Live Map also helps growers spot field stress in real time. They identify irrigation issues, detect ripeness, and analyze plant health early to solve problem areas and avoid lost harvests. "Thermal mapping is one of the most common and difficult requests from our customers to date, but the reward equals the challenge," said Mike Winn, CEO of DroneDeploy. "Live Map makes thermal insights more accessible while increasing safety and efficiency on job sites." 

The new solution uses the latest advancements in edge computing to generate thermal drone maps locally on iOS devices as a DJI drone flies.