Customer Success Story: Revolutionising Geospatial Analytics with GIX Consulting

We spoke with Tristian Campbell-Reynolds, Founding Partner at GIX Consulting, to find out how the Nano HP™ is supporting their work in geospatial analytics.

What are your main responsibilities at GIX? 

My main responsibility include conducting research and development as well as handling day-to-day activities at GIX. We focus on developing software for data processing, machine learning, and related tasks.

What challenges were you experiencing prior to purchasing the Nano HP™  compact VNIR hyperspectral imaging system? 

Up until now, we primarily focused on optical and LIDAR data collection, particularly in LIDAR segmentation and biomass estimation. We didn’t collect hyperspectral data, so had to rely on satellite multi-spectral data; we needed hyperspectral data for more accurate carbon estimation.

How did you first become aware of the Nano HP™ ?

I attended a workshop held in Germany at the Centre for Hyperspectral Remote Sensing Europe (CHRSE). During the workshop, we were provided with a comprehensive demonstration of the Nano HP™ system, which offered valuable insights into its potential applications, particularly in conjunction with machine learning.

“We were highly satisfied with the level of service provided by Headwall and Analytik. We encountered no issues and wish to express our positive feedback. The information request process proceeded seamlessly.” Tristian Campbell-Reynolds GIX Consulting 

Why the Nano HP?

We were impressed by the outcome of the workshop demonstration. It underscored the indispensable nature of hyperspectral data for our specific requirements, especially concerning precise carbon estimation. Although the Headwall Nano HP™ was not the exclusive option under consideration, our ultimate choice was influenced by our pre-existing relationship with Headwall Photonics and the distinct advantage of concurrently acquiring LIDAR and VNIR data. This capability is pivotal for our forestry data collection endeavours, and we have observed that the Headwall sensor is notably well-suited for deployment on drone platforms.

How do you plan to use the new capability in the future?

Our vision for the product encompasses an extensive range of applications, including the collection of diverse data related to tree species, biomass metrics, and the training of machine learning models. This collected data will play a fundamental role in enabling accurate tree species recognition and enriching our understanding of biodiversity and carbon sequestration. Furthermore, we anticipate expanding our data collection efforts into the agriculture sector, offering this service to our clientele. We are also in process of exploring applications in the realm of self-driving tractors and sprayers

What do you hope to contribute to science/the world with your work?

Our aim is to introduce higher-definition monitoring methodology for general forestry management, including precise carbon estimation for individual trees. Our overreaching goal is to leverage the acquired data for purposes such as species recognition, biodiversity assessments, and project focused on carbon dynamics. We intend to monitor the individual metrics of trees and their growth rates for more precise of carbon content.

What have been the highlights of your application that have been made possible by the product?

One of the noteworthy achievements facilitated by the Nano HP™ is the potential for species recognition, a capability that could not be attained to the required degree of accuracy using LIDAR data alone. It is worth nothing that we are currently in the process of developing this capability, and the inclusion of hyperspectral data is pivotal in this regard.

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