Geophysical Surveys Improved with Airborne LiDAR

Geophysical Surveys Improved with Airborne LiDAR

By Chase Wood, Data Acquisition Manager Goldspot Discoveries Corp. 

Editor’s Note: This article is being reported as a narrative as told by the author.

Background

Geophysical Surveys Airborne LiDAR

My name is Chase Wood, and I am the Data Acquisition Manager for Goldspot Discoveries Corp.  (GoldSpot) Applied Geophysics and Geomatics division. My first experiences with airborne data collection were using lightweight geophysical instruments (magnetometers) and LiDAR scanners attached to Unmanned Aerial Vehicles (UAV) for the mining and mineral exploration industry.  After many years, and a few companies later, I started branching out to include data collection from more traditional manned aviation platforms, including helicopters.  In mid-2021 Goldspot decided the time was right to add airborne data acquisition and LiDAR scanning to their arsenal and a group of us was brought on board to build the team.   A critical part of that team is Emma Woodlock. She brings a wealth of GIS – specific knowledge to our team as well as previous LiDAR data processing and QA/QC experience, specifically from the power line inspection industry. 

Inventory

Goldspot currently owns a RIEGL VUX-240 airborne laser scanner integrated into the VPX-1 pod and attached to Goldspot’s B2 ASTAR helicopter. In tandem with this, we also have dual PhaseOne RGB and NIR cameras bore sighted to the LiDAR to produce colorized point clouds and 4-band imagery.  All of the laser and photo data write to removable solid-state drives within the PhaseOne IX controller that acts as a systems control center.  Finally, TopoFlight Mission Planner triggers the LiDAR and camera systems automatically based on our pre-planned flight lines and specified mission parameters.  We made the decision to support the RIEGL system with the Trimble R12 GPS base and rover.  Using the Trimble system, we can collect static GPS data, to both correct the airborne scanners trajectory and to provide survey check point locations to ensure we are providing accurate and precise data.  The complete system was purchased in late 2021 for its first full season of operations in 2022.

Quality and Support Sets RIEGL Apart

Our team has used other airborne laser scanning systems in the past, but we always found that the hardware and software was lacking, and the support did not meet our expectations.  When we had the opportunity to purchase a new airborne laser scanner for Goldspot, we evaluated several other systems and manufactures, however RIEGL came out significantly ahead of the competition. This was for a few reasons, including the obvious fit/finish and the quality/attention to detail of the hardware solutions themselves.  The other big reason was the reputation that RIEGL has cultivated for being the go-to name in laser scanning and the support that is included when operating the system.  The bulk of our work is in very remote areas globally for the mining and mineral exploration sector. Having the confidence to know that RIEGL has our backs if there is an issue, from remote support to shipping outa backupscanner so we can continue our work in the event there is a major issue is something that “sealed the deal.” 

Best Practices and Lessons Learned

Since Goldspot initially started out providing high resolution geophysics surveys, we were well prepared for the challenges posed by implementing a new system into our airborne workflows.  There are some notable differences between geophysical and geomatics data collection that took some time to get right.  For example, to collect clean geophysics data, helicopter flights are typically flown at a very tight drape to the earth’s surface with the magnetometers, VLF, and radiometric sensors as close as fifty meters above the ground and at 50-meter swath widths.  

The ability to collect very clean, high-resolution LiDAR and photo data, hundreds of meters above ground level at swath widths greater than 400 meters is still amazing to me.  The two flying and data collection styles are so completely different to one another that it took some time for the pilots and collection teams to adapt to the new flight parameters.  

The second challenge was setting up the data storage and sharing workflows to accommodate the massive datasets that the sensors produce.  Luckily together with Goldspot’s data science team and experience in handling datasets of this size for machine learning inputs, we quickly navigated this challenge as well. 

Manned aviation is extremely expensive and the ability to reliably collect high quality data, hundreds of meters above ground level at swath widths greater than 400m creates a situation where we can not only cover most of our average sized projects in a handful of helicopter hours, but it also allows us to level the playing field and compete with fixed-wing data providers from a collection cost and data resolution standpoint.   Many of our clients choose helicopter surveys because of the increased data resolution when compared to fixed wing surveys in both the geophysics and geomatics fields.  

Looking to the Future

In general, in the mining and mineral exploration sector, I think that LiDAR datasets are still seen as a luxury not a necessity.  Goldspot would like to change that line of thinking.  We can collect many of the geophysical products that have for years been an absolute must for any exploration project, but now offer geomatics products (LiDAR and 4 band imagery) in one aircraft mobilization and packaged price. This creates a situation where many of our clients are choosing to collect the extra data layers, where otherwise they may not have.  

There is also a huge opportunity for our business moving forward to reach out from the more traditional mining and mineral exploration projects that we were used to, and branch into other areas which require this kind and quality of data.  That is construction and engineering projects, forestry, and powerline surveys to name a few.  There is a massive effort at Goldspot using our standardized data inputs to drive our machine learning and software development groups to create some unique offerings that haven’t been seen before. 

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