Field Spectroscopy: Part Two
Innovative data logging protocols to meet increased demand.
James Caudery
Spatial/Data Analyst at GHD
James is a Spatial Analyst at GHD in Melbourne.
James worked for 2Excel Geo as a Geospatial Analyst from 2015-2018. James was a functional lead for Field Operations and was responsible for the planning and execution of multiple successful field trials.
Single Spectrometer Data Logging
A critical element of field spectroscopy is to record the details (metadata) about the target at the time of measurement. Ideally, collecting data using a single spectrometer (as described in Part 1), is conducted with two operators, one operating the spectrometer and one to log metadata. However, manual data logging in the field is time consuming and prone to error; for example, if the scan numbers and logs become unsynchronised, this error can prove to be unrecoverable.
To address these issues, as part of our wheat disease campaign, we developed an application within Microsoft Excel to assist data logging, which is depicted in Figure 1.
This application allows the operator to record the actions taken by the spectrometer operator. This includes optimising the instrument to the intensity of light conditions, taking a white reference measurement (to be used to correct the target measurement/s), taking a quality control white reference measurement, and taking a actual target measurement. Each time an action was triggered, the scan (measurement) number would auto-update as appropriate. Other buttons were also included, which related to the target being measured. In the example shown above, this included the specific wheat cultivar and it’s treatment regime.
Figure 1
An example of an early assisted data logging tool.
Figure 1
An example of an early assisted data logging tool.
As described in Part One, white reference measurements corrected with a previous white reference measurement used to check the change in illumination in the intervening period. If the result varies more than a few percent, then the target measurements would be marked as poor and may prompt a further collection attempt.
This procedure improved efficiency over traditional form filling, and vastly reduced the occurrences of omissions and errors. Back in the office, the data log was used to group spectra into various categories and ensure that only reliable spectra were passed on for exploitation.
Automated Data Logging for the Dual Spectrometer System
In Part One we discussed the introduction of a Dual Spectrometer System. This system is capable of rapidly collecting thousands of spectra per hour. In order to realise this potential in a field context, we needed to upgrade our data logging abilities and so decided to use a spatial solution. Rather than actually recording the metadata in the field, we would record the spatial position of each measured spectrum and use this to match the measurement to the target’s metadata, post-collection.
Figure 2
From left to right: The RTK GNSS base station; the operator with a controller, roving spectrometer and RTK GNSS unit; and the base spectrometer measuring the standard reference panel synchronously with each roving target measurement.
Figure 2
From left to right: The RTK GNSS base station; the operator with a controller, roving spectrometer and RTK GNSS unit; and the base spectrometer measuring the standard reference panel synchronously with each roving target measurement.
The spatial accuracy required was on the order of centimetres. To obtain this accuracy we procured the Reach RS RTK GNSS system by Emlid. In this configuration, one receiver with an accurately known location acts as a base station, which transmits real-time corrections to the roving receiver positioned close to the spectrometer’s fiber optic cable.
This setup allowed roving spatial and spectral measurements, constantly referenced to a known position and standard reference respectively. To mitigate the influence of shadows and spectral contamination caused by the operator, the fiber optic cable and roving GPS are mounted on a side boom.
This system enables the constant recording of field spectra, with each measurement being geotagged with a highly accurate position. Quality checks to mitigate the effects of instrument drift were made periodically, by using both spectrometers to measure the standard reference simultaneously.
Figure 3
Post-processing associates each spectrum with a specific plot and it’s associated metadata.
Figure 3
Post-processing associates each spectrum with a specific plot and it’s associated metadata.
Using a Geographic Information System, the spectral measurements can be spatially matched to known attributes of each target, completely eliminating any manual data logging in the field. The outcome of this development is a system that reduces time spent in the field, maximises collection capacity and eliminates manual data logs.
The equipment and operators described in this article are available as a stand-alone service or as a component of a remote sensing project.
