Key Takeaways

• Remote sensing has the potential to make golf course maintenance more efficient and effective, but there are limitations with the various technologies currently available.
  
  
• Research has shown that remote sensing technology can identify turf stress before it is visible to the human eye.
  
  
• Preliminary findings in current studies suggest that there is a randomness and potential lack of sensitivity in the soil moisture values from remote sensors.
  
  
• Calibration and validation with known values is needed to produce accurate results and maps from remote sensing technology. Ground-truthing is essential.
  
  
  

When turf conditions are uniform (good or bad) the amount of light that is being reflected back to the sensor will be fairly consistent. The resulting imagery will show few to no variations. However, while there may not be obvious variations within each image, consistently “good” images will look different than consistently “bad” ones because of the relative amount of reflectance back to the sensors. Conversely, when turf conditions are variable throughout the surveyed area, this imagery can display those differences oftentimes before they become visible with the naked eye.

L-band radiometry: The amount of water in the soil influences the intensity of microwave radiation that is emitted into the atmosphere. L-band radiometers measure the intensity of these microwaves in the soil. A soil moisture percentage is then assigned to each level of intensity to create a mosaic of soil moisture across the entire area that has been sampled. These sensors can be mounted on a mower or cart. In their current format, each sensor has a 35-degree field of view, so they can sample much more ground than a traditional hand-held soil moisture meter.
 

Synthetic aperture radar: Similar to L-band radiometry, synthetic aperture radar also gathers backscattered microwave radiation from the soil. Electromagnetic pulses are captured from satellites far above Earth’s surface. The microwave data retrieved from this process is then converted into an estimated soil moisture image. Colors can be assigned to specific moisture levels to create a meaningful picture of soil VWC across a large area.

Cosmic ray neutron sensors: A cosmic ray neutron sensor (CRNS) is a device that can measure moisture levels by detecting fast moving neutrons in the soil and in the air just above the soil. Neutrons lose energy from collisions with hydrogen in soil water. These lower energy neutrons are what CRNS detect. When placed near a fairway, for example, the sensor can monitor neutron reflectance in a circular pattern that can reach a hundred meters away. Larger versions of this technology only give an average moisture reading over a big area, which is not useful for golf course superintendents. There are also versions of CRNS detectors that can be mounted on a cart or mower. These smaller units can theoretically have tighter spatial resolution and faster data collection than their big brothers. The data collected can then be converted into a soil moisture map with designated colors for different percentages of VWC.

Electromagnetic induction: This technology uses sets of coils above the turf surface to create a subsurface electromagnetic field. Electrical currents are then analyzed as they move through the soil substrate to determine, among other things, soil moisture content. The spacing between detection coils and power source determine the depth of sampling. These also can generate color-coded maps representing VWC, similar to the other instrumentations.

The goal for all these sensing technologies is to produce a map or image of the golf course that allows the superintendent to make informed decisions on turf management. Whether it is a soil moisture map or an NDVI image that shows traffic or other stressors, remote sensing done right should provide another layer of information that can help superintendents better manage their facilities. It should also make scouting for issues faster and more effective. Now to the big question, does this technology work in a golf context?
 

Does this stuff actually work?

These technologies may sound like science fiction, but they are real and theoretically work on a large scale. Even NASA has been using them to evaluate moisture on the Earth’s surface since the 1970s. But what about for golf courses? Can these technologies provide detailed intelligence for a superintendent to use?

Unfortunately, the current answer to this question is not a simple yes or no. Research has shown that some remote sensing technology can be used to detect a number of forms of plant stress before it becomes visible to the naked eye. Anecdotal evidence on the wide-ranging benefits of new remote sensing technologies abound. Reduced water use and improved visualization of turf stresses are the two I hear the most. But is there scientific evidence based on repeatable and controlled research that supports these claims?

Research findings to date

Multiple studies have evaluated thermal and multispectral imaging and its correlation with turf health. These have shown that things like canopy temperature, near-infrared images, NDVI and NDRE collected from small unmanned aircraft systems or portable devices can be good indicators of plant stress before it’s visible to the human eye. One such study found that these remote sensing products were showing drought stress five days ahead of visual symptoms being manifested on creeping bentgrass turf. Another study looked at NDVI and NDRE images and nematode activity. As these vegetative index images improved or declined, plant parasitic nematode populations decreased or increased respectively.

I point out these two studies for a reason. Causes for turf stress abound. Drought, disease, insects, shade, turf type, traffic stress, salinity, nematodes and any number of other things can be reasons why turf health suffers. Thermal and/or multispectral imaging can definitely show us that turf health or density is compromised. But how do we know what the real problem is by just looking at an image? Sometimes, it may be obvious. An image that shows green circles around every sprinkler head and yellow or orange in areas that are clearly not getting hit with the irrigation system highlights an issue with irrigation coverage. Other times it may not be so obvious. This is when the maintenance staff needs to get out and investigate. You can use the maps and images to focus your attention on potential problem areas and make your scouting more efficient, but there is no substitute for boots on the ground when it comes to understanding problems on the course.
 

Ongoing research

New entries into the turf remote sensing world are happening with greater frequency. Cosmic ray neutron sensors, L-band radiometry, synthetic aperture radar and electromagnetic induction aren’t necessarily new to the remote sensing world, just new to turf. These technologies have been used on much larger scales than fairways, greens and tees. The challenge for these products and services is to scale down their fields of vision while increasing their spatial resolution and accuracy. A golf course superintendent would not be interested in a moisture map that is accurate within 20 miles. Nor would they be interested in knowing what the soil moisture is 20-30 inches below their fairways. As these technologies enter the golf world, it is important that we do research to understand if they’re generating data that we can use on our courses, and if they can measure it in a robust and repeatable manner.

Two USGA-funded research trials are underway to evaluate the effectiveness of these new-to-golf remote sensing technologies. Texas A&M and New Mexico State University are putting these sensors to the test. Results so far have not shown a strong relationship between known soil moisture readings and these new sensing techniques. Preliminary findings suggest that there is a randomness and potential lack of sensitivity to the soil moisture values from these sensors. This basically means it’s a coin flip on whether it reads the same moisture level as the known VWC. It is important to note that these are preliminary findings and there is hope that with more research and development of these platforms, we’ll get to a point where there is a stronger relationship.
 

Challenges and opportunities

A major challenge with these new moisture sensing technologies is the depth of sampling. Portable moisture meters have probes that are inserted into the ground. They are measuring to a specific depth and averaging the soil VWC. With indirect sensing methods, there is no pinpointing depth. Research suggests the depth of measurement is a function of water content and surface temperature. They are relying on signal strength, or proximity of the sensor to the surface, or an angle of reflectance, or something else to measure moisture at specific depths. With variable soil conditions throughout most golf courses, calibrating a remote sensor to accurately read the same depth throughout seems very difficult, if not impossible.

Another consideration with these new products is that frequent calibration must happen in order for them to give us meaningful readings. In the case of soil moisture, since they’re not reading an actual soil moisture percentage, they rely on algorithms in their respective software platforms to translate their data into a VWC value. Those software platforms need validated VWC readings to make their calculations. These values may come from in-ground soil moisture sensors or on-site weather stations and it’s likely that some amount of regular validation and recalibration will always be needed.
 

So, how can we use remote sensing technologies on our courses now? Many superintendents have been using remote sensing for years. Some have found it useful, some have not. Proponents are using the data and imagery to make decisions on irrigation, spray applications and course setup among other things. Opponents would say that the information is not accurate enough or frequent enough to be useful. However, even though the raw data may not match what would be measured directly in the soil, repeated use of these technologies at a specific course or location can result in a “local calibration.” What I mean by this is that the data and images that the course receives, whether or not they match the real VWC, can begin to have meaning when compared to past images at the same location. If the data is consistent, the superintendent can see patterns and come up with action thresholds based on experience and validation. Such a process is similar to how hand-held TDRs are commonly used. At minimum, there is likely an efficiency in scouting for problems, even if ground-truthing that information is still necessary to truly understand whether there is an issue or not.

Final thoughts

Technological advances are great for golf course management. It seems like every year we hear of some new gadget or service that will help superintendents. As with any new technology, do your own research when it comes to using remote sensing tools at your course. Validate the data that you are receiving and provide the manufacturers with constructive feedback that can help them continuously improve their offerings. Think about how many years of development and refining it took to get our modern cell phones to where they are now. I am hopeful that as these remote sensing platforms are further refined, they can give the golf course industry excellent and reliable data on a much larger scale.