Golf Course Applications of Near-Surface Geophysical Methods: A Case Study
Bibliographic record
Abstract
Abstract As of the year 2000, there were over 15,000 golf course facilities in the U.S.A. alone. The upkeep of these facilities requires continual maintenance and occasional remodeling. The superintendents and architects responsible for the maintenance and remodeling efforts need non-destructive tools for obtaining information on shallow subsurface features within parts of the golf course, particularly tees and greens. The subsurface features of importance include, but are not limited to, constructed soil layer characteristics and drainage system infrastructure. Near-surface geophysical methods can potentially provide a non-destructive means for golf course superintendents and architects to obtain the shallow subsurface information required to address their maintenance and remodeling concerns. This case study assessment of near-surface geophysical methods in regard to golf course applications focused on electromagnetic induction (EMI) and ground penetrating radar (GPR) techniques. The investigation employed two different EMI ground conductivity meters. Two GPR systems were also tested including the evaluation of antenna center frequencies ranging from 250 to 1,000 MHz. The study incorporated three separate sites. Measurements with both EMI and GPR were collected on a tee and a green at the Muirfield Village Golf Club in Dublin, Ohio, U.S.A. and on a practice green at the Golf Club of Dublin in Dublin, Ohio, U.S.A. GPR was also tested on a golf course green at the Guelph Turfgrass Institute & Environmental Research Centre in Guelph, Ontario, Canada. Results indicate that use of the appropriate EMI equipment can provide information on spatial changes of shallow apparent electrical conductivity (ECa) within golf course green constructed soil layers. This ECa data could potentially be employed to gauge constructed soil layer conditions, including wetness, salinity, etc., within different areas of a green. GPR proved quite capable of obtaining useful information on the golf course tee and greens that were studied, at least in regard to constructed soil layer thicknesses/depths or their areal extent and in locating the subsurface drainage pipe systems present. For the GPR center antenna frequencies evaluated, ranging from 250 to 1,000 MHz, all seemed to work relatively well for mapping tee and green constructed soil layer areal extent and drainage pipe locations. The higher frequency 900 and 1,000 MHz antennas appeared to work best for resolving thicknesses/depths of constructed soil layers within the tee and greens investigated. In addition, computer modeling of synthetic GPR profiles provide valuable insight and help considerably with data interpretation. While more research is certainly warranted, near-surface geophysical methods, especially EMI and GPR, appear to show promise with respect to acquiring the data needed in golf course maintenance and remodeling applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".