Golf Course Management

MAR 2015

Golf Course Management magazine is dedicated to advancing the golf course superintendent profession and helping GCSAA members achieve career success.

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ent from previous work because Dr. Leinauer was especially interested in turfgrass quality, a measure that includes density, uniformity, leaf texture, smoothness, growth habit and green color. Previously, most of the work in this area focused on turfgrass color only. In this study, as with previous studies, the researchers found signifcant correlation in turf color data col - lected by the NDVI and DIA color-index methods, and in percent cover data collected through NDVI and DIA. Thus, both types of remote-sensing equipment seemed to agree with each other pretty well, when color and percent cover were assessed. But what about the quality of the turf — that multicharacteristic rating of the attrac - tiveness of a sward? Well, the NDVI meter was best for tracking changes over time. That is, from day to day, NDVI readings might be the best tool for describing changes in turf - grass quality over time — even better than a person's visual ratings. Thus, an NDVI meter could be a handy tool for your course, al - lowing you to track turfgrass quality in your specifc grass and management situation over time. The NDVI and DIA tools were less use - ful when different varieties were being com- pared. In that case, visual assessments best detected differences caused by variety. So, NDVI readings you collect from your course, with your variety, would not be especially use - ful to your neighbor at a different course with a different variety of turf. At this time, the au - thors concluded that a visual assessment de- tected quality differences in turfgrasses more accurately, especially when different varieties were involved. Source: Leinauer, B., D.M. VanLeeuwen, M. Serena, M. Schiavon and E. Sevostianova. 2014. Digital image analysis and spectral refectance to determine turfgrass quality. Agronomy Journal 106:1787-1794. Beth Guertal, Ph.D., is a professor in the department of crop, soil and environmental sciences at Auburn Univer - sity in Auburn, Ala., and the editor-in-chief for the Ameri- can Society of Agronomy. She is an 18-year member of GCSAA. 98 GOLF COURSE MANAGEMENT 03.15 Remote sensing. Digital imagery. Spectral refectance. All terms used to describe some basic procedure by which a digital image is used to quantify the color or growth of turf - grass. The science has made its way into gen- eral use, and now everything from relatively cheap hand-held sensors to affordable cell phone applications can be purchased to help keep track of the color of your turfgrass. Some of these tools have been shown to work well in rating and tracking percent green cover and turfgrass color. But what about quality? Although the color of turfgrass is certainly a primary factor in determining turf quality, a lot of other char - acteristics can often affect quality. The abil- ity of remote sensing to evaluate the quality of turf has not been well studied, and the re - sults that are out there are pretty mixed. So, in an effort to gain some more defnitive results, the folks at New Mexico State University (Dr. Bernd Leinauer and his crew) used the Na - tional Turfgrass Evaluation Program (NTEP) variety trials to try to get a handle on the re - mote sensing of turfgrass quality. They used bermudagrass, zoysiagrass, seashore paspalum, Kentucky bluegrass and tall fescue variety tri - als. Over four years, they took monthly visual ratings (using a standard 1–9 scale, where 1 indicates dormant or dead, 9 is perfect and 6 is minimally acceptable), NDVI (normal - ized difference vegetative index) readings and DIA (digital image analysis) readings. NDVI readings are a refectance (in the near- infrared and red ranges) obtained from scan - ning an area of turf, while DIA readings are photographs taken under controlled settings (camera mounted on a metal box that encom - passes a known area of turf ), which are then digitized to a green color index. In this study, the DIA readings were also used to obtain a percent cover rating. The idea of these alterna - tive measurement methods is that a quick scan or picture of a turfgrass sward would provide an accurate and unbiased estimate of turfgrass quality, an estimate not sullied by a human's perceptions or preconceptions. At the simplest, Dr. Leinauer wanted to see how well visual quality, NDVI and DIA related to each other. This study was differ - Beth Guertal, Ph.D. guertea@auburn.edu twitter: @AUTurfFert I see you doing that (verdure) This study was different from previous work because Dr. Leinauer was especially interested in turfgrass quality, a measure that includes density, uniformity, leaf texture, smoothness, growth habit and green color.

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