Short‐term spatiotemporal relationship between plant and soil properties on natural turfgrass sports fields

Straw, Chase M.; Grubbs, Rebecca A.; Henry, Gerald M.

doi:10.1002/agg2.20043

Cited by 7 publications

(8 citation statements)

References 21 publications

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“…Straw et al. (2020) studied spatial variability of bermudagrass grown on two soil types within American football fields. The authors found correlation coefficients of 0.57 and 0.62 before and after irrigation, respectively, on the sandy loam field, and 0.41 and 0.24 before and after irrigation, respectively, on the sand capped field.…”

Section: Resultsmentioning

confidence: 99%

“…Hong, Bremer, and Van der Merwe (2019b) found VWC to be positively correlated (r = 0.59) with NDVI measured using an active handheld sensor on creeping bentgrass plots in a controlled study. Straw et al (2020) studied spatial variability of bermudagrass grown on two soil types within American football fields. The authors found correlation coefficients of 0.57 and 0.62 before and after irrigation, respectively, on the sandy loam field, and 0.41 and 0.24 before and after irrigation, respectively, on the sand capped field.…”

Section: Correlation Of Vwc and Proximal Ndvimentioning

confidence: 99%

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Comparing ground‐based and aerial data at field scale during dry down on golf course fairways

Friell

Straw

2021

Intl Turfgrass Soc Res J

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Spatiotemporal data and analyses are gaining traction in the turfgrass industry as valuable tools to enable data-driven management practices, but to date there has been minimal research in practical settings. The objective of this work was to quantify relationships between soil volumetric water content (VWC), proximal normalized difference vegetation index (NDVI), and several aerial measurements (visible, NDVI, and thermal infrared) collected in a real-world application at field scale during a dry down. Data collection surveys were conducted in 2020 the morning of 25 Feb, afternoon of 25 Feb, and morning of 27 February on three golf course fairways in CA, USA. The first survey was initiated following an irrigation event, and then no additional irrigation or rainfall occurred prior to the second and third surveys.Ground-based data were collected using the Precision Sense 6000 ™ (The Toro Company, Bloomington, MN) and aerial data were collected using an unmanned aerial vehicle (GreenSight Inc., Boston, MA). Data were appropriately georeferenced and analyzed to determine correlation between VWC and proximal NDVI, proximal and aerial NDVI, and VWC and aerial measurements. A significant, weak correlation (r = -0.21, p < .05) was found between VWC and proximal NDVI measurements, but only for the first survey immediately following the irrigation event. Significant, moderate to strong correlations were found between proximal and aerial NDVI during all three surveys (r = 0.63, p < .001; r = 0.64, p < .001; r = 0.85, p < .001), respectively]. Volumetric water content was significantly correlated with aerial NDVI measurements (r = -0.26, p < .001) but the relationship was weak and only existed for the first survey following the irrigation event. This study demonstrates the complexity of scaling remote sensing technologies from small plots to real-world applications and identifies several barriers to providing quantitatively predictive and actionable data to turfgrass managers.

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Section: Resultsmentioning

confidence: 99%

Section: Correlation Of Vwc and Proximal Ndvimentioning

confidence: 99%

Comparing ground‐based and aerial data at field scale during dry down on golf course fairways

Friell

Straw

2021

Intl Turfgrass Soc Res J

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“…The highest dose of sewage sludge (1,428 g m -2 ) positively influenced the Normalized Difference Vegetation Index (NDVI), with an average of 0.53 (Figure 2A), 39.41% higher compared to control treatment (0 g m -2 ). This index can indicate when the lawn is exposed to stresses such as trampling/compaction, utilization, and water deficit (Kerr et al, 2019;Straw et al, 2020). NDVI can be used as an alternative to evaluate the DCGI in the turfgrass (Caturegli et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Regrowth and ornamental traits of bermudagrass fertilized with sewage sludge

et al. 2020

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The sewage sludge is a low-cost material and sustainable alternative to substitute chemical fertilizers on ornamental lawns and gardens. Thus, the objective was to evaluate the effects of the application of sewage sludge on the regrowth and ornamental traits of DiscoveryTM bermudagrass. The experiment was carried out during the fall/winter of 2019. The turf was removed and left the soil exposed for a new grass regrowth. The treatments applied were 0, 357, 714, 1,071 and 1,428 g m-2 sewage sludge spread evenly on the lawn in a single dose. The evaluations were carried out after 120 days and the soil solution (EC and NO3 -), Normalized difference vegetation index, root length, root + rhizome + stolon + leaves volume and digital image analysis were evaluated. The results showed that the increase of sewage sludge positively influenced the turfgrass development, both in the aesthetic aspect and on bermudagrass regrowth. The soil solution can show that the sludge increased the electrical conductivity and NO3- ions; however, it did not hinder the development of the lawn, even having positive correlations between these variables and the biometric evaluations of the plant. It is concluded that the dose of 1,428 g m-2 presented the best results for the evaluated characteristics, being the recommended one for use in the fertilization of bermudagrass DiscoveryTM.

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“…The patterns of variation in the Temple field (Figure 7) do not seem to relate to patterns of variation in elevation (Figure 2c) which is not particularly surprising, given the unpredictable patterns of soil texture within this field. Straw et al [38] also found that the strength of relationships between soil moisture and grass health patterns can vary between fields and with different soil types. Given the elevation patterns of the field, the unexpected dry areas at the base of the slope (western side of the field Figure 7d,g) could be related to the combination of the soil texture and the management practice of applying 30% less water to the three rows of sprinklers at the base of the slope in the 2021 growing season.…”

Section: Temple Field-spatial and Temporal Patternsmentioning

confidence: 99%

Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

et al. 2023

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Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management.

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Short‐term spatiotemporal relationship between plant and soil properties on natural turfgrass sports fields

Cited by 7 publications

References 21 publications

Comparing ground‐based and aerial data at field scale during dry down on golf course fairways

Comparing ground‐based and aerial data at field scale during dry down on golf course fairways

Regrowth and ornamental traits of bermudagrass fertilized with sewage sludge

Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

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