Quantifying Turfgrass Cover Using Digital Image Analysis

Abstract

able and subtle differences due to treatments are difficult to identify as a result of the high variances (Murphy Accurate cover estimates in turfgrass research plots are often diffiet al., 1995). The line-intersect method is commonly cult to obtain because of the time involved with traditional sampling and evaluation techniques. Subjective ratings are commonly used to used for ecological studies in which the occurrence of estimate turfgrass cover, but the data can be quite variable and difficult plants or the distribution of plant types within a plot to reproduce. New technologies and software related to digital image are required (Laycock and Canaway, 1980; Kershaw, analysis (DIA) may provide an alternative method to measure turf-1973). The line-intersect method involves setting up a grass parameters more accurately and efficiently than current techgrid system over an entire plot or a quadrat within the niques. A series of studies was conducted to determine the applicabilplot and counting the number or types of plants found at ity of DIA for turfgrass cover estimates. In the first study, plots each intersection on the grid. The number of intersects containing a range (1-16) of bermudagrass [Cynodon dactylon (L.) where the desired plant material is found is then Pers.] plugs of specific diameter (15.0 cm) were established to repremultiplied by the area of each grid section and divided sent values of turfgrass cover from 0.75 to 12%, by 0.75% increments.by the total sample area for a percentage of each species. Digital images (1280 by 960 pixels) were taken with a digital camera and processed for percent green color to a software package. Estimates

Solar Radiation Effect on Crop Production

“…Radiometric satellite data are now available for the evaluation of large areas, and small portable radiometers are becoming less expensive as the technology progresses. In this respect, good results have been obtained with measurements using digital photographic images to determine crop cover and radiation interception in soybean (Purcell, 2000) and lettuce (Klassen et al, 2003), crop cover in turfgrass (Richardson et al, 2001), and canopy and soil cover with straw mulch (Bennet et al, 2000;Beverly, 1996;Olmstead et al, 2004). Other important points are that the area of soil exposed to the sun can be differentiated from that covered by leaves while the angle of the camera is close to that of the sun (Purcell, 2000).…”

Development of a Rapid and Precise Method of Digital Image Analysis to Quantify Canopy Density and Structural Complexity

“…Significant differences in the variability of the estimates derived using digital image analysis versus the other techniques were ascertained using a series of three F tests. In all cases, square of the differences in all 10 canopy estimates (one at each sample location) was calculated on a per-individual basis to remove location-specific effects (as per [38]). The mean canopy calculation for each sampling site, according to each method, was calculated so that methods could be compared using correlation analysis.…”

“…were processed in this way, the resultant images were not a particularly accurate representation of the true conditions, with small areas of tree being regarded as background [28]. Purcell [37] and Richardson et al [38] have used a conceptually similar approach to quantify ground vegetation cover from colour photographs by counting the number of green pixels within specific hue and saturation ranges. Again, however, there were constraints: plants in shadow were often not included, sun flecks could bias analysis, and the technique only worked with green vegetation (such that it would not work, for example, for trees in the autumn).…”

Technical Note: Lightweight Camera Stand for Close-to-Earth Remote Sensing

“…Bennett et al (2000) constructed a portable aluminum stand equipped with a collapsible camera arm and two telescopic legs. Richardson et al (2001) the vertical post to which was attached a digital camera.…”