(Figure 1) and compared battery life, image resolution, and processing time from different software. Jing then further analyzed the images using geospatial software and experimented with various ways to characterize certain problems in the field based on the drone images. Tese included assessing flood damage, field uniformity, and shade pressure.


One case study originating from these collaborations was the assessment of flood damage in one of Super- Sod’s North Carolina tall fescue production fields. Te overall farm was about 230 acres and the total area that was impacted by the standing water was quantified (~72 acres) based on the drone images taken several weeks after flooding (Figure 2). Te impacted area was very hard to


Figure 3.


measure from the ground because of its irregular shape, but damage assessment was needed to determine crop loss for insurance purposes. It is worth mentioning that in this case the areas of interests were visually confirmed by the grower and the precise estimate of economic loss was used in the decision to abandon this field.


Similarly, drones can be used to monitor establishment following sprigging, regrowth following harvest, and to assess the efficacy of herbicide applications. Beyond the regular digital images, multispectral sensors provide a more robust understanding of plant health. During 2018, the most commonly used vegetation index, normalized difference vegetation index (NDVI), was used to estimate the uniformity and productivity in a seeded centipedegrass field at Patten Seed (Figure 3).


Figure 3. Production field of seeded centipedegrass. Left: digital RGB image; Right: NDVI image.


44


TPI Turf News March/April 2019


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