Digital Image Analysis Using Aerial Imagery to Quantify Spring Dead Spot.

Accurate, affordable disease incidence mapping has the potential to provide improved management options of turf diseases. Spring dead spot (SDS) of bermudagrass (Cynodon dactylon) weakens plants in the fall, making the turf more susceptible to localized winterkill during cold, dry periods. Symptoms can persist into summer months, making SDS a significant disease of bermudagrass in regions where bermudagrass enters winter dormancy. Suppression of SDS is often unreliable with current management strategies and our understanding of the disease’s epidemiology. Unmanned aerial vehicles (UAV) provide rapid and inexpensive aerial imagery of large acreage. Generating maps using aerial imagery to document SDS epidemics has proven to be successful for targeting fungicide applications based on geographic severity and limiting total treated acreage. However, the most feasible method for using disease maps currently relies on visual interpretation to assist with management decisions. Digital image analysis (DIA) of these maps is one potential solution to improve disease incidence accuracy and precision of fungicide applications. This study investigates using DIA of aerial imagery to quantify spring dead spot occurrence and isolate key management zones. Aerial imagery and ground-validation data were collected in the spring of 2016 and 2017 from six ‘Vamont’ bermudagrass fairways with a high SDS occurrence in Richmond, Virginia. Raw images were mosaicked and geo-rectified with known ground reference coordinates to create continuous coverage across fairways. Geographic coordinates of approximately sixty SDS patches were overlaid with mosaicked imagery to assess for accuracy. Image resolution was reduced and pixels were classified as SDS when digital values were below 0.5 standard deviation of plot averages. Classified digital values within eighty 33 m² plots were used to compare SDS incidence against visual estimations from 2016 to 2017. This research demonstrates a viable option to objectively assess SDS distribution and severity across seasons.