Researchers at The Ohio State University are developing a method and software workflow for evaluating irrigation-system performance using drone-mounted thermal imaging and geospatial analysis. The approach captures thermal imagery of turf surfaces before, during, and after an irrigation cycle. The imagery is then analyzed to identify relative temperature differences associated with areas receiving more or less water.

The proposed workflow uses geographic information system software to generate maps showing the spatial distribution of warmer and cooler areas. These maps are intended to help turf managers locate uneven irrigation patterns and identify sprinklers or irrigation components that may require adjustment, repair, or further inspection. The researchers plan to validate the thermal measurements against traditional catch-can audits and soil-moisture measurements.

Initial development is progressing from individual sprinkler evaluation to replicated turf plots and anticipated testing on golf-course greens and fairways. The longer-term concept includes automated analysis and potential integration with irrigation-control software to identify sprinklers requiring attention.