IrriDrone: Overhead drone-based video dataset for precision sprinkler irrigation assessment

Efficient water management in agriculture is a growing concern due to increasing water scarcity and over-reliance on groundwater resources. Despite advances in remote sensing and drone-based monitoring, the lack of standardized and publicly available datasets for vision-based sprinkler irrigation analysis has limited progress in the development of data-driven irrigation management systems. In this work, we present IrriDrone, a new dataset comprising aerial videos and corresponding quantitative water-discharge measurements collected from real-world sprinkler irrigation operations in carrot, potato, and alfalfa fields. Three operational pressure conditions were established by simultaneously operating 3, 6, or 9 sprinklers under an unchanged pump setting, representing high, intermediate, and low pressure per sprinkler, respectively; the corresponding discharge rates were determined in liters per second using a repeated volumetric measurement. The dataset captures variations in sprinkler configuration, drone flight altitude (35, 45, and 55 m), and time of day, and includes GPS metadata and paired video versions with and without manually defined circular overlays representing the irrigation spray boundaries. By providing aerial visual data together with corresponding quantitative irrigation measurements, the dataset supports the development and evaluation of machine learning and computer vision methods for irrigation monitoring and precision water management. The dataset includes continuous recordings covering sprinkler rotations, allowing flexible temporal segmentation for diverse downstream research tasks. To the best of our knowledge, IrriDrone is among the first publicly available datasets to combine overhead drone video with corresponding water-discharge measurements under real agricultural conditions.