The study area is the 400 km2 floodplain and wetlands of the upper Missouri River, located in the northwestern corner of North Dakota, near the community of Williston. Regional climate is semiarid, yet the Williston vector control agency battles large populations of Culicidae nearly every spring and summer. Best mosquito management practices (BMPs) are integrated, relying on a combination of thorough, routine, ground-based sampling and surveillance methods to provide important information on which control strategies and evaluations of effective are based. However, the mosquito breeding habitat near Williston is extensive and contains difficult terrain, which makes standard ground-based sampling and surveillance methods impractical. This study analyzed remotely sensed Interferometric Synthetic Aperture Radar (IfSAR) Digital Terrain Model (DTM) elevation data as a potential alternative for ground-based methods. Remotely sensed IfSAR technology is relative low-cost, has high-spatial resolution, is not limited by inclement weather, and only needs to be collected once if local topography remains stable. IfSAR elevation data provides information needed to model hydrological characteristics such as slope, aspect, water flow direction, and accumulation, important considerations in relation to mosquito control efforts. Predictive flood models, developed in this study from the IfSAR elevation data, make it possible to predict the locations of water accumulation within the floodplain as river elevations fluctuate. A vertical root mean squares error (RMSEz) assessment of the full IfSAR elevation data in all land cover classifications combined was 1.071 m, consistent with the vendor’s stated RMSEz of 1 meter. The vertical accuracy of the full IfSAR data was 2.099 meters at the 95% confidence level and is consistent with the 95th percentile accuracy of 2.211 meters. The frequency distribution of errors was generally normal. This study determined that airborne, high-resolution IfSAR DTM-elevation data can serve as an alternative for ground-based sampling and surveillance methods and provide a needed decision support system (DSS) tool to the local vector control agency. The predictive flood models are a new approach for predicting the locations of accumulated water within the floodplain will decrease vector control response time and improve the targeting of site-specific control efforts, which in turn, will decrease overall costs for these services.