GIS-Enabled Truck–Drone Hybrid Systems for Agricultural Last-Mile Delivery: A Multidisciplinary Review with Insights from a Rural Region

Efficient last-mile delivery remains a critical challenge for rural agricultural logistics, globally, particularly in cold-climate regions with dispersed agricultural operations. Truck–drone hybrids can reduce delivery times but face payload limits, cold-weather battery loss, and beyond-visual-line-of-sight regulations. This review evaluates the potential of GIS-enabled truck–drone hybrid systems to overcome infrastructural, environmental, and operational barriers in such settings. This study uses the state of North Dakota (USA) as a representative case because of its cold climate, low density, and weak connectivity. These conditions require different routing and system assumptions than typical regions. The study conducts a systematic review of 81 high-quality publications. It identifies seven interconnected research domains: GIS analytics, truck–drone coordination, smart agriculture integration, rural implementation, sustainability assessment, strategic design, and data security. The findings stipulate that GIS enhances hybrid logistics through route optimization, launch site planning, and real-time monitoring. Additionally, this study emphasizes the rural, low-density context and identifies specific gaps related to cold-weather performance, restrictions to line-of-sight operations, and economic feasibility in ultra-low-density delivery networks. The study concludes with a roadmap for research and policy development to enable practical deployment in cold-climate agricultural regions.