Drone-in-a-Box (DiaB) systems provide an automated remote sensing solution by integrating uncrewed aerial systems (UAS) with weather-resistant docking stations and cloud-based data processing. This architecture enables continuous operation, automated mission execution, and the generation of near real-time data products through combined onboard and cloud-based workflows. This offers significant new potential across a wide range of applications, including environmental monitoring, infrastructure inspection, emergency response, sustainable forestry, and precision agriculture. The objective of this study was to calibrate and evaluate the geometric performance of a novel multispectral DiaB system. A primary geometric processing pipeline was implemented, incorporating high-precision GNSS/IMU-based positioning and rigorous system calibration. The system’s performance was assessed in controlled test field conditions and in operational forestry environment. The results demonstrated that the system was capable of achieving cm-level geometric accuracy and reliable photogrammetric processing without the use of <em>in situ</em> ground control points when bundle block adjustment is applied. Direct georeferencing provided dm-level accuracy. The findings indicate that the proposed system enables efficient and reliable data acquisition, while current limitations of its fully autonomous use are primarily related to data transfer constraints affecting real-time processing capabilities.