UAV, PHOTOGRAMMETRY, GIS, AND DIGITAL TWIN IN AGRICULTURE – A THEORETICAL APPROACH

Abstract

The rapid advancement of remote sensing and spatial analysis technologies has led to a profound transformation of agricultural practices, fostering the transition toward precision, sustainable, and resource-efficient agriculture. In this context, unmanned aerial vehicles (UAVs) have become essential tools for acquiring high-resolution data, which, through advanced photogrammetric processes, can be converted into complex geospatial products—orthophotos, digital terrain models (DTMs), and detailed three-dimensional models. The integration of these products into geographic information systems (GIS) facilitates spatial and temporal analyses of agricultural crops, providing decision support for integrated farm management. Furthermore, the evolution toward the concept of the agricultural Digital Twin enables the creation of dynamic digital replicas of fields and crops, updated in real time with data collected from UAVs, IoT sensors, and satellite sources. These models allow the simulation of agronomic scenarios, optimization of irrigation, fertilization, and crop protection processes, as well as the prediction of yield performance.
This paper presents an integrated analysis of how UAVs, photogrammetry, GIS, and Digital Twin technologies can be combined into a coherent workflow for data acquisition, processing, and interpretation, with a particular focus on their applicability in agriculture. The discussion addresses technical advantages, implementation challenges, and future research directions concerning the standardization and interoperability of these technologies. The conclusions highlight the significant potential of these tools to enhance efficiency, reduce costs, and promote a sustainable, data-driven agricultural paradigm.