Mapping natural variability of crops and land is first step of the management cycle in terms of crop production. Several methods have been developed and engaged for data recording and analyzing that generate prescription maps such as yield monitoring, soil mapping, remote sensing etc. Although conventional remote sensing by capturing images via satellites has been very popular tool to monitor the earth surface, it has several drawbacks such as orbital period, unattended capture, investment cost. On the contrary, unmanned air vehicle (UAV) is more flexible in terms of deploying, monitoring small area and easy to acquire at low cost.

In this aspect, the objective of this study was to develop a low-cost and easy to implement technical solution to map spatial variability, and to explore its relationship with crop conditions. The idea was to build a close loop process starting from a standardized UAV based image shooting till an easy but reasonable production of NDVI and derived/prescription maps especially for vineyards.

The main components of this image acquisition system are Unmanned Air Vehicle (UAV) and modified commercial digital camera. Within the study, 3 different UAV (2 fixed wings and one flying wing) have been built, based on commercial airplanes models fitting the purpose and used open source autopilot. As sensors, 2 small format digital cameras (1 Nikon and 1 Canon) have been tested, part of them modified in order to be able to acquire also NIR radiations.

Laboratory tests were conducted in order to calibrate the cameras. After all, UAV based image acquisition system was developed. Future tests were planned for the assessment of practical usage in situ.