Navigation, mapping and geospatial data analysis in precision agriculture


Masiero Andrea Masiero

Andrea Masiero

University of Padova, Italy

Baiocchi Valerio Baiocchi

Valerio Baiocchi

Sapienza University of Rome, Italy

Radicioni Fabio Radicioni

Fabio Radicioni

University of Perugia, Italy


Precision agriculture includes several methodologies based on the development and availability of sensors and tools for crop monitoring and for designing actions and strategies to optimize agriculture returns and the use of fertilizers and pesticides. A key role in the development of such methodologies is played by the use of multi-sensor data in order to properly assess the health and status of crops in the all area of interest. From this point of view, ensuring precise localization and navigation in the all area of interest is of remarkable importance, fully exploiting GNSS technology and the techniques recently developed in order to partially compensate for the unreliability of GNSS in certain critical conditions. On the other hand, multi-sensor data georeferencing and analysis is the key step for improving both agriculture results and its environmental sustainability.


This special issue focuses on contributions dealing with several topics related to:

  • Localization techniques in precision agriculture: GNSS, IMU, and SLAM-based;
  • Georeferencing and co-registration of proximity sensor data, such as thermal/multi/hyper-spectral cameras, installed on terrestrial/aerial vehicles;
  • Geomatics and machine learning methods for the analysis of precision agriculture-related georeferenced spatial data;
  • Positioning and navigation tools for the control of farm operations including driving and steering of tractors;
  • Remote sensing and photogrammetric methodologies for supporting crop monitoring, optimized fertilizer distribution, evaluation of yields, and event-based irrigation control.


Dr. Andrea Masiero, is Associate Professor of Geomatics at the TESAF Department of the University of Padua. From 2020 to 2023 he was Associate Professor at the Department of Civil and Environmental Engineering of the University of Florence. He received his MSc Degree in Computer Engineering and his PhD degree in Automatic Control and Operational Research from the University of Padua. His research interests range from Geomatics, Mobile Mapping, Positioning and Navigation, Machine Learning to Computer Vision, Smart Camera Networks, modeling and control of Adaptive Optics systems. His research mainly focused on sensor integration and information fusion, positioning, photogrammetry, LiDAR data processing, visual and LiDAR odometry, remote sensing, statistical and mathematical modelling, machine and deep learning.

Dr. Valerio Baiocchi, is Geologist and Engineer, both full Graduation at the Sapienza University of Rome, one of the oldest university of Europe, with top marks. He obtained a Ph.D. in Geodesy and survey, at Parthenope University, Napoli, Italy (1996-1999), a Master in Environmental sciences (Scuola di specializzazione), at Urbino University, Italy (1995-1997), and a second Ph.D. in Infrastructures and transports, at the Sapienza University of Rome (2006-2009). He currently is Associate Professor of Geomatics at the Department of Civil, Constructional and Environmental Engineering of the Sapienza University of Rome.

Dr. Fabio Radicioni, received a PhD in Geodetic Sciences in 1988 and he currently is Full Professor of Geomatics at the Department of Engineering - University of Perugia. He deals with Applications of GNSS techniques for positioning, navigation and timing. In recent years, he has been involved in the use of the NRTK GNSS technique for driving and controlling vehicles, monitoring fleets, controlling construction machinery and for precision agriculture, and PPP and PPP-RTK techniques with low cost multi-constellation multi-frequency GNSS sensors and their IMU data fusion. He designed and implemented the GNSS Umbria regional network, capable of transferring network real-time differential corrections (Phase/Code) of all global satellite constellations with new signals for a wide range of technical and scientific applications.