Advanced Drone Technology for Agricultural Applications
Master advanced UAV sensing techniques and data analysis for precision agriculture, including multispectral, thermal, and LiDAR technologies.
Master advanced UAV sensing techniques and data analysis for precision agriculture, including multispectral, thermal, and LiDAR technologies.
This comprehensive course explores the cutting-edge applications of drone technology in agriculture. Students learn about various advanced sensing systems, including multispectral, hyperspectral, thermal, and LiDAR technologies, and how to transform this data into actionable crop management decisions. The course combines theoretical knowledge with hands-on exercises, enabling participants to design and implement data processing workflows for specific agricultural scenarios. Through practical experience and detailed instruction, students learn to interpret data from different sensors, choose appropriate solutions for their needs, and optimize crop management while conserving resources. The verified track offers additional materials on future sensing approaches and personalized feedback on data processing choices.
Instructors:
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What you'll learn
Understand different UAV sensing systems and their operational principles
Interpret data from various advanced sensors including multispectral and LiDAR
Design and implement processing workflows for different types of UAV data
Evaluate and improve UAV data analysis results
Apply advanced sensing techniques to specific agricultural scenarios
Optimize crop management using drone-based data collection
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 2 modules in this course
This innovative course delves into advanced drone sensing technologies and their applications in precision agriculture. The curriculum covers different sensing systems, data interpretation, and practical implementation through two comprehensive modules. Students learn about various sensor types, their operational principles, and specific agricultural applications. The course emphasizes hands-on experience with data processing workflows, enabling participants to adapt analysis techniques to their unique farming scenarios.
Advanced remote sensing with UAVs
Module 1
UAV data processing in practice
Module 2
Fee Structure
Instructors
1 Course
Remote Sensing and Precision Agriculture Expert
Sergio Vélez serves as a Postdoctoral Researcher at Wageningen University & Research, where he specializes in developing innovative remote sensing applications for precision agriculture. After earning his PhD with cum laude honors, he has established himself as an expert in using multispectral imagery and UAV technology for woody crop management. His current work within the Flexigrobots project focuses on developing advanced techniques for disease detection and crop monitoring using UAVs and artificial intelligence. His research has produced significant findings in mapping disease risks in vineyards using UAV multispectral imagery and developing novel methods for estimating canopy volumes in tree crops. With over 15 years of experience in the food production sector across multiple countries including Spain, Argentina, France, and South Africa, he brings a global perspective to precision agriculture research. His recent work includes pioneering studies in real-time crop disease detection, object detection and tracking in precision farming, and the development of high-resolution UAV RGB imagery datasets for agricultural applications. Through his research and international collaborations, he continues to advance the field of precision agriculture, particularly focusing on the integration of UAV technology and artificial intelligence for improved crop management and disease detection.
1 Course
Remote Sensing Pioneer and UAV Technology Expert
Harm Bartholomeus serves as Assistant Professor of Remote Sensing at Wageningen University's Laboratory of Geo-information Science and Remote Sensing, where he has established himself as a leading expert in environmental remote sensing applications. After completing his MSc in Physical Geography from Utrecht University in 2000, he earned his PhD from Wageningen University in 2009, focusing on spectroscopic estimation of soil properties. His research combines multiple sensing technologies, including imaging spectroscopy, LiDAR, and UAV-based systems, to advance environmental monitoring in forestry, soil science, and climate studies. In 2012, he co-founded the Wageningen UR Unmanned Aerial Remote Sensing Facility (UARSF), which has become a hub for innovation in UAV-based environmental research. His work has garnered over 8,400 citations, with significant contributions to forest inventory methods using terrestrial LiDAR, development of lightweight hyperspectral mapping systems, and evaluation of UAV-LiDAR systems for measuring forest structure. Through his leadership at UARSF and research initiatives, he continues to advance the application of remote sensing technologies in environmental monitoring, particularly focusing on the integration of multiple sensing modalities for comprehensive ecosystem assessment.
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