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The Centre for lifelong learning of the Cyprus University of Technology, in collaboration with the Department of Civil Engineering and Geomatics, is organizing a professional continuing education program titled:

"UAS Data Collection and Processing"

Program Overview

The "Data Collection and Processing with UAS" program addresses a broad spectrum of professionals working in fields such as environmental sciences, geosciences, Geographic Information Systems (GIS), 2D-3D mapping, geovisualization, multispectral data for crop monitoring, remote sensing, vegetation indices, and more.
Its goal is to train and upskill participants—both specialists and other interested individuals—in the use of Unmanned Aerial Systems (UAS) as data collection tools.

While the commercial development of UAS has largely been driven by their widespread use among the general public for photography and videography, their utility in scientific data collection across numerous applications remains underutilized.
This program aims to raise awareness about the capabilities of UAS as modern tools for rapid data acquisition and environmental documentation, with the goal of optimizing decision-making processes across a variety of scientific domains.

Target Audience

The program is intended for professionals and researchers in fields related to the environment, forestry, agriculture, archaeology, climate change, crisis management, and various branches of engineering (including Surveying, Civil, Mining, Architecture, Electrical Engineering, among others).

Basic computer skills are required.

Course Modules

1. Introduction to UAS
Types of UAS and their applications. Basic flight principles and data collection techniques. Flight regulations and safety protocols.

2. Photogrammetry and 3D reconstruction
Fundamentals of photogrammetry. Data collection workflows using UAS. Processing photogrammetric data to produce 3D models. Applications of 3D modeling in mapping.

3. Geographic Information Systems (GIS)
Introduction to GIS and its role in mapping. Management and processing of spatial data. Creation and analysis of thematic maps.

4. Remote Sensing and Multispectral Imaging
Principles of remote sensing. Uses and applications of multispectral data. Processing UAS-derived remote sensing data. Vegetation indices and environmental analysis. Calculating indices from multispectral imagery. Assessing vegetation and environmental changes.

5. Geovisualization and Map Creation
Concepts and principles of geovisualization. Techniques for visualizing UAS data in mapping spatiotemporal phenomena. Synthesis of thematic maps for specialized applications. Online and immersive (VR-AR) 2D-3D data visualization.

6. Practical Application and Tools
Hands-on experience with software tools. Case study: from data collection to mapping. Troubleshooting and data optimization. Visualizing an area using UAS data—from acquisition to final mapping. Open-source software will be used for instructional purposes.

7. Specialized UAS Applications
Precision agriculture data applications. Use in geology and natural resource management. Environmental monitoring and disaster management.

Learning Outcomes – Competencies Acquired Upon Completion

Knowledge-Based Outcomes

• Identify and categorize the advantages and limitations of UAS depending on the application.
• Correlate UAS applications across sectors such as environment, archaeology, infrastructure mapping, 3D digital twins, agriculture, etc.
• Enumerate the steps involved in post-processing and recognize its importance in UAS data analysis.
• Describe techniques used for processing spatial data obtained through UAS flights.
• Outline procedures and techniques for generating digital elevation models (DEMs) and complete 3D models from UAS data.
• Classify multispectral data for creating vegetation index maps.
• Distinguish between different types of UAS-collected data, including geographic, multispectral, and navigational data.

Skills-Based Outcomes

• Design UAS missions for data collection, adjusting flight parameters based on specific requirements.
• Organize and manage the data and information collected.
• Explain the procedures and techniques used in creating 3D models and maps.
• Select appropriate software and tools for UAS data processing (e.g., GIS, image processing software), justifying their choices.
• Justify each processing step, articulating its importance and role in the broader workflow.

Competency-Based Outcomes

• Provide rationale for decisions made during UAS flight planning and execution, explaining flight parameters and optimization techniques.
• Encourage peers to adopt new technologies and data processing methods, promoting innovation and continuous improvement.
• Collaborate effectively with professionals such as UAS pilots, geographers, and engineers to exchange knowledge and achieve shared objectives.
• Critically assess and analyze collected data, identifying errors or limitations and suggesting improvements.
• Actively participate in group projects and discussions, contributing knowledge and skills toward problem-solving.
• Compare and contrast different data processing methods and techniques, evaluating the advantages and disadvantages of each.