Remote Sensing and Data Analysis

This practical CPD course is designed for engineers, environmental professionals, geospatial specialists, surveyors, construction professionals, and data analysts seeking to develop expertise in drone-based remote sensing and geospatial data analysis. It provides a comprehensive introduction to data acquisition, processing, visualisation, and interpretation using industry-standard tools and emerging technologies.

Participants will gain hands-on experience in remote sensing workflows, Python programming, photogrammetry, machine learning, and advanced data analysis techniques, developing skills that can be applied across sectors including environmental monitoring, infrastructure management, construction, and precision agriculture.

To view the module descriptor (COMP11131), please visit Programme Specifications and Module Descriptors 

 

Who is this course for?

This course is suitable for:

• Engineers seeking to develop geospatial and remote sensing capabilities
• Environmental professionals involved in monitoring, assessment, and data collection
• Surveyors and GIS practitioners working with spatial data and mapping technologies
• Construction and infrastructure professionals using drone-based data for planning and inspection
• Data analysts interested in geospatial datasets and advanced visualisation techniques
• Professionals looking to develop practical Python programming skills for data processing
• Individuals seeking to understand how machine learning can be applied to remote sensing challenges

 

Why take this course?

The use of drones, remote sensing technologies, and geospatial data is transforming industries ranging from environmental management and agriculture to infrastructure inspection and urban planning. Organisations increasingly require professionals who can capture, process, analyse, and interpret large and complex datasets to support evidence-based decision-making.

This course provides practical experience with contemporary remote sensing technologies and analytical tools while introducing emerging techniques such as machine learning and data fusion. Participants will develop valuable technical skills that can support innovation, improve operational efficiency, and enhance decision-making within their professional practice. 

 

What will you learn

By the end of this course, you will be able to:

• Understand and apply the fundamental principles of remote sensing and geospatial data acquisition
• Evaluate the operation and application of drone-based mapping and imaging sensors
• Use reconstruction techniques to produce accurate georeferenced datasets
• Develop Python programming skills for processing, analysing, and visualising remote sensing data
• Integrate multiple datasets and apply machine learning techniques to support classification and object detection
• Critically evaluate remote sensing challenges and develop practical solutions using industry-standard tools and methodologies
• Plan, manage, and communicate complex remote sensing projects and analytical outputs

 

How will you learn

This course combines live teaching, practical workshops, laboratory activities, project-based learning, and independent study to develop both technical knowledge and hands-on analytical skills.

You will learn through:

• Tutor-led sessions introducing remote sensing principles, technologies, and applications
• Practical laboratory workshops using professional software and drone-derived datasets
• Guided Python programming exercises for data processing and analysis
• Activities focused on photogrammetry, data visualisation, and geospatial modelling
• Exploration of machine learning and artificial intelligence applications in remote sensing
• Real-world case studies demonstrating how remote sensing supports decision-making across industries
• Individual and collaborative project work addressing authentic data analysis challenges

 

Course content

The course explores the technologies, workflows, and analytical techniques used within contemporary remote sensing and geospatial data analysis.

• Foundations of Remote Sensing
• Drone Data Acquisition and Processing
• Photogrammetry and 3D Reconstruction
• Python for Data Analysis
• Machine Learning and Artificial Intelligence
• Data Fusion and Advanced Visualisation
• Applied Remote Sensing Projects

 

Assessment

Assessment is designed to help you apply remote sensing and data analysis techniques to realistic professional challenges.

You will complete an individual project supported by a portfolio of practical laboratory reports that demonstrate your ability to capture, process, analyse, and interpret remote sensing data. This project will allow you to apply Python programming, photogrammetry, machine learning, and data visualisation techniques to a real-world analytical problem.

You will also participate in a collaborative group project where you will work with others to integrate datasets, develop analytical tools or models, and present findings through a professional report and presentation.

Through the assessment, you will develop your ability to:

• Apply remote sensing methodologies to practical problems
• Process and analyse complex geospatial datasets
• Use Python programming to automate and enhance analytical workflows
• Apply machine learning techniques to classification and object detection challenges
• Communicate technical findings effectively to different audiences
• Collaborate successfully within multidisciplinary project teams

The assessment focuses on practical application, technical problem-solving, innovation, and professional relevance.

 

Applying your learning

Throughout the course, you will:

• Work with real-world remote sensing datasets and analytical challenges
• Develop practical skills in data capture, processing, and visualisation
• Apply Python programming techniques to solve complex analytical problems
• Explore machine learning approaches for classification and object detection
• Develop project management and communication skills through individual and group projects
• Build confidence in using industry-standard software and analytical tools

You will leave with:

• A strong understanding of remote sensing technologies and applications
• Practical experience in geospatial data processing and analysis
• Enhanced Python programming and data science skills
• Knowledge of photogrammetry, machine learning, and advanced visualisation techniques
• Greater confidence in managing and delivering data-driven projects
• Skills that can be applied across engineering, environmental, construction, infrastructure, and geospatial sectors

 

Entry requirements

There are no formal entry requirements for this course.

The course is suitable for professionals from engineering, environmental, construction, infrastructure, surveying, geospatial, and related disciplines who wish to develop specialist knowledge in remote sensing and data analysis.

Participants should be prepared to engage with practical technical activities, data analysis exercises, project work, and independent study at SCQF Level 11. Previous programming experience is not required, as introductory support for Python programming is incorporated into the course.

 

Certification

Upon successful completion, participants will be awarded 20 credits at SCQF Level 11.

These credits may contribute towards further postgraduate study where appropriate and in line with University regulations.

 

Funding 

A limited number of fully funded places are available, supported by the Digital Dairy Chain – a regional initiative focused on driving innovation, sustainability and skills development across the dairy sector. 

These funded places aim to support participants from the dairy supply chain to build capability in remote sensing and data analysis. 

Applicants must be resident in or employed in East, North, South Ayrshire; North, South Lanarkshire; Renfrewshire; East Renfrewshire; Glasgow City; Inverclyde; Dumfries and Galloway.

If you have any questions, please contact us at cpd@uws.ac.uk.

 

Sector and workforce relevance

This course reflects current industry practice in remote sensing, drone-based data acquisition, geospatial analysis, and data-driven decision-making. The content is informed by contemporary applications across sectors including engineering, environmental monitoring, construction, infrastructure management, precision agriculture, and spatial analytics.

Through the use of professional software tools, practical project work, Python programming, machine learning techniques, and real-world case studies, participants will develop skills that align closely with the capabilities increasingly sought by employers operating within geospatial, engineering, environmental, and technology-focused industries.

 

NOTE: This is a university module and upon approval of your application, you will be invited to register and then supported to complete enrolment. To enrol on the university system, the first step involves security set-up using the Microsoft Authenticator app; you will need to ensure that you have a compatible smartphone.

Further enrolment information is available at the Student Information Portal.

To access this module via the CPD route, individuals should be ordinarily resident in Scotland.