Remote Sensing and Data Analysis

This module (COMP11131) provides a comprehensive introduction to remote sensing and data analysis using drones, with a focus on real-world applications in precision agriculture, environmental monitoring, construction, and infrastructure assessment.  Students will learn the complete workflow of drone-based data acquisition, processing, and visualisation, equipping them with the skills needed to handle and analyse complex datasets.

The module emphasises practical, hands-on learning, utilising professional software tools and Python programming for data processing and analysis.  Students will be guided through the basics of Python, making the module accessible even to those without prior programming experience.  The course will also explore emerging technologies such as machine learning applications in remote sensing and data fusion techniques, preparing students to innovate and adapt to the rapidly evolving field of geospatial analysis.

The assessment comprises an individual project and a group project, where students develop tools for real-world data analysis problems.

The module will cover:

• Remote sensing principles and applications
• Drone sensors and data capture techniques
• Python programming for data analysis and processing
• Structure from Motion (SfM) and 3D reconstruction
• Photogrammetry and orthophoto-mosaic generation
• Machine learning for remote sensing and classification
• Object detection and segmentation using deep learning
• Data fusion and advanced visualisation techniques
• Real-world case studies

On successful completion of this module the student will be able to:

• Understand and apply the fundamental principles of remote sensing, including the operation of various mapping and imaging sensors and the use of reconstruction techniques (e.g., Structure from Motion) to produce accurate georeferenced datasets.
• Develop and utilise Python programming skills to analyse, process, and visualise remote sensing data, including the integration of multiple datasets and the application of machine learning models for data classification and object detection.
• Critically evaluate and solve complex remote sensing challenges by integrating theoretical knowledge with practical project management, culminating in the development, presentation, and peer review of a comprehensive remote sensing project.

This is an SCQF Level 11 module and upon successful completion, participants will be awarded 20 credits.

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

 

Delivery 

This module will be scheduled to run in September 2026 over 12 weeks, at the Lanarkshire campus.  Timetable to be confirmed.

 

Course presenter

This module will be delivered by Prof James Riordan.

 

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.