MSc Satellite Data for Sustainable Development

This practical-based class provides a thorough introduction to the rapidly growing field of Geographical Information Science. The class covers the key theoretical principles but also provides many computer-based exercises using current state-of-the-art Geographical Information Systems (GIS) – namely IDRISI and ArcGIS. The class evaluates how GIS can be used for spatial query and analysis, while at the same time assessing the quality and the effectiveness of the resultant products in terms of their use. Teaching staff: Dr Elsa João

This class is designed to provide students with an understanding on available satellite datasets, their characteristics, processing and visualisation methods and tools, descriptive analytics methods. The class is designed to provide theoretical foundations, as well as hands on exercises.

This class is designed to provide the students with the theoretical and practical foundations on the applications of machine learning methods to satellite data for prediction, classification, clustering and time series analysis.

The class introduces the UN’s 17 Sustainable Development Goals and will explore in depth multidisciplinary perspective of responding to the challenges of four particular goals, namely: SDG 3 Good Health and Wellbeing, SDG6 Clean Water and Sanitation, SDG 10 Reduced Inequalities and SGD 13 Climate Action. Through focused study of these four SDGs, students will gain an understanding of the different ways in which various disciplines in Business, Engineering, Humanities and Social Sciences, and Science, can contribute to addressing these challenges. 

The second part of the course, that will run in parallel with the first one, is focused on providing students with a practical understanding of the application of satellite data to SDGs and the  sustainability of data gathering itself. This articulates in a series of invited lectures from academics from other departments, private practitioners and governmental representatives; and a series of tutorials where notable success stories on the topic will be analysed and discussed in terms of results achieved, impact and technology demonstrated.

60 credits, during Summer and Sept Semester

In addition to taught modules, students are expected to conduct an individual research project which may be an industry-themed project or one aligned to engineering research at Strathclyde. Students can also self-propose projects if there is any application of satellite data that they are really interested in exploring further.

This class aims to provide engineers and scientists with a better understanding of what it takes to create and grow technology-based businesses. Specifically it aims to provide you with:

• an appreciation of the intrinsic value of entrepreneurship, innovation and commercialisation activities to business
• a set of frameworks to better understand and more successfully engage in high-tech business opportunities
• a better appreciation and understanding of management in a complex, uncertain and interdisciplinary high-tech business environment

This class is designed to provide a practical introduction to business modelling and understanding how new ventures are developed. The class is multi-disciplinary in nature and integrates within it the main business disciplines. It focuses upon the processes within new businesses but draws comparisons with larger organisations and as such introduces a more entrepreneurial approach to the career patterns of individuals who pursue careers in larger organisations.

The class will not follow the more traditional lecture pattern but will be highly interactive with class participants being involved in individual and group activities which will encourage creative thinking and 'learning by doing' in addressing the real opportunities and challenges that face the first-time entrepreneur.

This class considers the nature of business planning and deals with the business planning process. It is a project-based course in which students, working in small groups, research and develop a business plan for a new venture. Students will select a business idea and develop it into a business model. In the final weeks of the course, each group will showcase a video presentation of their plan and will be questioned by an 'enterprise panel' about aspects of this business model.

This module provides students with skills relating to the use of engineering practices in Project Management with particular respect to the effective and efficient use of resources. The syllabus includes an introduction to project management techniques and project control, project networks including critical path analysis, procedural and graphical presentation techniques, an introduction to Contract Law and project budgetary control.

Under Health and Safety legislation, and under the wider European Post-Seveso Directives, it is mandatory for many industries to carry out risk assessments with the aim of showing that risk is As Low As Reasonably Practicable. This module introduces the fundamental techniques of risk analysis and risk-informed decision making. Students will learn the general principles of methods and their place in risk management, as well as the chance to develop skills in applying these methods to variety of engineering examples.

The aim of this module is to give students:

• an understanding of the new challenges posed by the advent for big data, as they refer to its modelling, storage & access
• an understanding of the key algorithms & techniques which are embodied in data analytics solutions
• an understanding of the fundamentals of Python to enable the use of various big data technologies
• an understanding of how classical statistical techniques are applied in modern data analysis
• an understanding of the potential application of data analysis tools for various problems & appreciate their limitations

The aim of this class is to equip students with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how to apply the techniques. The class will teach the students how to:

• understand the aims & fundamental principles of machine learning
• understand a range of the key algorithms & approaches to machine learning
• apply the algorithms covered & interpret the outcomes
• understand the applicability of the algorithms to different types of data & problems along with their strengths & limitations

This module builds on a basic understanding of the relational database approach, covering more complex SQL query design and efficient execution, as well as transactional design using database triggers/stored procedures or by embedding SQL code within other programming environments. Upon completion you will:

• display knowledge of declarative versus procedural approaches to access databases and the relative benefits/costs associated with each
• display skill to construct complex SQL queries
• demonstrate the ability to utilise triggers/stored procedures within a commercial database management platform
• understand how to appropriately embed SQL queries within other programming languages and environments
• display an appreciation for the importance of database indexing in the context of supporting complex queries on big data
• display knowledge of transactional processes within database systems and understand their relevance to code design and execution

This module aims to ensure that you're aware of the legal, social, ethical and professional issues commensurate with the practice of Information Systems Engineering.

On completion of the module, you'll be able to:

• appreciate the characteristics of professionalism as it relates to modern data management
• recognise and appreciate the professional aspects of other modules in the course, and how those aspects influence practice
• form a sound basis on which you'll subsequently be able to practise Information Systems Engineering with a due regard for legal, ethical and social issues

The aims of this class are to help you:

• display knowledge of the process of designing a database system, starting from an informal specification
• display skill in formulating database queries using SQL
• show an appreciation of the facilities and services which should be provided by a fully featured database management system
• demonstrate knowledge of commonly occurring data models

This module will enhance your understanding of the challenges posed by the advent of Big Data and will introduce you to scalable solutions for data storage and usage.

You can expect to learn about:

• the design and implementation of cloud NoSQL systems
• addressing design trade-offs and their impact
• the Map-Reduce programming paradigm

This module will provide you with conceptual and practical understanding of data modelling, database design, and database technology. You’ll gain an in-depth understanding of key database concepts underpinning big data tools and technologies. After completing the module you'll:

• understand the process of designing a database from an informal business specification
• be able to formulate database queries using SQL
• understand the facilities and services that should be provided by a fully featured database management system
• understand commonly occurring data models
• have experience of using a relational database management system in a client-server environment

We generally use Glasgow as a living laboratory for our studio project. Our City is an example of  a European metropolis experiencing change and globalisation,. You will learn to develop appropriate strategies for resilient sustainable urban development, encompassing social, political, economic, environmental, architectural, aesthetic and psychological aspects. You'll work on the design of a complex urban area, generally on commission of a real client (local authority, housing association, community group or private developer). In addition you'll work at the interconnected levels of the entire city, the neighbourhood and the individual public space defined by urban architecture.

Studio meets once a week in Semesters 1 and 2 with design development work taking place between sessions. You'll work in multidisciplinary teams of architects, planners, geographers and economists, in the same way you'll do in practice. Work is fast-paced but also in-depth. You'll have considerable responsibility (ie presenting to clients and organising public events), but it is also a lot of fun.

You'll look at the impact of the urban landscape on human wellbeing and perception and the role of ecological networks as an integral part of urban form.

We'll cover the impact of growth on social, economic and environmental sustainability.

In this class, run by the Department of Civil and Environmental Engineering, you'll gain the knowledge and skills on atmospheric pollution and climate change impacts, ranging from local to global scales. The class includes a focus on the assessment and management of environmental impacts on people through the interface between environmental science and engineering activities that mitigate environmental risks. Learning objectives are assessed through a formative portfolio covering the main syllabus areas. Student interaction is encouraged throughout the class through structured feedback sessions, directed reading, student-led question sessions & directed questions sessions.

Environmental impact assessment (EIA) relates to the process of identifying, evaluating, and mitigating the biophysical, social, economic, cultural and other relevant effects of development proposals prior to major decisions being taken and commitments made. This class, run by the Department of Civil & Environmental Engineering but open to all MSc and MEng students across the University, introduces the methods used to predict environmental impacts, and evaluates how these may be used to integrate environmental factors into decisions.

The class draws principally on the UK planning context of environmental impact assessment of individual projects (project EIA), but also takes account of EIA experience in other countries and international organisations. Participants evaluate the quality of Environmental Statements (or EIA Reports) and of the EIA process using the Institute of Environmental Management and Assessment (IEMA) methodology.

The class discusses how EIA can be used a pro-active design tool for projects and how it can contribute to the enhancement of environmental, social and health issues. Students are also introduced to key principles of Strategic Environmental Assessment (SEA) and biodiversity net gain (BNG). Class has the contribution of key practitioners in the field and includes different case studies, such as proposed onshore and offshore windfarms.

This class initially introduces the circular economy as a framework for the development and management of a sustainable 'waste-as-resource' economic system in which production is designed to be restorative and resilient. The class then proceeds to cover a range of contemporary challenges in the practical application of circular economic principles within different sectors, incorporating presentations from leading practitioners in the field.

The implications of the concept of circular economy for research, policy, business practices and societal transformations towards sustainability are explored in detail through a mix of theory, case studies, individual and group project work. This includes consideration of the role of innovation and knowledge production; social trends and consumer behaviour; conservation and sustainable use of energy and material resources; climate change and environmental sustainability; and the design of business models that maximise product life and value retention.

The class discusses the role of individuals and communities in the making and operation of the circular economy. Students are challenged to identify and critically evaluate opportunities to use waste as an economic good and as the basis for commercially, socially and environmentally profitable business initiatives through the application of creative design; as well as the range of business opportunities arising from repair, reconditioning and remanufacturing activities. The class also introduces the key principles of Life Cycle Assessment (LCA), carbon measurement and management.

Against the background of international commitments on atmospheric emissions, diminishing fossil fuel resources, renewable energy systems deployment and the liberalisation of energy markets, this module examines sustainable options for energy production, supply and consumption. The aim is to give students an understanding of current trends in the energy market, and to enable a critical evaluation of emerging ideas, technologies and policies especially in relation to new and renewable energy supply systems.

This module provides an understanding of the theoretical and operational principles underlying simulation modelling of energy supply and demand systems and their environmental impact. The emphasis is on practical computer lab-based modelling exercises. It covers detailed energy system simulation, supply-demand matching, energy management and monitoring.

TBC

This class is designed to provide a comprehensive overview of spaceflight mechanics, including both orbit and attitude dynamics. The classic two-body problem is solved then used to investigate various modes of orbit transfer and attitude stabilisation for both spin- and 3-axis stabilised spacecraft. The various elements of the class will be brought together to illustrate the mission analysis and design process.

This class is designed to provide a comprehensive overview of spaceflight systems. An overview of the complete spacecraft lifecycle from proposal, through delivery and operations is covered, along with the function and purpose of the spacecraft sub-system level components. The various elements of the class are brought together through the production of competitive proposals for a typical spaceflight system development program.

This module aims to impart an understanding of the underpinning theoretical principles and practical calculation methods for analysis of energy systems and an appreciation of how these systems are integrated in practical applications. Emphasis is on heat transfer and thermodynamic cycles. The underlying principles and analysis methods are appropriate for both renewable and non-renewable energy systems.

This module aims to provide you with:

• principles and methodologies to analyse and evaluate the marine renewable energy sources potential
• principles and methodologies to analyse and compare the main offshore wind, wave, and tidal systems available

This module covers:

• introduction to marine renewable energy systems: context, trends, basic concepts
• offshore wind energy resource characterisation and analysis
• wave energy resource characterisation and analysis
• tidal energy resource characterisation and analysis
• marine Renewable Energy Systems economics: an introduction
• offshore wind turbines: main technologies and modelling approaches
• wave energy converters: main technologies and modelling approaches

At the end of this module you'll be able to:

• analyse the potential of the main marine renewable energy sources (offshore wind, wave, and tidal)
• classify and compare, from a techno-economic point of view, the main offshore wind, wave, and tidal energy systems
• propose a preliminary design of a marine renewable energy system for a given geographical area
• discuss on the main challenges of the experimental testing of marine renewable energy systems
• demonstrate an awareness of the wider, multidisciplinary context for marine renewable energy devices

Assessment and feedback are in the form of:

• quick quizzes for formative feedback
• a class test, mid-way through the module, weighting 40% of the final module mark
• an exam, at the end of the module, weighting 60% of the final module mark