CEG8711 : City Analytics
- Offered for Year: 2019/20
- Module Leader(s): Professor Stuart Barr
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
|Semester 1 Credit Value:||20|
The aims of the module are:
* To develop an understanding of current and future environmental, social and physical pressures faced by cities;
* To understand how modern data management, analysis and modelling approaches can be applied to cities.
Outline Of Syllabus
Cities: spatial and temporal form, function and dynamics.
Environmental, social and physical pressures on and drivers of cities.
Analysis of the social-economic structure of cities.
Population and demographic modelling and simulation.
Simulating the physical form and function of cities.
Intra-urban infrastructure network and systems analytics (transport, energy, water and ICT).
Smart cities and data analytics for real-time data.
Integrated GeoBIM analytics and modelling.
City visualisation and decision support.
Integrate city analytical platforms.
|Guided Independent Study||Assessment preparation and completion||1||2:00||2:00||Exam|
|Guided Independent Study||Assessment preparation and completion||1||25:00||25:00||Project submission on simulation and modelling of cities.|
|Scheduled Learning And Teaching Activities||Lecture||20||1:00||20:00||N/A|
|Guided Independent Study||Assessment preparation and completion||20||0:30||10:00||Revision for exam|
|Scheduled Learning And Teaching Activities||Practical||10||2:00||20:00||N/A|
|Guided Independent Study||Directed research and reading||9||2:00||18:00||Homework questions for review in future lectures/blackboard feedback.|
|Scheduled Learning And Teaching Activities||Workshops||5||1:00||5:00||N/A|
|Guided Independent Study||Reflective learning activity||16||2:00||32:00||Practical and project work preparation|
|Guided Independent Study||Independent study||35||1:00||35:00||Lecture follow-up and reflection|
|Guided Independent Study||Independent study||1||33:00||33:00||Background reading|
Teaching Rationale And Relationship
Lectures provide core knowledge and understanding of the theory and applied understanding of the use of computational analytics for the spatial and temporal analysis and modelling of cities. Practicals allow students to gain skills in the application of analytics software in relation to generating evidence for objective decision-support for cities. Students will be expected to apply independently the gained computational analytics skills to further data sets and projects given. This will enable to enhance the understanding of the methods and learning through the required reflective learning.
The format of resits will be determined by the Board of Examiners
|Written exercise||1||M||40||2000 word report|
Assessment Rationale And Relationship
Exam will assess student understanding of the core principles taught in the module. Practical assessment evaluates students ability to apply analytical approaches to a ’real-world’ situation.