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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Object Orientated Software Engineering: Spatial Algorithms (PGGE11106)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe course assumes a prior working knowledge of the Python 3 programming language. It uses these to develop an understanding of computational algorithms used to manipulate and analyse spatial data and the concepts behind object oriented programming. A range of practical examples are used to identify and utilise generic algorithmic principles across a variety of different spatial data types and problems. Concepts of algorithm efficiency and resource usage and design of clear, maintainable software, are addressed. There is a strong practical emphasis to learning on the course and it is delivered through a sequence of five, four-hour workshops that allow you to iteratively learn about aspects of algorithm design and then to implement these in practice for yourself. PGGE 11234 Technological Infrastructures for GIS or other equivalent experience is a pre-requisite for this course.
Course description Course Description (week by week breakdown of the course) Week 1:

Handling Spatial Data: Introduction to object oriented programming and version control. Simple geometric calculations, range searching and data sorting.

Week 2
Divide and Conquer methods: Binary searching, Recursion, Line generalization.

Week 3
Grid Data and Arrays. Handling, traversing and searching raster data. Point and focal functions.

Week 4
Problem solving by task partitioning. Nearest Neighbour analysis and cartogram generation examples.

Week 5
Hydrological modelling. Using skills learnt to produce a DEM and model water flow.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites It is RECOMMENDED that students have passed Technological Infrastructures for GIS (PGGE11234)
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2018/19, Available to all students (SV1) Quota:  40
Course Start Block 3 (Sem 2)
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 98 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand object oriented programming.
  2. Identify how different spatial data models can be implemented in object-oriented designs
  3. Have an understanding the principles of algorithm development and of generic concepts employed in algorithm design and be familiar with a range of algorithms used to manipulate and analyse spatial data
  4. Be able to develop Python classes suited to the representation and analysis of spatial data.
  5. Be able to undertake spatial data Input/Output in standard formats and to interface Python with other proprietary software and ┐ Be able to complete programming and software documentation within specified parameters and to a professional standard
Reading List
Martelli A, (2009), Python in a Nutshell, O┐Reiley
Lutz M, Learning Python(2009), O┐Reiley
Sedgewick R, and Wayne K (2011):,Algorithms 4th edition
Westra, E 2015 Python GeoSpatial Analysis essentials. Packt publishing
Additional Information
Course URL
Graduate Attributes and Skills Not entered
KeywordsPGGE11106 Algorithms,Java,object oriented design
Course organiserDr Steven Hancock
Tel: (01316)51 7112
Course secretaryMrs Karolina Galera
Tel: (0131 6)50 2572
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